Representation Learning based and Interpretable Reactor System Diagnosis Using Denoising Padded Autoencoder

With the mass construction of Gen III nuclear reactors, it is a popular trend to use deep learning (DL) techniques for fast and effective diagnosis of possible accidents. To overcome the common problems of previous work in diagnosing reactor accidents using deep learning theory, this paper proposes a diagnostic process that ensures robustness to noisy and crippled data and is interpretable. First, a novel Denoising Padded Autoencoder (DPAE) is proposed for representation extraction of monitoring data, with representation extractor still effective on disturbed data with signal-to-noise ratios up to 25.0 and monitoring data missing up to 40.0%. Secondly, a diagnostic framework using DPAE encoder for extraction of representations followed by shallow statistical learning algorithms is proposed, and such stepwise diagnostic approach is tested on disturbed datasets with 41.8% and 80.8% higher classification and regression task evaluation metrics, in comparison with the end-to-end diagnostic approaches. Finally, a hierarchical interpretation algorithm using SHAP and feature ablation is presented to analyze the importance of the input monitoring parameters and validate the effectiveness of the high importance parameters. The outcomes of this study provide a referential method for building robust and interpretable intelligent reactor anomaly diagnosis systems in scenarios with high safety requirements

Nonhuman Primate Induced Pluripotent Stem Cells in Regenerative Medicine

Among the various species from which induced pluripotent stem cells have been derived, nonhuman primates (NHPs) have a unique role as preclinical models. Their relatedness to humans and similar physiology, including central nervous system, make them ideal for translational studies. We review here the progress made in deriving and characterizing iPS cell lines from different NHP species. We focus on iPS cell lines from the marmoset, a small NHP in which several human disease states can be modeled. The marmoset can serve as a model for the implementation of patient-specific autologous cell therapy in regenerative medicine

Assessment of the three-dimensional flow field in the reactor pressure vessel in Hualong One nuclear power plants

This study uses computational fluid dynamics (CFD) to investigate the three-dimensional flow field under normal operating conditions in the reactor pressure vessel (RPV) in the Hualong One nuclear power plants (NPPs). With a particular focus on the flowrate distribution at the core inlet, the numerical framework is validated against the integral hydraulic experiment in a 1:4-scaled RPV of CNP1000, the prototype of the Hualong One reactor. The simulation results of the normalized flowrate at the core inlet agree reasonably well with the measured data. Based on the experimental data, several methods of calibrating the CFD turbulence model coefficients are suggested by introducing the concepts of data assimilation and machine learning. The flow field in a realistic RPV for Hualong One is predicted using the validated numerical framework, showing that the flowrate distribution at the core inlet is nearly homogeneous and that the turbulent intensity is acceptably low for each fuel assembly. It can provide essential information for the reactor core thermal–hydraulic design and the fuel assembly mechanical assessment

Molecular Profiling of Human Induced Pluripotent Stem Cell-Derived Hypothalamic Neurones Provides Developmental Insights into Genetic Loci for Body Weight Regulation

Recent data suggest that common genetic risks for metabolic disorders such as obesity may be human-specific and exert effects via the central nervous system. To overcome the limitation of human tissue access for study, we have generated induced human pluripotent stem cell (hiPSC)-derived neuronal cultures that recapture many features of hypothalamic neurones within the arcuate nucleus. In the present study, we have comprehensively characterised this model across development, benchmarked these neurones to in vivo events, and demonstrate a link between obesity risk variants and hypothalamic development. The dynamic transcriptome across neuronal maturation was examined using microarray and RNA sequencing methods at nine time points. K-means clustering of the longitudinal data was conducted to identify co-regulation and microRNA control of biological processes. The transcriptomes were compared with those of 103 samples from 13 brain regions reported in the Genotype-Tissue Expression database (GTEx) using principal components analysis. Genes with proximity to body mass index (BMI)-associated genetic variants were mapped to the developmentally expressed genesets, and enrichment significance was assessed with Fisher\u27s exact test. The human neuronal cultures have a transcriptional and physiological profile of neuropeptide Y/agouti-related peptide arcuate nucleus neurones. The neuronal transcriptomes were highly correlated with adult hypothalamus compared to any other brain region from the GTEx. Also, approximately 25% of the transcripts showed substantial changes in expression across neuronal development and potential co-regulation of biological processes that mirror neuronal development in vivo. These developmentally expressed genes were significantly enriched for genes in proximity to BMI-associated variants. We confirmed the utility of this in vitro human model for studying the development of key hypothalamic neurones involved in energy balance and show that genes at loci associated with body weight regulation may share a pattern of developmental regulation. These data support the need to investigate early development to elucidate the human-specific central nervous system pathophysiology underlying obesity susceptibility

