Air Traffic Control Research Articles

Tangible digital twin with shared visualization for collaborative air traffic management operations

In recent years, digital twin technology has become increasingly popular and been widely applied across different industries including air traffic management (ATM). While previous studies on digital twin in ATM focused on factors such as system architecture, synthetic data generation and transfer, and real-time simulation, there is currently a lack of research on visualization and interaction design of digital twin from human factors’ perspective. Moreover, recent advances in virtual and mixed reality (VR/MR) technology give potential for designing interactive digital twin in 3D space that can assist human operators in performing their duties. Therefore, this research aims to explore visualization and interaction design of an MR-based digital twin prototype that can assist air traffic controllers (ATCOs) in carrying out ground control tasks. Specifically, MR headsets (Microsoft HoloLens 2) are leveraged to project out-of-tower view of airport traffic onto a 3D printed airport model at a 1:1 scale. The spatially aligned tangible system enables ATCOs to perform typical ATM operations by directly touching the 3D printed airport model. In addition, collaborative features are implemented into the system, which enable multiple ATCOs to have a shared view of the airport traffic and collaboratively perform ATM operations when wearing the MR headsets. Finally, a user study was conducted with the recruitment of ten licensed ATCOs to investigate usability of the system and ATCOs’ workload, situational awareness and trust when using the system. The feedback from the ATCOs in the user study suggested that: (1) The visual and interactive design were acceptable; (2) The ATCOs indicated varied workload under different scenarios; (3) The ATCOs developed a high level of shared situational awareness with shared view of the system; and (4) The ATCOs were open and confident to use the system in its’ mature form. The findings show that the MR-based tangible airport digital tower system has high potential in collaborative ATM operations by improving user performance and user experience.

Influence of Post-Curing in Nitrogen-Saturated Condition on the Degree of Conversion and Color Stability of 3D-Printed Resin Crowns.

Post-curing is the process of applying extra light to complete the polymerization process of 3D printing. The mechanical properties of light-cured three-dimensional (3D) printed resin can be improved by decreasing the oxygen concentrations during post-curing, and nitrogen-saturated post-curing has been applied for this purpose. This study aimed to evaluate and compare the color stability of 3D-printed resin crowns that were post-cured in both normal air and nitrogen-saturated conditions. Crowns were fabricated with a 3D printer and post-cured in normal air (control group; air) or nitrogen-saturated conditions (experimental group; nitrogen). The specimens in each group were subdivided into four subgroups, each exposed to different discoloration agents: distilled water, coffee, wine, and curry. Post-immersion color changes were measured using a digital spectrophotometer and analyzed using repeated-measures ANOVA. Fourier transform infrared (FT-IR) spectroscopy evaluated the degree of conversion of resin over immersion times for both post-curing conditions. Upon comparing the effects of post-curing conditions, a significant difference between the control and experimental groups in terms of immersion time in the wine and curry subgroups was found. FT-IR analysis showed a significant difference in the degree of conversion between the air and nitrogen groups from 10 to 300 s. These findings suggest that nitrogen-saturated post-curing can potentially enhance the conversion rate of 3D-printed resin crowns, thereby improving their color stability.

Assessment and analysis of accents in air traffic control speech: a fusion of deep learning and information theory.

Enhancing the generalization and reliability of speech recognition models in the field of air traffic control (ATC) is a challenging task. This is due to the limited storage, difficulty in acquisition, and high labeling costs of ATC speech data, which may result in data sample bias and class imbalance, leading to uncertainty and inaccuracy in speech recognition results. This study investigates a method for assessing the quality of ATC speech based on accents. Different combinations of data quality categories are selected according to the requirements of different model application scenarios to address the aforementioned issues effectively. The impact of accents on the performance of speech recognition models is analyzed, and a fusion feature phoneme recognition model based on prior text information is constructed to identify phonemes of speech uttered by speakers. This model includes an audio encoding module, a prior text encoding module, a feature fusion module, and fully connected layers. The model takes speech and its corresponding prior text as input and outputs a predicted phoneme sequence of the speech. The model recognizes accented speech as phonemes that do not match the transcribed phoneme sequence of the actual speech text and quantitatively evaluates the accents in ATC communication by calculating the differences between the recognized phoneme sequence and the transcribed phoneme sequence of the actual speech text. Additionally, different levels of accents are input into different types of speech recognition models to analyze and compare the recognition accuracy of the models. Experimental results show that, under the same experimental conditions, the highest impact of different levels of accents on speech recognition accuracy in ATC communication is 26.37%. This further demonstrates that accents affect the accuracy of speech recognition models in ATC communication and can be considered as one of the metrics for evaluating the quality of ATC speech.

