A Human-in-the Loop Exploration of the Dynamic Airspace Configuration Concept

An exploratory human-in-the-loop study was conducted to better understand the impact of Dynamic Airspace Configuration (DAC) on air traffic controllers. To do so, a range of three progressively more aggressive algorithmic approaches to sectorizations were chosen. Sectorizations from these algorithms were used to test and quantify the range of impact on the controller and traffic. Results show that traffic count was more equitably distributed between the four test sectors and duration of counts over MAP were progressively lower as the magnitude of boundary change increased. However, taskload and workload were also shown to increase with the increase in aggressiveness and acceptability of the boundary changes decreased. Overall, simulated operations of the DAC concept did not appear to compromise safety. Feedback from the participants highlighted the importance of limiting some aspects of boundary changes such as amount of volume gained or lost and the extent of change relative to the initial airspace design

Required Time of Arrival as a Control Mechanism to Mitigate Uncertainty in Arrival Traffic Demand Management

The objective of this study is to explore the use of Required Time of Arrival (RTA) capability on the flight deck as a control mechanism on arrival traffic management to improve traffic delivery accuracy by mitigating the effect of traffic demand uncertainty. The uncertainties are caused by various factors, such as departure error due to the difference between scheduled departure and the actual take-off time. A simulation study was conducted using the Multi Aircraft Control System (MACS) software, a comprehensive research platform developed in the Airspace Operations Laboratory (AOL) at NASA Ames Research Center. The Crossing Time (CT) performance (i.e. the difference between target crossing time and actual crossing time) of the RTA for uncertainty mitigation during cruise phase was evaluated under the influence of varying two main factors: wind severity (heavy wind vs. mild wind), and wind error (1 hour, 2 hours, and 5 hours wind forecast errors). To examine the CT performance improvement made by the RTA, the comparison to the CT of the aircraft that were not assigned with RTA (Non-RTA) under the influence of the selected factors was also made. The Newark Liberty International Airport (EWR) was chosen for this study. A total 66 inbound traffic to the EWR (34 of them were airborne when the simulation was initiated, 32 were pre-departures at that time) was simulated, where the pre-scripted departure error was assigned to each pre-departure (61 conform to their Expected Departure Clearance Time, which is +-300 seconds of their scheduled departure time). The results of the study show that the delivery accuracy improvement can be achieved by assigning RTA, regardless of the influence of the selected two factors (the wind severity and the wind information inaccuracy). Across all wind variances, 66.9 (265 out of 396) of the CT performance of the RTA assigned aircraft was within +- 60 seconds (i.e. target tolerance range) and 88.9 (352 out of 396) aircraft met +-300 seconds marginal tolerance range, while only 33.6 (133 out of 396) of the Non-RTA assigned aircrafts CT performance achieved the target tolerance range and 75.5 (299 out of 396) stayed within the marginal. Examination of the impact of different error sources i.e. departure error, wind severity, and wind error suggest that although large departure errors can significantly impact the CT performance, the impacts of wind severity and errors were modest relative the targeted +- 60 second conformance range

Impact of Different Trajectory Option Set Participation Levels within an Air Traffic Management Collaborative Trajectory Option Program

This paper presents the methodology and results of a Human-In-The-Loop (HITL) simulation study conducted in the Airspace Operations Laboratory at NASA Ames Research Center. This study is a part of NASA's ongoing research into developing an Integrated Demand Management (IDM) concept, whose aim is to improve traffic flow management (TFM) by coordinating the FAA's strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The purpose of TFM is to regulate air traffic demand so that it is delivered efficiently through constrained airspace resources without exceeding their capacity limits. The IDM concept leverages a new TFMS capability called the Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for managing traffic tactically by generating precise arrival schedules. Unlike other TFM tools, CTOP gives flight operators the option of submitting a set of user-preferred alternative trajectories for each flight. CTOP can then use these trajectory option sets (or TOSs) to find user-preferred alternative routes to reduce demand on an overloaded resource. CTOP's effectiveness in redistributing demand is limited, however, by the availability of flights with alternative routes. The research presented in this paper focuses on evaluating the impact on TFM operations by varying the percentage of flights that submit a multiple-option TOS ('TOS participation levels'). Results show the impact on overall system performance and on the rerouted flights themselves. The simulation used a Newark (EWR) airport arrival scenario, with en route weather affecting traffic inbound from the west. Participants were asked to control each of the three arrival flows (north, west, and south) to meet their individual capacity constraints while simultaneously ensuring efficient utilization of the capacity at the destination airport. A large, permeable convective weather cell located southeast of Chicago severely reduced the capacity of the west flow. The study evaluated the impact of five different TOS participation levels on CTOP's ability to re-allocate traffic from the west and improve TFM performance in terms of delay assignment and traffic delivery rate to the airport. Overall, the results showed that increasing TOS submissions allowed the overall system delays to be reduced and fairly distributed among the three arrival flows, at the same time achieving the airport throughput rate. Moreover, it was found that aircraft who submitted a TOS saw a greater reduction in delay, even when they were assigned longer routes. This was particularly true when fewer aircraft submitted a TOS. The results confirm that the CTOP operations with higher TOS participation levels helped utilize the overall National Airspace System (NAS) resources as well as benefited the users who participated

