Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre.In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.

The DRACO Door: Design, Test, and Integration of the Mechanism on the DART Spacecraft

The Double Asteroid Redirection Test (DART) mission is NASA's first planetary defense mission to demonstrate the viability of kinetically impacting an asteroid and deflecting its trajectory. The DART spacecraft successfully launched on November 24, 2021 from the Vandenberg Space Force Base and successfully made impact on Dimorphos, the smaller asteroid in the Didymos system, on September 26, 2022. The DART spacecraft has one instrument called Didymos Reconnaissance and Asteroid Camera for Optical navigation (DRACO). DRACO is an imaging telescope that, in conjunction with the SMART Navigation algorithm, autonomously guided the DART spacecraft to the asteroid. Because DRACO is a mission critical and light sensitive instrument, the DRACO Door mechanism was designed as the protective cover. The door functions to shield DRACO from stray light during launch, to deploy in space once when commanded, and to stay 180 degrees open for the duration of the mission. The DRACO Door went through several iterations during the design phase with decisions on various components such as Frangibolts ®, torsion springs, hardstops, and latches. After fabrication and assembly, the door went through a rigorous environmental testing plan, which included deployment testing, vibration testing, and thermal vacuum testing. After successful qualification of the mechanism, the door was installed and integrated into the DART spacecraft. It should be noted that during the fabrication of the mechanism piece-parts, the COVID-19 pandemic began, and the effects of the pandemic were seen in the challenges faced during the DRACO door assembly and testing. Under the constraints of the pandemic, the DART spacecraft was successfully built, tested, and launched, and the DRACO door was successfully deployed on December 7, 2021. The door has continued to function as intended. This paper will discuss the design choices behind the door components, the environmental qualification test program, and the installation of the door onto the DART spacecraft. In addition, this paper will discuss the lessons learned and the challenges of fabricating and testing the flight hardware. © 2023 IEEE.

Stress Factors and the Impacts of COVID-19 Pandemic: A Review on the Aviation Industry

This study outlines the stress factors and the impact of the COVID-19 pandemic on the stress variables among aviation workers, which includes airline employees, flight crews, pilots, maintenance crews, air traffic controllers, airport or ground workers, engineers, training personnel, and other aviation-related personnel. A review was done on 37 research papers using systematic literature review (SLR) and discovered nine stress factors among aviation workers which are working hours, workloads, internal factors, ergonomic issues, job uncertainty, job demands, organizational issues, team conflict, and the COVID-19 itself. The findings of this study could provide insights to employers in the aviation industry for mitigation actions that could help to successfully reduce and eliminate stress factors in the workplace. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Dual-band Air-Ground Radio Performance: Example Flight Test Results

We recently concluded a four-year University Leadership Initiative (ULI) project sponsored by NASA, which investigated multiple aviation communications technology areas aimed at enhancing future aviation safety. These areas were dual-band air-ground communications for air traffic management, detection and interdiction of small drones, and high-capacity terrestrial airport communications networking. In this paper we report on flight test results of our dual-band radios. These radios were designed to use a spectrally efficient multi-carrier modulation, filterbank multicarrier (FBMC), which we had previously shown to improve resilience to high-power distance measurement equipment (DME) adjacent-channel interference, in comparison to existing orthogonal frequency division multiplexing (OFDM) schemes. In our NASA project, we designed the FBMC radios to extend performance even further, using the following techniques: (i) simultaneous dual-band transmission and reception;(ii) ground station (GS) spatial diversity;(iii) higher-order modulation for a factor of 5 capacity increase over QPSK;(iv) a Doppler-resilient option using a smaller number of subcarriers;and, (v) 5-MHz bandwidth C-band transmissions for an order of magnitude capacity increase over existing 500-kHz channel schemes. To our knowledge, these are novel achievements for civil aviation, and our flight test results attained a technology readiness level (TRL) of 5. In this paper we briefly describe the project history, in which we spent approximately one year working with Boeing to participate in one of their Eco-Demonstrator flight trials, and obtained special temporary authorizations to transmit in both the L-band and C-band, from the FAA, the FCC, and the DoD. When COVID-19 dispersed worldwide, Boeing was no longer able to support us, so we revised our plans and teamed with the South Carolina Civil Air Patrol (SC CAP) to conduct smaller-scale flight tests. This paper summarizes the radio designs and the novel features we employed, as well as analyses, computer simulations, and laboratory tests prior to terrestrial mobile testing, all of which culminated in our successful flight tests. We show example flight test results that serve as proof of concept for all the five aforementioned radio performance enhancements. Example results include signal-to-noise ratio and bit error ratio, diversity gains, and throughput gains through both higher-order modulation and wider bandwidth channels. We also report on some lessons learned, and some ideas for future advancement of our work. © 2023 IEEE.

