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The narrow pH application range and lower utilization of ferrous ions (Fe(II)) restrict the application of Fe(II)/persulfate (PS) technology. In this paper, simulated sunlight and citric acid (Cit) as a chelator were introduced in an Fe(II)/PS system to overcome the drawbacks and enhance the degradation of typical antibiotic sulfamethoxazole (SMX) in secondary wastewater. The degradation kinetics, mechanism, and influence factors of SMX in a sunlight/Fe(II)/Cit/PS system and a sunlight/Fe(II)/Cit system as a comparable system were investigated. The removal efficiency of SMX can reach 71.15% and 85.25% in the sunlight/Fe(II)/Cit system and sunlight/Fe(II)/Cit/PS system with 0.1 mM Fe(II), 0.6 mM Cit, and 1 mM PS. The increase of Fe(II) concentration in both systems proved that sunlight promoted the regeneration of Fe(II) from the ferric ion chelates. However, the Fe(II) concentration decreased after 30 min in the sunlight/Fe(II)/Cit/PS system because of the decomposition of Cit. Radical quencher experiments indicated that SO4·−, ·OH, and O2·− contributed 2.48%, 88.43%, and 6.91% to the removal of SMX, respectively. Electron paramagnetic resonance spectra also proved the formation of ·OH and O2·−. The degradation of SMX was proposed to proceed via isomerization, cleavage of S–N bond, and hydroxylation. Overall, the sunlight/Fe(II)/Cit/PS process can be used as an advanced treatment technology for antibiotics in municipal wastewater. [ABSTRACT FROM AUTHOR]

Assessing the impact of varied rainfall patterns on soil and water loss within a hilly watershed over an extended temporal scope holds paramount importance in comprehending regional runoff and sediment traits. This study utilized continuous rainfall and sediment data spanning from 2013 to 2021, and the K-means clustering method was employed to analyze rainfall types. Subsequently, the rain-type characteristics underwent further analysis through LSD, and a multiple linear regression equation was formulated. The result showed that: within the Qiaotou small basin, rainfall, maximum rainfall intensity within 30 min (I30), and rainfall erosivity exhibited notable effects on sediment yield and loss. The water-sediment attributes of 305 rainfall events were characterized by rainfall below 100 mm, I30 of less than 35 mm/h, a runoff coefficient below 0.5, and sediment content under 0.6 g/L. According to the characteristics of different rainfall types and the degree of influence on water and sediment in small watersheds, 305 rainfall events in the basin were divided into three types by the K-means clustering analysis method: A (heavy rainfall, moderate rain), B (small rainfall, light rain), and C (medium rainfall, heavy rain). The most frequent rain type observed was B, followed by C, while A had the lowest frequency. Despite the lower intensity of B-type rainfall, it holds significant regional importance. Conversely, C-type rainfall, although intense and short, serves as the primary source of sediment production. The multiple regression equation effectively models both sediment yield modulus and flood peak discharge, exhibiting an R2 coefficient exceeding 0.80, signifying significance. This equation enables the quantitative calculation of pertinent indicators. Sediment yield modulus primarily relies on sediment concentration, runoff depth, and rainfall, while peak discharge is significantly influenced by runoff depth, sediment concentration, and I30. Furthermore, the efficacy of various soil and water conservation measures for flow and sediment reduction correlates with I30. Overall, the impact of different measures on reducing flow and sediment increases with a higher I30, accompanied by a reduced fluctuation range. [ABSTRACT FROM AUTHOR]

