Digital twin with augmented state extended Kalman filters for forecasting electric power consumption of industrial production systems.

The work aims to develop an effective tool based on Digital Twins (DTs) for forecasting electric power consumption of industrial production systems. DTs integrate dynamic models combined with Augmented State Extended Kalman Filters (ASEKFs) in a learning process. The connection with the real counterpart is realized exclusively through non-intrusive sensors. This architecture enables the model development of industrial systems (components, machinery and processes) on which complete knowledge is not available, by identifying the model's unknown parameters through short online training phases and small amounts of real-time raw data. ASEKFs track the unknowns keeping models updated as physical systems evolve. When a forecast is needed, the current estimates of the uncertain parameters are integrated into the dynamic models. These can then be used without ASEKFs to predict the actual energy use of the system under the desired operating conditions, including scenarios that differ from typical functioning. The approach is validated offline with reference to the electricity consumption of an automatic coffee machine, which represents a real test environment and a blueprint to design DTs for other industrial systems. The appliance is observed by measuring the supply voltage and the absorbed current. The accuracy of the results is analyzed and discussed. This method is developed in the context of energy consumption prediction and optimization in the manufacturing industry through refined energy management and planning.

Thermodynamic parameters for DNA sequences with dangling ends.

The thermodynamic contributions to duplex formation of all 32 possible single-nucleotide dangling ends on a Watson-Crick pair are reported. In most instances, dangling ends are stabilizing with free energy contributions ranging from +0.48 (GT(A)) to-0.96 kcal/mol (). In comparison, Watson-Crick nearest-neighbor increments range from -0. 58 (TA/AT) to -2.24 (GC/CG) kcal/mol. Hence, in some cases, a dangling end contributes as much to duplex stability as a Watson-Crick A-T base pair. The implications of these results for DNA probe design are discussed. Analysis of the sequence dependence of dangling-end stabilities show that the nature of the closing base pair largely determines the stabilization. For a given closing base pair, however, adenine dangling ends are always more or equally as stable as the other dangling nucleotides. Moreover, 5' dangling ends are more or equally as stabilizing as their 3' counterparts. Comparison of DNA with RNA dangling-end motifs shows that DNA motifs with 5' dangling ends contribute to stability equally or more than their RNA counterparts. Conversely, RNA 3' dangling ends contribute to stability equally or more than their DNA counterparts. This data set has been incorporated into a DNA secondary structure prediction algorithm (DNA MFOLD) (http://mfold2.wustl.edu/mfold/dna/for m1.cgi) as well as a DNA hybridization prediction algorithm (HYTHERtrade mark) (http://jsl1.chem.wayne.edu/Hyther/hythermenu .html).

Nearest-neighbor thermodynamics and NMR of DNA sequences with internal A.A, C.C, G.G, and T.T mismatches.

Thermodynamic measurements are reported for 51 DNA duplexes with A.A, C.C, G.G, and T.T single mismatches in all possible Watson-Crick contexts. These measurements were used to test the applicability of the nearest-neighbor model and to calculate the 16 unique nearest-neighbor parameters for the 4 single like with like base mismatches next to a Watson-Crick pair. The observed trend in stabilities of mismatches at 37 degrees C is G.G > T.T approximately A.A > C.C. The observed stability trend for the closing Watson-Crick pair on the 5' side of the mismatch is G.C >/= C.G >/= A.T >/= T.A. The mismatch contribution to duplex stability ranges from -2.22 kcal/mol for GGC.GGC to +2.66 kcal/mol for ACT.ACT. The mismatch nearest-neighbor parameters predict the measured thermodynamics with average deviations of DeltaG degrees 37 = 3.3%, DeltaH degrees = 7. 4%, DeltaS degrees = 8.1%, and TM = 1.1 degrees C. The imino proton region of 1-D NMR spectra shows that G.G and T.T mismatches form hydrogen-bonded structures that vary depending on the Watson-Crick context. The data reported here combined with our previous work provide for the first time a complete set of thermodynamic parameters for molecular recognition of DNA by DNA with or without single internal mismatches. The results are useful for primer design and understanding the mechanism of triplet repeat diseases.