Meeting report: Flight Safety Foundation International Air Safety Summit, Atlanta, GA, November 7-9, 2022

Flight Safety Foundation's 75th annual International Air Safety Summit (IASS;https://flightsafety.org/) was held November 7-9, 2022, at the Omni Atlanta Hotel at CNN Center in Atlanta, GA, USA. The IASS 2022 agenda featured presentations and panel discussions on a range of safety-related topics with an emphasis on the industry's ongoing recovery from the COVID-19 pandemic and the recognition that the mental and emotional well-being of personnel and the development and maturation of robust organizational safety cultures are important elements of the safety landscape. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Flight-to-quality or not? Evidence from China's green bond and green equity markets during COVID-19 crisis

This study investigates the time-varying interdependence relationships between green bonds and green equity returns in China before and during the COVID-19 period. The rolling-window Copula Quantile-on-Quantile regression method has been employed to capture the dynamic dependence structure of the asset returns. The empirical results are as follows: First, the green bond-green equity correlations have increased significantly during the COVID-19 pandemic era. Second, the heterogeneous dependencies across different quantiles show the time-varying information transmission mechanism between green financial markets depending on the market conditions. Specifically, the correlations have increased around median level given pandemic shocks and an opposite correlation movement can be found in extreme quantiles, supporting the ‘flight-to-quality' effect.

Lt Gen Kamal Davar says... India and the new geopolitical churnings

According to the WHO, this virus still exists in many parts of the globe in some form or the other. After the end of the Cold War in the early 90s, the global geopolitical and geo-economic divide, consequent to the ongoing Russo-Ukraine War, has never been so harshly polarised. [...]it is pertinent to note what President Xi had spoken recently in the National People's Congress stating that he will endeavour to "more quickly elevating the armed forces to world-class standards-and make it a great wall of steel." Importantly, for decades, India does carry some moral authority with itself with its foreign policy based on the Nehruvian concept of nonalignment now aptly called 'strategic autonomy' which has been long respected by the 'third world' now referred to as the 'global south'.

Improved Barnacle Mating Optimizer-Based Least Square Support Vector Machine to Predict COVID-19 Confirmed Cases with Total Vaccination

Every country must have an accurate and efficient forecasting model to avoid and manage the epidemic. This paper suggests an upgrade to one of the evolutionary algorithms inspired by nature, the Barnacle Mating Optimizer (BMO). First, the exploration phase of the original BMO is enhanced by enforcing and replacing the sperm cast equation through Levy flight. Then, the Least Square Support Vector Machine (LSSVM) is partnered with the improved BMO (IBMO). This hybrid approach, IBMO-LSSVM, has been deployed effectively for time-series forecasting to enhance the RBF kernel-based LSSVM model since vaccination started against COVID-19 in Malaysia. In comparison to other well-known algorithms, our outcomes are superior. In addition, the IBMO is assessed on 19 conventional benchmarks and the IEEE Congress of Evolutionary Computation Benchmark Test Functions (CECC06, 2019 Competition). In most cases, IBMO outputs are better than comparison algorithms. However, in other circumstances, the outcomes are comparable.

COVID-19 Disease Prediction Utilizing Dilated Convolution Neural Network Based Levy Flight Tunicate Swarm Optimization.

The worldwide pandemic of COVID-19 illness has wreaked havoc on the health and lives of countless individuals in more than 200 countries. More than 44 million individuals have been afflicted by October 2020, with over 1,000,000 fatalities reported. This disease, which is classified as a pandemic, is still being researched for diagnosis and therapy. It is critical to diagnose this condition early in order to save a person's life. Diagnostic investigations based on deep learning are speeding up this procedure. As a result, in order to contribute to this sector, our research proposes a deep learning-based technique that may be employed for illness early detection. Based on this insight, gaussian filter is applied to the collected CT images and the filtered images are subjected to the proposed tunicate dilated convolutional neural network, whereas covid and non-covid disease are categorized to improve the accuracy requirement. The hyperparameters involved in the proposed deep learning techniques are optimally tuned using the proposed levy flight based tunicate behaviour. To validate the proposed methodology, evaluation metrics are tested and shows superiority of the proposed approach during COVID-19 diagnostic studies.