Preliminary design of an ATC support tool for the implementation of the Ad Hoc Separation Minima concept in an en-route sector.

The current aim in response to the anticipated growth in air traffic demand is to expand airspace capacity. However, this poses a challenge, as many airspace volumes are nearing saturation. An influential factor in determining airspace capacity is separation minima, which have remained unchanged for more than two decades. It seems that technological developments in recent years, such as new aircraft capabilities and ATC (Air Traffic Control) support tools, may eventually enhance current separation minima standards. Consequently, there is a push to improve separation management by introducing new operational concepts. Ad Hoc separation minima are one such concept, allowing different separation values to be applied within the same airspace volume based on factors such as aircraft models, weights, and wind conditions, among others. These values are computed individually for each aircraft pair in each situation. Implementing different separation minima values within the same airspace volume requires a significant change in certain ATC activities. In addition, new functionalities or ATC support tools are essential, as Air Traffic Control Officers (ATCO) cannot mentally determine the appropriate separation value for each situation. To address this, a new tool, the Ad Hoc Separation Minima Tool (ASMT), is proposed. It aims to integrate this concept seamlessly into an en-route (ENR) sector without increasing ATCOs workload and altering ATC responsibilities. This study provides a high-level overview of the ASMT architecture, and its functional system has been evaluated in a simulated ENR sector using MATLAB®.

A step-by-step guide to include key electroencephalography (EEG) parameters in the study of human performance applied to air traffic control

The study of human performance of air traffic controllers (ATCOs) is an interesting line of research to improve operational safety. In recent years, there has been an increase in the number of techniques available to develop this research based on massive data analysis. This study presents the use of certain electroencephalography (EEG) parameters to study the human performance of ATCOs. Although software and applications are now available to calculate these parameters, there are often problems in understanding the detailed process used to calculate them. The parameters presented in this study are intended to overcome this limitation and are applicable in real air traffic control (ATC) situations. Six parameters are analysed: excitement, stress, relaxation, boredom, engagement, and attention. As an application case for the parameters, a total of 50 data samples obtained during the development of real-time simulations on a highly realistic ATC platform are analysed. From these data, the above-mentioned EEG parameters and their trends are calculated. In addition, the evolution of these parameters is studied in relation to two other variables that characterise the operational situation of the sector during the simulations: the taskload based on ATC events and the number of simultaneous aircraft in the sector per minute.

Safety and Resilience Bayesian Belief Network (SR-BBN) for ATM

This study delves into the realm of Air Traffic Management (ATM) and its criticality in ensuring the safety and resilience of aviation systems. Traditionally, safety has been approached reactively (Safety I), but with the complexities of socio-technical systems like ATM, a shift towards proactive measures is essential. This research explores Resilience Engineering (RE) and Safety II, emphasizing learning from a system’s adaptability in everyday situations. ATM, a multifaceted system, relies on technology, organization, and human interactions, striving to maintain equilibrium among these pillars for safe and efficient operations. Any changes to these elements can disrupt this balance, necessitating a systemic perspective. Safety in ATM depends on resource availability, timeliness, and coordination among organizations and humans, while resilient performance extends safety beyond the expected operating conditions. To unify safety and resilience, this study introduces the Safety Resilience-Bayesian Network (SR-BBN) model. This model integrates data-driven and knowledge-based approaches, categorizing variables into separations, external factors, nominal conditions, and Air Traffic Controller (ATCO) strategies. The SR-BBN model aids in predicting safety outcomes and identifies influential variables.

