Co-chaperone HOP (also called stress-inducible protein 1) is a co-chaperone that interacts with the cytosolic 70-kDa heat shock protein (HSP70) and 90-kDa heat shock protein (HSP90) families using different tetratricopeptide repeat domains. HOP plays crucial roles in the productive folding of substrate proteins by controlling the chaperone activities of HSP70 and HSP90. Here, we examined the levels of HOP, HSC70 (cognate of HSP70, also called HSP73), and HSP90 in the tumor tissues from colon cancer patients, in comparison with the non-tumor tissues from the same patients. Expression level of HOP was significantly increased in the tumor tissues (68% of patients, n=19). Levels of HSC70 and HSP90 were also increased in the tumor tissues (95% and 74% of patients, respectively), and the HOP level was highly correlated with those of HSP90 (r=0.77, p<0.001) and HSC70 (r=0.68, p<0.01). Immunoprecipitation experiments indicated that HOP complexes with HSC70 or HSP90 in the tumor tissues. These data are consistent with increased formation of co-chaperone complexes in colon tumor specimens compared to adjacent normal tissue and could reflect a role for HOP in this process.

Thermal Z to E isomerization reactions of azobenzene and 4-dimethylamino-4'-nitroazobenzene were examined in three ionic liquids of general formula 1-R-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (R = butyl, pentyl, and hexyl). The first-order rate constants and activation energies for the reactions of azobenzene measured in these ionic liquids were consistent with those measured in ordinary organic solvents, which indicated that the slow isomerization through the inversion mechanism with a nonpolar transition state was little influenced by the solvent properties, such as the viscosity and dielectric constant, of ionic liquids. On the other hand, the rate constants and the corresponding frequency factors of the Arrhenius plot were significantly reduced for the isomerization of 4-dimethylamino-4'-nitroazobenzene in ionic liquids compared with those for the isomerization in ordinary organic molecular solvents with similar dielectric properties. Although these ionic liquids are viscous, the apparent viscosity dependence of the rate constant could not be explained either by the Kramers-Grote-Hynes model or by the Agmon-Hopfield model for solution reactions. It is proposed that the positive and the negative charge centers of a highly polar rotational transition state are stabilized by the surrounding anions and cations, respectively, and that the ions must be rearranged so as to form highly ordered solvation shells around the charge centers of the reactant in the transition state. This requirement for the orderly solvation in the transition state results in unusually small frequency factors of 10(4)-10(7) s(-1).

This paper proposes data-driven queuing models and solutions to reduce arrival time delays originating from aircraft arrival processing bottlenecks at Tokyo International Airport. A data-driven analysis was conducted using two years of radar tracks and flight plans from 2016 and 2017. This analysis helps not only to understand the bottlenecks and operational strategies of air traffic controllers, but also to develop mathematical models to predict arrival delays resulting from increased, future aircraft traffic. The queue-based modeling approach suggests that one potential solution is to expand the realization of time-based operations, efficiently shifting from traffic flow control to time-based arrival management. Furthermore, the proposed approach estimates the most effective range of transition points, which is a key requirement for designing extended arrival management systems while offering automation support to air traffic controllers.

Although the application of new, reduced aircraft separation minima can directly increase runway throughput, the impact thereof on the traffic flow of aircraft arriving at the destination airport has not been discussed yet. This paper proposes a data-driven and queue-based modeling approach and presents an analysis of the impact on the delay time of arriving aircraft in the airspace within a radius of 100 nautical miles around an airport. The parameters of our queuing model were estimated by analysing the data contained in the radar tracks and flight plans for flights that arrived at Tokyo International Airport during the 2 years of 2016 and 2017. The results clarified the best arrival strategy according to the distance from the arrival airport: The combination of airspace capacity control and reduction of the flight time and separation variance is the most powerful solution to mitigate delays experienced by arriving traffic while also allowing an increase in the amount of arrival traffic. The application of new wake vortex categories would enable us to increase the arrival traffic to 120%. In addition, the arrival delay time could be minimised by implementing the proposed arrival traffic strategies together with automation support for air traffic controllers.

Airborne Separation Assistance System (ASAS) is seen as a promising option for the future ATM concept to increase capacity and flight efficiency while maintaining flight safety. One idea of recent interest in ASAS applications is Airborne SPacing Application using enhanced Sequencing and Merging (ASPA-S&M). The S&M is expected to support energy saving arrivals, commonly referred to as Continuous Descent Arrivals (CDA). The motivation for our study is the need to clarify how safety and capacity depend on the setting of spacing criteria and in combination with specific S&M design aspects, and to identify any potential emergent behavior that should be taken into account in the operation design. For this purpose, a preceding study has designed initial mathematical models of the ASAS application for two aircraft trailing. This research develops the models to multiple aircraft trailing under stochastic wind conditions. In this paper, ASAS core components and their interactions are captured to build an integrated model using a Stochastically and Dynamically Colored Petri Net (SDCPN). Through Monte Carlo simulation based on the SDCPN model, we evaluate the performance of ASAS speed control for CDA operation considering the wind effect and multiple trailing aircraft.