Neural patterns of threat response in adolescents predict vulnerability for and resilience against internalizing symptoms during COVID-19 waves

Defensive stress reactions, such as freezing and active fight-or-flight, are relevant for coping with threat. Action-preparatory activity supporting these reactions, including the amygdala, has been posited as a potential marker for stress-resilience. We considered the successive COVID-19 lockdowns as two pervasive stressors, to prospectively investigate the predictive value of neural threat-responses towards symptom development. Five years prior to the COVID-19 pandemic, 17-year-old adolescents (n = 64, Baseline-17) performed the fMRI-adapted Go/Nogo Under Threat (GUNT) task, where threat-anticipatory freezing reactions and transition to action are evoked to avoid a shock. A majority (n = 44) made themselves available for follow-up assessments before COVID (Baseline-20, age 20), during the first COVID-19 lockdown in the Netherlands (LD1, age 22.5), and during a second lockdown (LD2, age 23). The GUNT task quantified neural (thalamic, subcortical, amygdala) and physiological (bradycardia) markers of threat-anticipatory freezing and transition to action (mediated by anterior cingulate cortex). Threat-anticipatory amygdala responses (Baseline-17) were linked to stressor resilience, as quantified by self-reported anxiety symptoms between LD1 and LD2. However, stronger amygdala responses to low threat cues (Baseline-17) were associated with stronger anxiety symptoms. These effects occurred over and above early-life stress, COVID-19 stress burden, and overall symptom changes between age 17 and 20. These findings suggest that amygdala responses to acute threat provide a marker for resilience against real-life stressors, with adequate threat discrimination signaling resilience and stronger amygdala responses to low threat predicting vulnerability. The findings support the notion that neural responses to threat are instrumental for adaptive coping with pervasive stress.

Support vector regression model for flight demand forecasting

Flight demand forecasting is a particularly critical component for airline revenue management because of the direct influence on the booking limits that determine airline profits. The traditional flight demand forecasting models generally only take day of the week (DOW) and the current data collection point (DCP) adds up bookings as the model input and uses linear regression, exponential smoothing, pick-up as well as other models to predict the final bookings of flights. These models can be regarded as time series flight demand forecasting models based on the interval between the current date and departure date. They fail to consider the early bookings change features in the specific flight pre-sale period, and have weak generalization ability, at last, they will lead to poor adaptability to the random changes of flight bookings. The support vector regression (SVR) model, which is derived from machine learning, has strong adaptability to nonlinear random changes of data and can adaptively learn the random disturbances of flight bookings. In this paper, flight bookings are automatically divided into peak, medium, and off (PMO) according to the season attribute. The SVR model is trained by using the vector composed of historical flight bookings and adding up bookings of DCP in the early stage of the flight pre-sale period. Compared with the traditional models, the priori information of flight is increased. We collect 2 years of domestic route bookings data of an airline in China before COVID-19 as the training and testing datasets, and divide these data into three categories: tourism, business, and general, the numerical results show that the SVR model significantly improves the forecasting accuracy and reduces RMSE compared with the traditional models. Therefore, this study provides a better choice for flight demand forecasting.

High Time-Resolution Monitoring of Volatile Organic Compounds During Multi-Surface Disinfection Activities in Buildings with PTR-TOF-MS

Increased usage of chemical disinfectants during the COVID-19 pandemic may impact the chemical composition of indoor air in residential and commercial buildings. This study characterized gas-phase concentrations of volatile organic compounds (VOCs) during multi-surface disinfection activities in a tiny house research facility. This unique facility provided a controlled, yet realistic environment for simulating whole-building disinfection events. VOCs were measured in real-time (1 Hz) in the bulk air of the tiny house with a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS). In addition, particle number (PN) size distributions were measured with a high-resolution electrical low-pressure impactor (HR-ELPI+). PTR-TOF-MS measurements demonstrate that chemical disinfectant spray products applied to multiple surfaces can substantially increase indoor VOC concentrations. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Analyzing factors affecting charter flight service demand: A case of Taiwan

Global charter flight demand remined relatively stable over the last decades, and international charter flight is an integrated product of the aviation and tourism industries. To better understand charter flight tourism in Asia, this study analyses key reasons affected Taiwan's charter flight demand from Japan, South Korea, Malaysia, and Singapore during the period 2009‒2018, with a consideration of aviation- and tourism-related variables. Empirical results show that the reduction in scheduled flight aircraft size stimulated new charter flight demand to Taiwan, offsetting the negative effects caused by scheduled seat increment to a certain degree. This study contributes to literature by exploring the impact of scheduled flight service availability on charter flight demand, and further enriches our understanding of the impact of scheduled flight services on international tourist arrivals in terms of aircraft size. Importantly, it has implications for policymakers and stakeholders involved in charter business, assisting them in facilitating aviation and tourism recovery during the post-COVID-19 era.