Reduction of lead leakage from damaged lead halide perovskite solar modules using self-healing polymer-based encapsulation

In recent years, the major factors that determine commercialization of perovskite photovoltaic technology have been shifting from solar cell performance to stability, reproducibility, device upscaling and the prevention of lead (Pb) leakage from the module over the device service life. Here we simulate a realistic scenario in which perovskite modules with different encapsulation methods are mechanically damaged by a hail impact (modified FM 44787 standard) and quantitatively measure the Pb leakage rates under a variety of weather conditions. We demonstrate that the encapsulation method based on an epoxy resin reduces the Pb leakage rate by a factor of 375 compared with the encapsulation method based on a glass cover with an ultraviolet-cured resin at the module edges. The greater Pb leakage reduction of the epoxy resin encapsulation is associated with its optimal self-healing characteristics under the operating conditions and with its increased mechanical strength. These findings strongly suggest that perovskite photovoltaic products can be deployed with minimal Pb leakage if appropriate encapsulation is employed

Highly Efficient and Stable Perovskite Solar Cells via Modification of Energy Levels at the Perovskite/Carbon Electrode Interface

Perovskite solar cells (PSCs) have attracted great attention in the past few years due to their rapid increase in efficiency and low-cost fabrication. However, instability against thermal stress and humidity is a big issue hindering their commercialization and practical applications. Here, by combining thermally stable formamidinium-cesium-based perovskite and a moisture-resistant carbon electrode, successful fabrication of stable PSCs is reported, which maintain on average 77% of the initial value after being aged for 192 h under conditions of 85 degrees C and 85% relative humidity (the "double 85" aging condition) without encapsulation. However, the mismatch of energy levels at the interface between the perovskite and the carbon electrode limits charge collection and leads to poor device performance. To address this issue, a thin-layer of poly(ethylene oxide) (PEO) is introduced to achieve improved interfacial energy level alignment, which is verified by ultraviolet photoemission spectroscopy measurements. Indeed as a result, power conversion efficiency increases from 12.2% to 14.9% after suitable energy level modification by intentionally introducing a thin layer of PEO at the perovskite/carbon interface

Negligible‐Pb‐Waste and Upscalable Perovskite Deposition Technology for High‐Operational‐Stability Perovskite Solar Modules

An upscalable perovskite film deposition method combining raster ultrasonic spray coating and chemical vapor deposition is reported. This method overcomes the coating size limitation of the existing stationary spray, single‐pass spray, and spin‐coating methods. In contrast with the spin‐coating method (>90% Pb waste), negligible Pb waste during PbI2 deposition makes this method more environmentally friendly. Outstanding film uniformity across the entire area of 5 cm × 5 cm is confirmed by both large‐area compatible characterization methods (electroluminescence and scattered light imaging) and local characterization methods (atomic force microscopy, scanning electron microscopy, photoluminescence mapping, UV–vis, and X‐ray diffraction measurements on multiple sample locations), resulting in low solar cell performance decrease upon increasing device area. With the FAPb(I0.85Br0.15)3 (FA = formamidinium) perovskite layer deposited by this method, champion solar modules show a power conversion efficiency of 14.7% on an active area of 12.0 cm2 and an outstanding shelf stability (only 3.6% relative power conversion efficiency decay after 3600 h aging). Under continuous operation (1 sun light illumination, maximum power point condition, dry N2 atmosphere with <5% relative humidity, no encapsulation), the devices show high light‐soaking stability corresponding to an average T80 lifetime of 535 h on the small‐area solar cells and 388 h on the solar module

A holistic approach to interface stabilization for efficient perovskite solar modules with over 2,000-hour operational stability

The upscaling of perovskite solar cells to module scale and long-term stability have been recognized as the most important challenges for the commercialization of this emerging photovoltaic technology. In a perovskite solar module, each interface within the device contributes to the efficiency and stability of the module. Here, we employed a holistic interface stabilization strategy by modifying all the relevant layers and interfaces, namely the perovskite layer, charge transporting layers and device encapsulation, to improve the efficiency and stability of perovskite solar modules. The treatments were selected for their compatibility with low-temperature scalable processing and the module scribing steps. Our unencapsulated perovskite solar modules achieved a reverse-scan efficiency of 16.6% for a designated area of 22.4 cm². The encapsulated perovskite solar modules, which show efficiencies similar to the unencapsulated one, retained approximately 86% of the initial performance after continuous operation for 2,000 h under AM1.5G light illumination, which translates into a T₉₀ lifetime (the time over which the device efficiency reduces to 90% of its initial value) of 1,570 h and an estimated T80 lifetime (the time over which the device efficiency reduces to 80% of its initial value) of 2,680 h