Analysis of the spatial and temporal variation patterns of surface evapotranspiration is important for understanding global climate change, promoting scientific deployment of regional water resources, and improving crop yield and water productivity. Based on Landsat 8 OIL_TIRS data and remote sensing image data of the lower Yangtze River urban cluster for the same period of 2016–2021, combined with soil and meteorological data of the study area, this paper constructed a multiple linear regression (MLR) model and an extreme learning machine (ELM) inversion model with evapotranspiration as the target and, based on the model inversion, quantitatively and qualitatively analyzed the spatial and temporal variability in surface evapotranspiration in the study area in the past six years. The results show that both models based on feature factors and spectral indices obtained a good inversion accuracy, with the fusion of feature factors effectively improving the inversion ability of the model for ET. The best model for ET in 2016, 2017, and 2021 was MLR, with an R2 greater than 0.8; the best model for ET in 2018–2019 was ELM, with an R2 of 0.83 and 0.62, respectively. The inter-annual ET in the study area showed a "double-peak" dynamic variation, with peaks in 2018 and 2020; the intra-annual ET showed a single-peak cycle, with peaks in July–August. Seasonal differences were obvious, and spatially high-ET areas were mainly found in rural areas north of the Yangtze River and central and western China where agricultural land is concentrated. The net solar radiation, soil heat flux, soil temperature and humidity, and fractional vegetation cover all had significant positive effects on ET, with correlation coefficients ranging from 0.39 to 0.94. This study can provide methodological and scientific support for the quantitative and qualitative estimation of regional ET. [ABSTRACT FROM AUTHOR]

Laser shock peening (LSP) is an innovative and promising surface strengthening technique of metallic materials. The LSP-induced plastic deformation, the compressive residual stresses and the microstructure evolution are essentially attributed to the laser plasma-induced shock wave. A three-dimensional finite element model in conjunction with the dislocation density-based constitutive model was developed to simulate the LSP of pure Al correlating with the LSP-induced shock wave, and the predicted in-depth residual stresses are in reasonable agreement with the experiment results. The LSP-induced shock wave associated with the laser spot diameter of 8.0 mm propagates in the form of the plane wave, and attenuates exponentially. At the same time, the propagation and attenuation of the LSP-induced shock wave associated with the laser spot diameter of 0.8 mm are in the form of the spherical wave. The reflection of the LSP-induced shock wave at the bottom surface of the target model increases the plastic deformation of the target bottom, resulting in the increase of dislocation density and the decrease of dislocation cell size accordingly. Reducing the target thickness can significantly increase the reflection times of the LSP-induced shock wave at the bottom and top surfaces of the target model, which is considered to be conductive to the generation of the compressive residual stress field and grain refinement. [ABSTRACT FROM AUTHOR]

This paper presents the future intelligent transmission network substation architecture; it identifies the most important design patterns for the purpose of building simplified versions of the communication infrastructure with High-Availability Seamless Redundancy (HSR) and Parallel Redundancy Protocol (PRP) configurations, respectively. The network model used for the laboratory tests is detailed, and details regarding the modelling of current-transformer (CT) saturation are given and discussed. Several intentional communications related to equipment or fibre failures are discussed. The laboratory setup for both HSR and PRP is presented. A real-time digital simulator (RTDS) network model is built and the test processes are presented. Some tests are carried out to test the functionality and interoperability with different fault conditions under the future intelligent transmission network substation architectures' HSR-only and PRP-only data network configurations. The results are analysed and discussed, and a future intelligent transmission network substation test platform is successfully implemented in the laboratory. The experimental results can provide valuable information for power utilities and manufacturers to optimise substation architecture and their products under different conditions. [ABSTRACT FROM AUTHOR]

The control strategy is crucial for the effective and safe operation of the ORC system. A transient model of the ORC system was developed in the present work and validated by the experimental data of a 4 kW ORC prototype. Then, the effect of heat source temperature on the dynamic response and operation characteristics of the ORC system were analyzed. Five control strategies were compared: the constant working fluid mass flow rate mode, constant vapor superheat mode, constant vapor temperature mode, constant evaporation pressure mode and constant output power load mode. Under the constraint that the working fluid at the expander inlet should be superheated, we found that the constant vapor superheat mode enabled the safe operation with the largest range of heat source temperature, while the other four modes were only available for a certain temperature range. Apart from the constant output power mode, the constant evaporation pressure mode can also provide a relatively stable performance for the ORC unit. The variation of the thermal efficiency was limited when the heat source temperature was higher than 125 °C, except for the constant vapor temperature mode. Considering the high performance and stable operation of the ORC system, it is necessary to have different operation modes combined in the control strategy according to the specific working scenarios. [ABSTRACT FROM AUTHOR]

A multi-objective optimization based on the non-dominated sorting genetic algorithm (NSGA-II) is carried out in the present work for the basic organic Rankine cycle (BORC) and regenerative ORC (RORC) systems. The selection of working fluids is integrated into multi-objective optimization by parameterizing the pure working fluids into a two-dimensional array. Two sets of decision indicators, exergy efficiency vs. thermal efficiency and exergy efficiency vs. levelized energy cost (LEC), are adopted and examined. Five decision variables including the turbine inlet temperature, vapor superheat degree, the evaporator and condenser pinch temperature differences, and the mass fraction of the mixture are optimized. It is found that the turbine inlet temperature is the most effective factor for both the BORC and RORC systems. Compared to the reverse variation of exergy efficiency and thermal efficiency, only a weak conflict exists between the exergy efficiency and LEC which tends to make the binary objective optimization be a single objective optimization. The RORC provides higher thermal efficiency than BORC at the same exergy efficiency while the LEC of RORC also becomes higher because the bare module cost of buying one more heat exchange is higher than the cost reduction due to the reduced heat transfer area. Under the heat source temperature of 423.15 K, the final obtained exergy and thermal efficiencies are 45.6% and 16.6% for BORC, and 38.6% and 20.7% for RORC, respectively. [ABSTRACT FROM AUTHOR]

Since the effects of mono-unsaturated fatty acids (MUFA) on lipid profile are still controversial, a meta-analysis of randomized controlled trials was conducted in the present study to assess the effect of MUFA-rich food on lipid profiles. The study was designed, conducted, and reported according to the guidelines of the 2020 preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement. A systematic and comprehensive search was performed in several databases from inception up to 30 January 2022. The results showed that the intake of edible oil-derived MUFA (EDM) could increase the blood HDL-C level (mean difference = 0.08; 95%CI: −0.01, 0.17, p = 0.03), but did not affect the level of TC, TG, or LDL-C. Moreover, the consumption of other food-derived MUFA (ODM) significantly decreased TG concentration (mean difference = −0.35; 95%CI: −0.61, −0.09, p = 0.01)), but did not affect the level of TC, LDL-C, or HDL-C. Findings from this study suggest that MUFA-rich food might be beneficial to modulate the blood lipid profile. [ABSTRACT FROM AUTHOR]

The acoustic signal in the operation of a power transformer contains a lot of transformer operation state information, which is of great significance to the detection of DC bias state. In this paper, three typical parameters used for DC bias state detection are selected by comparing the acoustic variation of a 500 kV Jingting transformer substation No. 2 transformer with that of the core model built in the laboratory; then, acoustic samples of the 162 EHV normal state transformers are collected, and the distribution regularity of three typical parameters in normal state is given. Finally, according to the distribution regularity, clear warning threshold of typical parameters are given, and the DC bias cases from the 500 kV Jingting transformer substation are used to verify the effectiveness of the threshold. [ABSTRACT FROM AUTHOR]

To investigate the action mechanism of titanium, the effects of different Ti-bearing compounds, including CaTiO3, MgTiO3, and nano-TiO2, on the properties of alumina–magnesia castables were studied. By analyzing the phase compositions, microstructures, and physical and mechanical properties of the castables, it was demonstrated that an intermediate product, CaTiO3, was first generated. This was then consumed by solid-solution reactions, and titanium was involved in the liquid formation as the temperature increased. The solid-solution reaction of CA6 (CaAl12O19) was more prominent due to the incorporation of more titanium in the crystal lattice of CA6 instead of spinel (MgAl2O4). Moreover, the liquid formation was strongly promoted when more titanium accompanied the calcium, which finally accelerated the densification and improved the strengths of alumina–magnesia castables. On the whole, castables with CaTiO3 addition presented higher bulk density and excellent strength after the heat treatment. Besides, the castables with 2 wt.% CaTiO3 contents were estimated to possess greater thermal shock resistance. [ABSTRACT FROM AUTHOR]

This paper proposes a meta-modeling workflow to forecast the cooling and heating loads of buildings at individual and district levels in the early design stage. Seven input variables, with large impacts on building loads, are selected for designing meta-models to establish the MySQL database. The load profiles of office, commercial, and hotel models are simulated with EnergyPlus in batches. A sequence-to-sequence (Seq2Seq) model based on the deep-learning method of a one-dimensional convolutional neural network (1D-CNN) is introduced to achieve rapid forecasting of all-year hourly building loads. The method performs well with the load effective hour rate (LEHR) of around 90% and MAPE less than 10%. Finally, this meta-modeling workflow is applied to a district as a case study in Shanghai, China. The forecasting results well match the actual loads with R2 of 0.9978 and 0.9975, respectively, for the heating and cooling load. The LEHR value of all-year hourly forecasting loads is 98.4%, as well as an MAPE of 4.4%. This meta-modeling workflow expands the applicability of building-physics-based methods and improves the time resolution of conventional data-driven methods. It shows small forecasting errors and fast computing speed while meeting the required precision and convenience of engineering in the building early design stage. [ABSTRACT FROM AUTHOR]

The advent of optogenetics provides a well-targeted tool to manipulate neurons because of its high time resolution and cell-type specificity. Recently, closed-loop neural manipulation techniques consisting of optical stimulation and electrical recording have been widely used. However, metal microelectrodes exposed to light radiation could generate photoelectric noise, thus causing loss or distortion of neural signal in recording channels. Meanwhile, the biocompatibility of neural probes remains to be improved. Here, five kinds of neural interface materials are deposited on flexible polyimide-based neural probes and illuminated with a series of blue laser pulses to study their electrochemical performance and photoelectric noises for single-unit recording. The results show that the modifications can not only improve the electrochemical performance, but can also reduce the photoelectric artifacts. In particular, the double-layer composite consisting of platinum-black and conductive polymer has the best comprehensive performance. Thus, a layer of polypeptide is deposited on the entire surface of the double-layer modified neural probes to further improve their biocompatibility. The results show that the biocompatible polypeptide coating has little effect on the electrochemical performance of the neural probe, and it may serve as a drug carrier due to its special micromorphology. [ABSTRACT FROM AUTHOR]

Studies have shown that bone marrow-derived mesenchymal stem cells (BMSCs) can differentiate into dermal fibroblasts to participate in skin-repairing. However, at present, little is known about how microgravity affects dermal fibroblastic differentiation of BMSCs in space. The aim of this study was to investigate the effect of simulated microgravity (SMG) on the differentiation of BMSCs into dermal fibroblasts and the related molecular mechanism. Here, using a 2D-clinostat device to simulate microgravity, we found that SMG inhibited the differentiation and suppressed the Wnt/β-catenin signaling and phosphorylation of extracellular regulated protein kinases 1/2 (ERK1/2). After upregulating the Wnt/β-catenin signaling with lithium chloride (LiCl) treatment, we found that the effect of the differentiation was restored. Moreover, the Wnt/β-catenin signaling was upregulated when phosphorylation of ERK1/2 was activated with tert-Butylhydroquinone (tBHQ) treatment. Taken together, our findings suggest that SMG inhibits dermal fibroblastic differentiation of BMSCs by suppressing ERK/β-catenin signaling pathway, inferring that ERK/β-catenin signaling pathway may act as a potential intervention target for repairing skin injury under microgravity conditions. [ABSTRACT FROM AUTHOR]

Progress in understanding kidney disease mechanisms and the development of targeted therapeutics have been limited by the lack of functional in vitro models that can closely recapitulate human physiological responses. Organ Chip (or organ-on-a-chip) microfluidic devices provide unique opportunities to overcome some of these challenges given their ability to model the structure and function of tissues and organs in vitro. Previously established organ chip models typically consist of heterogenous cell populations sourced from multiple donors, limiting their applications in patient-specific disease modeling and personalized medicine. In this study, we engineered a personalized glomerulus chip system reconstituted from human induced pluripotent stem (iPS) cell-derived vascular endothelial cells (ECs) and podocytes from a single patient. Our stem cell-derived kidney glomerulus chip successfully mimics the structure and some essential functions of the glomerular filtration barrier. We further modeled glomerular injury in our tissue chips by administering a clinically relevant dose of the chemotherapy drug Adriamycin. The drug disrupts the structural integrity of the endothelium and the podocyte tissue layers, leading to significant albuminuria as observed in patients with glomerulopathies. We anticipate that the personalized glomerulus chip model established in this report could help advance future studies of kidney disease mechanisms and the discovery of personalized therapies. Given the remarkable ability of human iPS cells to differentiate into almost any cell type, this work also provides a blueprint for the establishment of more personalized organ chip and 'body-on-a-chip' models in the future. [ABSTRACT FROM AUTHOR]