Investigating Fatigue in Operational Nightshifts

Abstract: The study investigated sleepiness and fatigue in a single split nightshift arrangement in air traffic control. The arrangement included two mirrored nightshift types, with sleep and operational phases alternating once mid-shift. Sleep duration, subjective sleepiness, and fatigue as well as sustained attention, which have not been thoroughly studied to date, were examined. The findings suggest different sleep strategies. Working during the second part of the night resulted in reduced sleep duration before the shift. Subjective fatigue exhibited varying patterns depending on the shift type and time, with elevated fatigue observed at the start and middle of the shift. However, subjective sleepiness and sustained attention were primarily influenced by the passage of time.

Carbon monoxide affects early cardiac development in an avian model.

Carbon monoxide (CO) is a toxic gas that can be lethal in large doses and may also cause physiological damage in lower doses. Epidemiological studies suggest that CO in lower doses over time may impact on embryo development, in particular cardiac development, however other studies have not observed this association. Here, we exposed chick embryos in ovo to CO at three different concentrations (3, 9, 18 ppm) plus air control (4 protocols in total) for the first 9 days of development, at which point we assessed egg and embryo weight, ankle length, developmental stage, heart weight, ventricular wall thickness, ventricular-septal thickness and atrial wall thickness. We found that heart weight was reduced for the low and moderate exposures compared to air, that atrial wall and ventricular wall thickness was increased for the moderate and high exposures compared to air and that ventricular septal thickness was increased for low, moderate and high exposures compared to air. Ventricular wall thickness was also significantly positively correlated with absolute CO exposures across all protocols. This intervention study thus suggests that CO even at very low levels may have a significant impact on cardiac development.

Long-term effects of chronic exposure to electronic cigarette aerosol on the cardiovascular and pulmonary system in mice: A comparative study to cigarette smoke

Electronic cigarettes (e-cigarettes) have rapidly gained popularity as alternatives to traditional combustible cigarettes. However, their long-term health impact remains uncertain. This study aimed to investigate the effects of chronic exposure to e-cigarette aerosol (ECA) in mice compared to conventional cigarette smoke (CS) exposure. The mice were exposed to air (control), low, medium, or high doses of ECA, or a reference CS dose orally and nasally for eight months. Various cardiovascular and pulmonary assessments have been conducted to determine the biological and prosthetic effects. Histopathological analysis was used to determine structural changes in the heart and lungs. Biological markers associated with fibrosis, inflammation, and oxidative stress were investigated. Cardiac proteomic analysis was applied to reveal the shared and unique protein expression changes in ECA and CS groups, which related to processes such as immune activation, lipid metabolism, and intracellular transport. Overall, chronic exposure to ECA led to adverse cardiovascular and pulmonary effects in mice, although they were less pronounced than those of CS exposure. This study provides evidence that e-cigarettes may be less harmful than combustible cigarettes for the long-term health of the cardiovascular and respiratory systems in mice. However, further human studies are needed to clarify the long-term health risks associated with e-cigarette use.

Feasibility of contrail avoidance in a commercial flight planning system: an operational analysis

Aircraft condensation trails, also known as contrails, contribute a substantial portion of aviation’s overall climate footprint. Contrail impacts can be reduced through smart flight planning that avoids contrail-forming regions of the atmosphere. While previous studies have explored the operational impacts of contrail avoidance in simulated environments, this paper aims to characterize the feasibility and cost of contrail avoidance precisely within a commercial flight planning system. This study leverages the commercial Flightkeys 5D algorithm, developed by Flightkeys GmbH, with a prototypical contrail forecast model based on the Contrail Cirrus Prediction (CoCiP) model to simulate contrail avoidance on 49 411 flights during the first two weeks of June 2023, and 35 429 flights during the first two weeks of January 2024. The utilization of a commercial flight planning system enables high-accuracy estimates of additional cost and fuel investments by operators to achieve estimated reductions in contrail-energy forcing and overall flight global warming potential. The results show that navigational contrail avoidance will require minimal additional cost (0.08%) and fuel (0.11%) investments to achieve notable reductions in contrail climate forcing (−73.0%). This simulation provides evidence that contrail mitigation entails very low operational risks, even regarding fuel. This study aims to serve as an incentive for operators and air traffic controllers to initiate contrail mitigation testing as soon as possible and begin reducing aviation’s non- CO2 emissions.

E-Cigarette Exposure Alters Neuroinflammation Gene and Protein Expression in a Murine Model: Insights from Perinatally Exposed Offspring and Post-Birth Mothers.

The use of E-cigarettes, often considered a safer alternative to traditional smoking, has been associated with high rates of cellular toxicity, genetic alterations, and inflammation. Neuroinflammatory impacts of cigarette smoking during pregnancy have been associated with increased risks of adverse childhood health outcomes; however, it is still relatively unknown if the same propensity is conferred on offspring by maternal vaping during gestation. Results from our previous mouse inhalation studies suggest such a connection. In this earlier study, pregnant C57BL/6 mice were exposed daily to inhaled E-cig aerosols (i.e., propylene glycol and vegetable glycerin, [PG/VG]), with or without nicotine (16 mg/mL) by whole-body inhalation throughout gestation (3 h/d; 5 d/week; total ~3-week) and continuing postnatally from post-natal day (PND) 4-21. As neuroinflammation is involved in the dysregulation of glucose homeostasis and weight gain, this study aimed to explore genes associated with these pathways in 1-mo.-old offspring (equivalent in humans to 12-18 years of age). Results in the offspring demonstrated a significant increase in glucose metabolism protein levels in both treatment groups compared to filtered air controls. Gene expression analysis in the hypothalamus of 1 mo. old offspring exposed perinatally to E-cig aerosols, with and without nicotine, revealed significantly increased gene expression changes in multiple genes associated with neuroinflammation. In a second proof-of-principal parallel study employing the same experimental design, we shifted our focus to the hippocampus of the postpartum mothers. We targeted the mRNA levels of several neurotrophic factors (NTFs) indicative of neuroinflammation. While there were suggestive changes in mRNA expression in this study, levels failed to reach statistical significance. These studies highlight the need for ongoing research on E-cig-induced alterations in neuroinflammatory pathways.

Features of scientific research work of future aviation specialists

The article presents the peculiarities of research work of future aviation specialists. It is noted that higher education institutions in the aviation field pay considerable attention to ensuring the scientific and research component of the use of modern educational technologies for the professional training of future specialists. The purpose of the study was the analysis and peculiarities of the research work of aviation institutions of higher education, aimed at the formation of research skills and professional skills. The methods of research were the analysis and generalization of scientific literature on the organization of research work in higher education, ICAO documents regulating the flight safety management system for air transport. Features of research work for students of higher education at aviation institutions are singled out, in particular: application of the problem-based learning method through the analysis of aviation regulatory documents and investigation materials of aviation events; simulation of real professional situations through a business game (imitation simulation), where the student is given the opportunity to be a pilot, air traffic controller, dispatcher-instructor, aviation shift leader, etc.; student conferences as an opportunity to present professional research work; simulator (practical) training; the practically oriented character of the educational program – the involvement and use of the work experience of aviation specialists-practitioners. The criteria for ensuring the effective organization and implementation of research work of future aviation specialists are summarized, which is the complexity, consistency and comprehensiveness of learning and use of methods and technologies of conducting scientific research, implementation of their results, the continuity of research work according to training courses, the logic of the complication of methods, types and forms of scientific creativity

Development and validation of a method for the quantitative determination of metoprolol succinate in the air of the working area by high-performance liquid chromatography using mass spectra

