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In this work, a machine learning (ML) metamodel is developed for the time-series forecasting of a typical nuclear power plant response undergoing a loss of coolant accident (LOCA). The plant model of choice is based on the APR1400 nuclear reactor. The key systems and components of APR1400 relevant to the investigated scenario are modelled using the thermal-hydraulic code, RELAP5/MOD3.4, following the description published in the design control document. The model is tested under a spectrum of initial and boundary conditions via propagation of key uncertain parameters (UPs) which are derived from the phenomena identification and ranking table (PIRT). This is achieved by loosely coupling RELAP5/MOD3.4 with the statistical tool, Dakota. The most probable nuclear power plant (NPP) response was calculated using the best estimate plus uncertainty (BEPU) approach. Next, the database generated from the NPP system response was used as an input for the ML model. The NPP system response was represented by peak cladding temperature (PCT), safety injection system (SIT), mass flow rate, reactor power, and primary system pressure. In this research, two regression models were tested with reasonably good performance, namely, the gated recurrent unit (GRU) and the long short-term memory (LSTM).

The following paper presents a simple, low-cost, and repeatable manufacturing process for fabricating conductive, elastic carbon-elastomer nanocomposite fibers for applications in the textile industry and beyond. The presented method allows for the manufacturing of fibers with a diameter of 0.2 mm, containing up to 50 vol. % of graphite powder, 10 vol. % of CNT, and a mix of both fillers. As a result, resistivity below 0.2 Ωm for the 0.2 mm-diameter fibers was achieved. Additionally, conductive fibers are highly elastic, which makes them suitable for use in the textile industry as an element of circuits. The effect of strain on the change in resistance was also tested. Researches have shown that highly conductive fibers can withstand strain of up to 40%, with resistivity increasing nearly five times compared to the unstretched fiber. This research shows that the developed composites can also be used as strain sensors in textronic systems. Finally, functional demonstrators were made by directly sewing the developed fibers into a cotton fabric. First, the non-quantitative tests indicate the feasibility of using the composites as conductive fibers to power components in textronic systems and for bending detection.

The synthesis and characterization of Ga1-xMnxN thick layers are reported. The layers were prepared by the modified sublimation sandwich method (SSM) from GaN powder and powdered Mn sources and reacted with ammonia. Ga1-xMnxN layers having a current maximum size of 60 m thickness and 10 mm × 10 mm area were obtained. The crystals of best crystalline quality were obtained with a growth rate of 25 m/h. SIMS measurements showed the presence of layers containing up to 4 atom % Mn. Measurements involving X-ray diffraction (structure refinement), rocking curves, map of reflections, and EXAFS confirmed good structural properties without phase separation. The measurements carried out by a superconducting quantum interferometer showed that the material revealed typical paramagnetic properties. [ABSTRACT FROM AUTHOR]

Mechanical parameters of Scots pine wood (Pinus sylvestris L.) of low (about 8%) and high (higher than the fiber saturation point) moisture content (MC) subjected to tensile stress along the grains were studied. The measurements were performed for microtome samples sliced from either earlywood or latewood and for samples containing both earlywood and latewood. The effect of MC on the mechanical properties of earlywood and latewood of Scots pine was different. The MC was found to have greater influence on the tensile strength and modulus of elasticity in latewood than in earlywood, but its effect on strain at failure was greater in earlywood. As determined individually for earlywood and latewood, the tensile strength, modulus of elasticity, and the strain at failure that were calculated from the rule of mixtures (the weighted mean for earlywood and latewood) did not differ significantly from the values found in the samples containing both zones. This similarity was observed at low and high MC.

The inadequate efficiency of existing therapeutic anti-cancer regiments and the increase in the multidrug resistance of cancer cells underscore the need to investigate novel anticancer strategies. The induction of apoptosis in tumors by cytotoxic agents produced by pathogenic microorganisms is an example of such an approach. Nevertheless, even the most effective drug should be delivered directly to targeted sites to reduce any negative impact on other cells. Accordingly, the stabilized nanosystem (SNS) for active agent delivery to cancer cells was designed for further application in local anti-tumor therapy. A product of genetically modified Escherichia coli, listeriolysin O (LLO), was immobilized within the polyelectrolyte membrane (poly(ethylenimine)|hyaluronic acid) shells of 'LLO nanocarriers' coupled with the stabilizing element of natural origin.The impact of LLO was evaluated in human leukemia cell lines in vitro. Correspondingly, the influence of the SNS and its elements was assessed in vitro. The viability of targeted cells was evaluated by flow cytometry. Visualization of the system structure was performed using confocal microscopy. The membrane shell applied to the nanocarriers was analyzed using atomic force microscopy and Fourier transform infrared spectroscopy techniques. Furthermore, the presence of a polyelectrolyte layer on the nanocarrier surface and/or in the cell was confirmed by flow cytometry. Finally, the structural integrity of the SNS and the corresponding release of the fluorescent solute listeriolysin were investigated.The construction of a stabilized system offers LLO release with a lethal impact on model eukaryotic cells. The applied platform design may be recommended for local anti-tumor treatment purposes.