Analytical and biomedical applications of microfluidics in traditional Chinese medicine research

Traditional Chinese medicine (TCM) has significant benefits in the prevention and treatment of diseases due to its unique theoretical system and research techniques. However, there are still key issues to be resolved in the full interpretation and use of TCM, such as vague active compounds and mechanism of action. Therefore, it is promising to promote the research on TCM through innovative strategies and advanced cutting-edge technologies. Microfluidic chips have provided controllable unique platforms for biomedical applications in TCM research with flexible composition and large-scale integration. In this review, the analysis and biomedical applications of microfluidics in the field of TCM are highlighted, including quality control of Chinese herbal medicines (CHMs), delivery of CHMs, evaluation of pharmacological activity as well as disease diagnosis. Finally, potential challenges and prospects of existing microfluidic technologies in the inheritance and innovation of TCM are discussed.Copyright © 2022 Elsevier B.V.

Take-off, turbulence and turnaround

PurposeThe aim of this paper is to explore the evolving nature of the work of cabin crew in a Scandinavian carrier in three eras, drawing on theories of gender and emotional labour.Design/methodology/approachThe paper draws on ethnographic data from fieldwork, interviews and documents.FindingsFrom being a feminized and temporary occupation for young, upper- and middle-class women in the 1970s, the occupation became a full-time job and with greater diversity of cabin crew. Today there are signs of the job becoming a precarious and temporary one of demanding and devalorized work in a polarized and class-divided labour market. Changing circumstances impact on the emotional labour requirement and terms and conditions at work.Research limitations/implicationsA limitation is that the research design was not initially longitudinal in the sense that the author does not have exactly the same kind of data from each era. The author has, however, been involved in this field for two decades, used multiple methods and interacted with different stakeholders and drew on a unique data material.Practical implicationsThe development in aviation is contributing to new discriminatory practices, driving employee conditions downwards and changing the job demands. This development will have practical consequences for the lives and families of cabin crew.Social implicationsThe analysis illustrates how work ‘constructs' workers and contributes in creating jobs that are not sustainable for the employees. Intensification of work, insecurity and tougher working conditions also challenge key features in the Nordic model such as proper pay, decent work and a life-long employment. Much indicates that the profession is again becoming a temporary one of demanding work with poor working conditions in a polarized and class-divided labour market.Originality/valueThe research contributes to the literature on emotional labour, gender and the evolving nature of the work of cabin crew. The unique data material, the longitudinal aspect of the research and the focus on a single network carrier are good in charting changes over time.

A Mission-Oriented Flight Path and Charging Mechanism for Internet of Drones.

In addition to traditional battery exchange services and stationary charging stations, researchers have proposed wireless charging technology, such as decentralized laser charging or drone-to-drone charging in flight, to provide power to drones with insufficient battery electricity. However, the charging methods presented in the literature will inevitably cause drones to wait in line for charging during peak hours and disrupt their scheduled trips when the number of drones grows rapidly in the future. To the best of our knowledge, there have been no integrated solutions for drone flight path and charging planning to alleviate charging congestion, taking into account the different mission characteristics of drones and the charging cost considerations of drone operators. Accordingly, this paper provides adaptive charging options to help drone operators to solve the above-mentioned problems. Drones on ordinary missions can use conventional battery swap services, wired charging stations, or electromagnetic wireless charging stations to recharge their batteries as usual, whereas drones on time-critical missions can choose drone-to-drone wireless charging or decentralized laser charging deployed along the fight paths to charge the batteries of drones in flight. Notably, since fixed-wing drones have larger wing areas to install solar panels, they can also use solar energy to charge during flight if the weather is clear. The simulation results exhibited that the proposed work reduced the power load of the power grid during peak hours, met the charging needs of each individual drone during flight, and cut down the charging costs of drone operators. As a result, an all-win situation for drone operators, drone customers, and power grid operators was achieved.