Introduction. Metoprolol is a cardioselective blocker of β-adrenergic receptors. Drugs containing metoprolol have hypotensive, antianginal, antiarrhythmic effects. Moderately dangerous when taken orally, has a general toxic effect. Metoprolol is produced in two forms: in the form of salts of tartaric and succinic acids, the approximate safe level of exposure to which is 0.3 mg/m3. To ensure the safety of workers, it is necessary to carry out sanitary and hygienic air control. Methods for the quantitative analysis of metoprolol in the air of the working area, presented in the current scientific literature, allow monitoring only for metoprolol salts in the form of tartrate. 
 The aim of the study is to develop and validate an analytical method for the quantitative determination 
 of metoprolol succinate in the air of the working area by HPLC-MS. 
 Materials and methods. For the analysis, standard samples of metoprolol succinate and air samples taken at all stages of the life cycle of the production of the drug metoproolol were used. Chromatographic separation and detection were performed on an Agilent 1260 Infinity G6125B high performance liquid chromatograph (Agilent Technologies, USA) equipped with a column and sample thermostat, a degasser, a pump, an autosampler, and a G6125B mass selective detector. A Waters Xbridge® C18 3.5 µm column was used; 2.1×30 mm (Waters, Ireland). Primary data were processed using Open Lab CDS ChemStation Edition (Rev. C.01.07 SR3) software (Agilent Technologies, USA).
 Results. A method for the quantitative determination of metoprolol succinate in air samples by HPLC-MS has been developed and validated. During the validation of the developed methodology, it was found that the validation characteristics (specificity, linearity, accuracy and precision, correctness, reproducibility) are within the acceptance criteria. The analytical range of the technique was 0.1–10.0 µg/ml and allows the developed technique to be used to control the average shift MPCs in the air of the working area.
 Limitations. The results of the study of the air in the working area are applicable only to the production of the drug metoprolol in the form of tablets; the study of air during the synthesis and packaging of the active pharmaceutical substance was not carried out. 
 Conclusion. An analysis of air samples from the production of the drug metoprolol was carried out and the safety of working conditions was proved.

Microglial reactivity in brainstem chemosensory nuclei in response to hypercapnia.

Microglia, the resident immune cells of the CNS, surveil, detect, and respond to various extracellular signals. Depending on the nature of these signals, an integrative microglial response can be triggered, resulting in a phenotypic transformation. Here, we evaluate whether hypercapnia modifies microglia phenotype in brainstem respiratory-related nuclei. Adult C57BL/6 inbred mice were exposed to 10% CO2 enriched air (hypercapnia), or pure air (control), for 10 or 30min and immediately processed for immunohistochemistry to detect the ubiquitous microglia marker, ionized calcium binding adaptor molecule 1 (Iba1). Hypercapnia for thirty, but not 10min reduced the Iba1 labeling percent coverage in the ventral respiratory column (VRC), raphe nucleus (RN), and nucleus tractus solitarius (NTS) and the number of primary branches in VRC. The morphological changes persisted, at least, for 60min breathing air after the hypercapnic challenge. No significant changes were observed in Iba1+ cells in the spinal trigeminal nucleus (Sp5) and the hippocampus. In CF-1 outbred mice, 10% CO2 followed by 60min of breathing air, resulted in the reduction of Iba1 labeling percent coverage and the number and length of primary branches in VRC, RN, and NTS. No morphological change was observed in Iba1+ cells in Sp5 and hippocampus. Double immunofluorescence revealed that prolonged hypercapnia increased the expression of CD86, an inflammatory marker for reactive state microglia, in Iba1+ cells in VRC, RN, and NTS, but not in Sp5 and hippocampus in CF-1 mice. By contrast, the expression of CD206, a marker of regulatory state microglia, persisted unmodified. In brainstem, but not in hippocampal microglia cultures, hypercapnia increased the level of IL1β, but not that of TGFβ measured by ELISA. Our results show that microglia from respiratory-related chemosensory nuclei, are reactive to prolonged hypercapnia acquiring an inflammatory-like phenotype.

Surface Degradation of Ion-releasing Restorative Materials With Cariogenic Challenge.

