Aiming at the problem of rapid processing of real-time data in intelligent dispatching, a new method for calculating the information flow of distribution network monitoring is proposed. Access the distribution network monitoring data by publishing subscriptions, combining the topology parallel model of flow calculation, comprehensive use of multi-theme partition message caching technology, to achieve low-latency and high-throughput processing of distribution network monitoring information[1-3]. The method can obtain hundreds of millisecond monitoring data processing delay, and it has practical value in research to improve low-latency distribution network dispatch system.
We present the Temporal Logic Synthesis Format (TLSF), a high-level format to describe synthesis problems via Linear Temporal Logic (LTL). The format builds upon standard LTL, but additionally allows to use high-level constructs, such as sets and functions, to provide a compact and human-readable representation. Furthermore, the format allows to identify parameters of a specification such that a single description can be used to define a family of problems. Additionally, we present a tool to automatically translate the format into plain LTL, which then can be used for synthesis by a solver. The tool also allows to adjust parameters of the specification and to apply standard transformations on the resulting formula.
Unmanned Aircraft Systems (UAS) with autonomous decision-making capabilities are of increasing interest for a wide area of applications such as logistics and disaster recovery. In order to ensure the correct behavior of the system and to recognize hazardous situations or system faults, we applied stream runtime monitoring techniques within the DLR ARTIS (Autonomous Research Testbed for Intelligent System) family of unmanned aircraft. We present our experience from specification elicitation, instrumentation, offline log-file analysis, and online monitoring on the flight computer on a test rig. The debugging and health management support through stream runtime monitoring techniques have proven highly beneficial for system design and development. At the same time, the project has identified usability improvements to the specification language, and has influenced the design of the language. 1 input double lat, lon, ug, vg, wg, time_s, time_micros 2 output double time := time_s + time_micros / 1000000.0 3 output double flight_time := time -time#[0,0.0] 4 output double frequency := switch position{ 5 case 0 { 1.0 / ( time[1,0.0] -time ) } 6 default { 1.0 / ( time -time[-1,0.0] ) } } 7 output double freq_sum := freq_sum[-1,0.0] + frequency 8 output double freq_avg := freq_sum / double(position+1) 9 output double freq_max := max( frequency, freq_max[-1,double_min] ) 10 output double freq_min := min( frequency, freq_min[-1,double_max] ) 11 12 output double velocity := sqrt( ug^2.0 + vg^2.0 + wg^2.0 ) 13 const double R := 6373000.0 14 const double pi := 3.1415926535 15 16 output double lon1_rad := lon[-1,0.0] * pi / 180.0 17 output double lon2_rad := lon * pi / 180.0 18 output double lat1_rad := lat[-1,0.0] * pi / 180.0
The autonomous control of unmanned aircraft is a highly safety-critical domain with great economic potential in a wide range of application areas, including logistics, agriculture, civil engineering, and disaster recovery. We report on the development of a dynamic monitoring framework for the DLR ARTIS (Autonomous Rotorcraft Testbed for Intelligent Systems) family of unmanned aircraft based on the formal specification language RTLola. RTLola is a stream-based specification language for real-time properties. An RTLola specification of hazardous situations and system failures is statically analyzed in terms of consistency and resource usage and then automatically translated into an FPGA-based monitor. Our approach leads to highly efficient, parallelized monitors with formal guarantees on the noninterference of the monitor with the normal operation of the autonomous system.
Tuberculosis (TB) still represents a major global health problem affecting over 10 million people worldwide. The gold-standard procedures for TB diagnosis are culture and nucleic acid amplification techniques. In this context, both lipoarabinomannan (LAM) urine test and rapid molecular tests have been major game changers. However, the low sensitivity of the former and the cost and the prohibitive infrastructure requirements to scale-up in endemic regions of the latter, make the improvement of the TB diagnostic landscape a priority. Most forms of life produce extracellular vesicles (EVs), including bacteria despite differences in bacterial cell envelope architecture. We demonstrated that Mycobacterium tuberculosis (Mtb), the causative agent of TB, produces EVs in vitro and in vivo as part of a sophisticated mechanism to manipulate host cellular physiology and to evade the host immune system. In a previous serology study, we showed that the recognition of several mycobacterial extracellular vesicles (MEV) associated proteins could have diagnostic properties. In this study, we pursued to expand the capabilities of MEVs in the context of TB diagnostics by analyzing the composition of MEVs isolated from Mtb cultures submitted to iron starvation and, testing their immunogenicity against a new cohort of serum samples derived from TB+ patients, latent TB-infected (LTBI) patients and healthy donors. We found that despite the stringent condition imposed by iron starvation, Mtb reduces the number of MEV associated proteins relative to iron sufficient conditions. In addition, TB serology revealed three new MEV antigens with specific biomarker capacity. These results suggest the feasibility of developing a point-of-care (POC) device based on selected MEV-associated proteins.
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