Remarkable progress has been made in the high resolution, biocompatibility, durability and stretchability for the implantable brain-computer interface (BCI) in the last decades. Due to the inevitable damage of brain tissue caused by traditional rigid devices, the thin film devices are developing rapidly and attracting considerable attention, with continuous progress in flexible materials and non-silicon micro/nano fabrication methods. Therefore, it is necessary to systematically summarize the recent development of implantable thin film devices for acquiring brain information. This brief review subdivides the flexible thin film devices into the following four categories: planar, open-mesh, probe, and micro-wire layouts. In addition, an overview of the fabrication approaches is also presented. Traditional lithography and state-of-the-art processing methods are discussed for the key issue of high-resolution. Special substrates and interconnects are also highlighted with varied materials and fabrication routines. In conclusion, a discussion of the remaining obstacles and directions for future research is provided. [ABSTRACT FROM AUTHOR]

Analog circuit fault diagnosis technology is widely used in the diagnosis of various electronic devices. The basic strategy is to extract circuit fault characteristics and then to use a clustering algorithm for diagnosis. The discrete Volterra series (DVS) is a common feature extraction method; however, it is difficult to calculate its parameters. To solve the problem of feature extraction in fault diagnosis, we propose an improved hierarchical Levenberg–Marquardt (LM)–DVS algorithm (IDVS). First, the DVS is simplified on the basis of the hierarchical symmetry of the memory parameters, the LM strategy is used to optimize the coefficients, and a Bayesian information criterion based on the symmetry of entropy is introduced for order selection. Finally, we propose a fault diagnosis method by combining the improved DVS algorithm and a condensed nearest neighbor algorithm (CNN) (i.e., the IDVS–CNN method). A simulation experiment was conducted to verify the feature extraction and fault diagnosis ability of the IDVS–CNN. The results show that the proposed method outperforms conventional methods in terms of the macro and micro F1 scores (0.903 and 0.894, respectively), which is conducive to the efficient application of fault diagnosis. In conclusion, the improved method in this study is helpful to simplify the calculation of the DVS parameters of circuit faults in analog electronic systems, and provides new insights for the prospective application of circuit fault diagnosis, system modeling, and pattern recognition. [ABSTRACT FROM AUTHOR]

In this study, a template copolymer (TPAA) of (3-Acrylamidopropyl) trimethylammonium chloride (AATPAC) and acrylamide (AM) was successfully synthesized though ultrasonic-initiated template copolymerization (UTP), using sodium polyacrylate (PAAS) as a template. TPAA was characterized by an evident cationic microblock structure which was observed through the analyses of the reactivity ratio, Fourier transform infrared spectroscopy (FTIR), ¹H ( 13 C) nuclear magnetic resonance spectroscopy (¹H ( 13 C) NMR), and thermogravimetry/differential scanning calorimetry (TG/DSC). The introduction of the template could improve the monomer (AATPAC) reactivity ratio and increase the length and amount of AATPAC segments. This novel cationic microblock structure extremely enhanced the ability of charge neutralization, patching, and bridging, thus improving the activated sludge flocculation performance. The experiments of floc formation, breakage, and regrowth revealed that the cationic microblock structure in the copolymer resulted in large and compact flocs, and these flocs had a rapid regrowth when broken. Finally, the larger and more compact flocs contributed to the formation of more channels and voids, and therefore the specific resistance to filtration (SRF) reached a minimum., Competing Interests: The authors declare no conflict of interest.