This study examined the influence of cariogenic environments on the surface roughness of ion-releasing restorative materials (IRMs). Custom-made stainless steel molds with holes of 5 mm × 2mm were used to fabricate 60 disc-shaped specimens of each of the following materials: Activa Bioactive (AV), Beautifil Bulk Restorative (BB), Cention N (Bulk-fill) (CN), and Filtek Z350XT (FZ) (Control). Baseline surface roughness (Ra) measurements were obtained using an optical 3D measurement machine (Alicona Imaging GmbH, Graz, Austria). The specimens were then randomly divided into five subgroups (n=12) and exposed to 10 ml of the following mediums at 37°C: distilled water (DW), demineralization solution (DM), remineralization solution (RM), pH cycling (PC) and air (AR) (control). Ra measurements were again recorded after one week and one month, followed by statistical evaluations with two-way analysis of variance (ANOVA) to determine interactions between materials and mediums. One-way ANOVA and post hoc Games Howell tests were performed for intergroup comparisons at a significance level of 0.05. Mean Ra values ranged from 0.085 ± 0.004 (µm) to 0.198 ± 0.001 µm for the various material-medium combinations. All IRMs showed significant differences in Ra values after exposure to the aqueous mediums. The smoothest surfaces were observed in the AR for all materials. When comparing materials, AV presented the roughest surfaces for all mediums. All IRM materials showed increased surface roughness over time in all cariogenic environments but were below the threshold value for bacterial adhesion, except for AV 1-month post immersion with pH cycling. Therefore, besides AV, the surface roughness of IRMs did not deteriorate to an extent that it is clinically relevant.

Swarm Division-Based Aircraft Velocity Obstacle Optimization Considering Low-Carbon Emissions

In the pursuit of sustainable aviation, this paper presents an innovative approach that adopts a swarm division strategy to enhance and refine the velocity obstacle (VO) method, guided by a low-carbon principle. A dynamic elliptical protection zone model forms the core of this innovative approach. Specifically, this dynamic elliptical protection zone is created based on the difference in aircraft velocity, and a swarm division strategy is introduced in this process. Initially, aircraft that share the same route and type, and have similar velocities and distances, are grouped into swarms. Then, the characteristics of the swarms, such as mass points, velocities, and protection zones, are recorded. Second, the collision cone (CC) between swarms is established, and planar geometrical analysis is used to determine the optimal relief velocity and heading of aircraft on the low-carbon objective while ensuring a safe interval between aircraft in the swarm during the relief period. Additionally, a swarm control algorithm is utilized to adjust the velocity of the aircraft by a small margin. Finally, simulation experiments are conducted using Python, revealing that the swarm relief efficiency of the enhanced VO method sees a notable increase of over 33%. Concurrently, the need for adjustments decreases by an average of 32.78%, while fuel savings reach as high as 70.18%. The strategy is real-time and operational, significantly reduces the air traffic controller (ATC) workload, improves flight efficiency and safety, and contributes positively to the reduction in carbon emissions, which is beneficial for the environment.

How to measure and control indoor air quality based on intelligent digital twin platforms: A case study in China

In order to address the current disparity between indoor air quality assessment, prediction, and control, this study proposes an intelligent management approach for indoor air quality based on digital twin platforms. By collecting and fusing multi-level, and multi-dimensional data at the physical level, a comprehensive data integration and analysis platform is established in the digital realm, encompassing the ‘Sense-Integrate-Retrieve-Analyze-Feedback’ framework. Various digital technologies, such as the Internet of Things (IoT), Building Information Modeling (BIM), and machine learning, are utilized to integrate and visualize multi-source heterogeneous data through a lightweight web-based interface so that data retrieval, rapid prediction, and intelligent control are feasible based on various backend algorithm models. Compared to traditional measurement methods, this system offers broader spatiotemporal coverage, increased mobility, and less disruption to physical infrastructure, which underscores the sophistication of monitoring technology, data integration, and environmental management. The proposed intelligent platform has been validated in a traditional Chinese dwelling, and practical results demonstrate that most air quality problems occur in the early morning of winter while this system can swiftly predict and issue control signals for adjustments in occupied spaces exceeding predefined healthy thresholds. Field measurements confirmed that most air quality problems can be solved within 30 min after their appearance. By eliminating data silos through real-time synchronization and remote intelligent control via the digital platform, it bridges the gap between problem identification by managers and problem resolution by end-users, ensuring timely responses to indoor air quality concerns.

Attenuated incubation of ethanol-induced conditioned taste aversion in a model of dependence.

Preclinical studies report attenuated ethanol-induced conditioned taste aversion (CTA) following chronic ethanol exposure, suggesting that tolerance develops to the aversive properties of ethanol. However, these studies are confounded by pre-exposure to the unconditioned stimulus (US; ethanol), which is well known to hinder conditioning. This study was designed to determine whether chronic ethanol exposure produces tolerance to the aversive properties of ethanol in the absence of a US pre-exposure confound. CTA was performed in adult male and female Long-Evans rats by pairing 0.1% ingested saccharin with an intraperitoneal injection of ethanol (1.5 or 2.0g/kg) or saline. Rats were then rendered ethanol dependent using chronic intermittent ethanol (CIE) vapor exposure. Controls were exposed to room air (AIR). The effect of chronic ethanol on CTA expression and reconditioning were examined following vapor exposure. Prior to vapor exposure, both sexes developed CTA to a comparable degree with 2.0g/kg producing greater CTA than 1.5g/kg ethanol. Following vapor exposure, AIR controls exhibited an increase in CTA magnitude compared to pre-vapor levels. This effect was largely absent in CIE-exposed rats. Re-conditioning after vapor exposure facilitated increased CTA magnitude to a similar degree in AIR- and CIE-exposed males. In contrast, CTA magnitude was unchanged by re-conditioning in females. These data suggest that chronic ethanol does not facilitate tolerance to the aversive properties of ethanol but rather attenuates incubation of ethanol-induced CTA. Loss of CTA incubation suggests that CIE exposure disrupts circuits encoding aversion.

Adaptable automation for a more human-centered work design? Effects on human perception and behavior

This experiment systematically examines whether, in safety-critical environments such as Air Traffic Control, the negative effects of increasing automation associated with static automation concepts can be mitigated by adaptable automation. Adaptable automation is a form of flexible automation in which the human operator (rather than the system as in adaptive automation) can decide when and to what extent to delegate tasks. A special focus is on its effects on human perception in terms of perceived autonomy and competence, satisfaction, and human role perception. We conducted two online studies using the same dual-task paradigm. Study 1 was conducted with a novice sample via Prolific (N = 93) and study 2 with an expert sample of Air Traffic Controllers (N = 126). Participants were either supported by static information automation, static decision automation, or an adaptable solution that allowed them to switch between the two automation stages. The findings of both studies are similar. Results indicated that, even when humans rarely switched, adaptable automation could increase perceived autonomy, led to high satisfaction, and had positive effects on role perceptions without impairing performance or workload. Furthermore, satisfaction was found to correlate with performance. From a human-centered perspective, flexible concepts seem to be particularly suitable when automation increasingly takes over parts of a job task not only at the stage of information analysis but also at the stage of decision-making.

Development of novel compact wind tunnel for testing efficacy of insecticide formulated products in mosquitoes.

Ultra-low volume (ULV) space sprays aerosolize insecticide formulated products (FP) to contact flying mosquitoes, while barrier sprays expose mosquitoes to FP residue on vegetation and other surfaces. Centers for Disease Control and Prevention bottle bioassays used to assess insecticide resistance are based on residual active ingredient (AI) exposure and do not directly relate to FP efficacy. The current pilot study developed a novel compact wind tunnel for mosquito exposure to FP. Caged Aedes albopictus and Culex pipiens/quinquefasciatus were exposed to undiluted Biomist®3 + 15 FP (permethrin AI) or air (control) within the wind tunnel, transferred to new cages, and held in a 28 °C incubator. Separate mosquitoes were exposed to residual permethrin AI (8 μg mL-1) in bottle bioassays. Mortality was monitored 15, 30, 60, and 120 min post-exposure. Chi-square tests (P < 0.05) showed significantly higher mortality in Aedes compared to Culex populations for most time points in both bioassay and wind tunnel exposure groups. As expected, mosquitoes exposed to Biomist®3 + 15 showed higher mortality rates than bottle bioassay exposure to permethrin. Two Culex colonies resistant to permethrin in bottle bioassays were susceptible to Biomist®3 + 15 in the wind tunnel. The novel compact wind tunnel developed here may be an alternative to field trials for testing FP efficacy, avoiding factors such as weather, logistical planning, and extended personnel hours. The wind tunnel could allow programs to conveniently test efficacy of multiple FP. Comparisons of different insecticide exposure methods provide practical information to inform operational decisions. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.