Stock-bond dependence and flight to/from quality

This paper investigates the stock-bond dependence structure using a dependence-switching copula model. The model allows stock-bond dependence to switch between positive dependence regimes (contagions or crashes of the two markets during downturns or booms in both markets during upturns) and negative dependence regimes (flight-to-quality from stock markets to bond markets or flight-from-quality from bond markets to stock markets). Using data from four developed markets including the US, Canada, Germany, and France for the period between January 1985 and August 2022, we find that the within-country stock-bond (extreme) dependence could be both positive and negative. In the positive dependence regimes, the stock-bond dependence is asymmetric with stronger left tail dependence than the right tail dependence, giving evidence of a higher likelihood of joint stock-bond market crashes or contagions during market downturns than the collective stock-bond market booms. Under the negative dependence regimes, we find both flight-from-quality and flight-to-quality, with flight-to-quality being more dominant in the North American markets while flight -from-quality is more prominent in the European markets. Further, the dependence switches between positive and negative regimes over time. Moreover, the dependence is mainly in the positive regimes before 2000 while mostly in the negative regimes after that, indicating contagions mostly before 2000 and flights afterwards. Further, the dependence switches between positive and negative regimes around financial crises and the COVID-19 pandemic. These results greatly enrich the findings in the existing literature on the co-movements of stock-bond markets and are important for risk management and asset pricing.

National Capital Section Presents Future City 2023 SpeciaI Award

Future City organizations and teams have returned to normal activities this year after Covid;and have reorganized and conducted a very successful Future City 2023 Competition. On 19 February, regional Future City winners from 41 middle schools and after-school organizations (eg, scouts, 4H, boys/girls clubs) from nationwide and China participated in the Future City National Finals. The Special Awards judging was done in person in Washington DC. In its 31st year Future City has engaged middle school in STEM and diversity. This year's Future City theme was "Climate Change Challenge." Middle school students were asked to create cities of the future, first on a computer and then as large tabletop models. Working in teams with a teacher and volunteer engineer mentor, students create their cities using the SimCity 3000 TM video game donated to all participating schools by Electronic Arts, Inc., of Redwood City CA.

An Electric Vehicle Assisted Charging Mechanism for Unmanned Aerial Vehicles

The global greenhouse effect and air pollution problems have been deteriorating in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have also announced the ban on the sale of vehicles powered by fossil fuels in the next few decades, to effectively alleviate the global greenhouse effect and air pollution problems. In addition to electric vehicles (EVs) that will replace traditional fuel vehicles as the main ground transportation vehicles in the future, unmanned aerial vehicles (UAVs) have also gradually and more recently been widely used for military and civilian purposes. The recent literature estimated that UAVs will become the major means of transport for goods delivery services before 2040, and the development of passenger UAVs will also extend the traditional human ground transportation to low-altitude airspace transportation. In recent years, the literature has proposed the use of renewable power supply, battery swapping, and charging stations to refill the battery of UAVs. However, the uncertainty of renewable power generation cannot guarantee the stable power supply of UAVs. It may even be very possible that a large number of UAVs need to be charged during the same period, causing congestion in charging stations or battery swapping facilities and delaying the arranged schedules of UAVs. Although studies have proposed the method of that employing moving EVs along with wireless charging technology in order to provide electricity to UAVs with urgent needs, the charging schemes are still oversimplified and have many restrictions. In addition, different charging options should be provided to fit the individual need of each UAV. In view of this, this work attempts to meet the mission characteristics and needs of various UAVs by providing an adaptive flight path and charging plan attached to individual UAVs, as well as reducing the power load of the renewable power generation during the peak period. We ran a series of simulations for the proposed flight path and charging mechanism to evaluate its performance. The simulation results revealed that the solutions proposed in this work can be used by UAV operators to fit the needs of each individual UAV.

Modeling technology changes in air transport in the presence of a market shock: A passenger-based analysis

This paper proposes a formal model to assess the introduction of hydrogen technology in the air transport sector when the initial market is uncovered, a situation relevant to the current COVID-19 crisis. The "flight shame” movement causes some passengers to leave the market while allowing for some willingness-to-pay for cleaner technologies. Starting from a horizontally differentiated duopoly between airlines with old technology and an uncovered market, the introduction of hydrogen technology provides the opportunity for vertical differentiation in line with the increased environmental consciousness of passengers. The principal methodological novelties start from an uncovered market and combine horizontal and vertical differentiation. The main results are the airlines' optimal strategy sets and the adoption strategy dynamics with an increased valuation of quality by passengers. We justify a regulator's intervention and draw several potential policy implications from this dynamic, such as a minimum subsidy level and educational advertising. © 2022