Evaluation of Integrated Demand Management Looking into Strategic & Tactical Flow Management

The motivation behind Integrated Demand Management (IDM) research is to explore possible improvements to United States National Airspace System (NAS) performance that could be realized through procedural integration of strategic traffic flow management capabilities, such as the Collaborative Trajectory Options Program (CTOP), and tactical capabilities, such as Time Based Flow Management (TBFM). An initial IDM concept for clear weather operations was developed and evaluated for potential benefits, including efficiency, delay reduction, predictability and throughput, and to identify any major issues that might represent a showstopper for a fielded application. Newark Liberty International Airport (EWR) arrival operations provided a use case for concept development. EWR uses miles-in-trail (MIT) metering to regulate demand into TBFM during high volume operations, and short-haul flights are often penalized with excessive, last-minute ground delays when the overhead stream is saturated. IDM addresses this problem by replacing MIT conditioning with CTOP to better manage the demand delivery to the TBFM entry points. A quasi-real time high-fidelity simulation that would normally involve participants was conducted using heuristic-based procedures that mimicked operators behaviors instead. Five total conditions were compared: two baseline conditions with MIT delivery to TBFM entry points using two different TBFM settings; and three IDM conditions: one with airborne speed control using an Required Time of Arrival (RTA) capability, a second without RTA, and a third with no wind forecast errors. Results suggest that the IDM concept can deliver traffic more efficiently by shifting the delays from airborne to ground for both RTA and non-RTA conditions, while maintaining a target throughput rate. The results also suggest that with good predictability of airport capacity, excessive TBFM ground delay can be minimized by applying more strategic CTOP delay, increasing predictability for the airline operators. Overall, the results indicate that the implementation of an IDM concept under clear weather conditions can improve NAS system performance. Future IDM research aims to expand the concept to address demandcapacity imbalance d severe weather

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The ARID1B spectrum in 143 patients: from nonsyndromic intellectual disability to Coffin–Siris syndrome

Purpose: Pathogenic variants in ARID1B are one of the most frequent causes of intellectual disability (ID) as determined by large-scale exome sequencing studies. Most studies published thus far describe clinically diagnosed Coffin–Siris patients (ARID1B-CSS) and it is unclear whether these data are representative for patients identified through sequencing of unbiased ID cohorts (ARID1B-ID). We therefore sought to determine genotypic and phenotypic differences between ARID1B-ID and ARID1B-CSS. In parallel, we investigated the effect of different methods of phenotype reporting. Methods: Clinicians entered clinical data in an extensive web-based survey. Results: 79 ARID1B-CSS and 64 ARID1B-ID patients were included. CSS-associated dysmorphic features, such as thick eyebrows, long eyelashes, thick alae nasi, long and/or broad philtrum, small nails and small or absent fifth distal phalanx and hypertrichosis, were observed significantly more often (p < 0.001) in ARID1B-CSS patients. No other significant differences were identified. Conclusion: There are only minor differences between ARID1B-ID and ARID1B-CSS patients. ARID1B-related disorders seem to consist of a spectrum, and patients should be managed similarly. We demonstrated that data collection methods without an explicit option to report the absence of a feature (such as most Human Phenotype Ontology-based methods) tended to underestimate gene-related features

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival