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Abstract The monument, or the memorial, as a place of memory and emotional support, has been the focus of scholarly attention. Although existing studies have explored its space’s materialization, identity, history, and memory content, the materials about its design transformation have yet to be deeply excavated. Based on the relevant theories of place and place-making, the researchers constructed a knowledge system of the place-making model, the spatial vector pattern, and the worship behaviors of monuments. On this basis, a qualitative research methodology is adopted. Through case studies and participant observation, the design transformation of the monument/memorial is interpreted in the following five dimensions: function theme, morphology style, spatial relationship, visitor experience, and symbolic meaning. The results of this study show that the monument/memorial tends to promote in-depth public reflection and critical engagement with history, reflecting changes in how society perceives historical events. This research provides new perspectives for understanding the multidimensionality of the monument/memorial but also emphasizes the need to continue exploring its interaction with the socio-cultural context.

Flexible electronic devices with mechanical properties like the soft tissues of human organs have great potential for the next generation of wearable and implantable electronic devices. Self-healing hydrogel composites typically have high tensile strength, high electrical conductivity and damage repair properties and have wide applications in flexible electronics, such as human-computer interaction, health detection and soft robots. Various self-healing hydrogel composites have been developed to produce new stretchable conductive materials with satisfactory mechanical and self-healing properties. This paper presents the fabrication of self-healing hydrogel composites and their application in flexible electronic devices. Firstly, the repair mechanism of physically cross-linked and chemically cross-linked self-healing hydrogel composites is presented. Secondly, self-healing double network hydrogels, self-healing nanocomposite hydrogels and double crosslinked self-healing hydrogel composites and their applications in flexible sensors, energy harvesting devices, energy storage devices and optical devices are presented and discussed. Finally, the challenges and prospects of self-healing hydrogel composites in flexible electronic devices in the future are presented.

The effect of the fine content (FC) and the relative density (Dr) on the deformation properties of saturated coral sand has been explored through a series of drained cyclic triaxial tests. An important finding is that both FC and Dr significantly affect the development of cumulative volumetric strain (εvd,irN) and dynamic elastic modulus (Ed,N). Steady state cumulative volumetric strain (εvd,irs) increases with FC and decreases with Dr. When FC increases from 0 % to 30 %, the increment in εvd,irs is about 0.69 %, 0.41 %, 0.16 % under Dr=30 %, 45 %, 70 %, respectively. Furthermore, the development rate of εvd,irN increased with FC. Another significant finding is that the increase of the FC leads to a certain decay of the initial dynamical shear modulus (Ed,1) and the steady state dynamical elastic modulus (Ed,s). When FC increases from 0 % to 30 %, the reduction in Ed,1 is about 16.38 MPa, 12.39 MPa, 10.31 MPa and the reduction in Ed,s is about 6.96 MPa, 5.44 MPa, 3.24 MPa under Dr = 30 %, 45 %, 70 %, respectively. A dimensionless parameter, the relative dynamic elastic modulus (Er), is introduced to characterize the development of Ed,N with N. It is found that the growth rate of Er increased with FC, but it is independent on Dr. The equivalent skeleton void ratio (esk*) was introduced based on the binary medium theory. It is found that εvd,irs shows a power-function growth trend with an increase in esk*, while Ed,1 and Ed,s decrease linearly with the increase of esk*. A predictive model between εvd,irN/εvd,irs, Er, and esk* was established, and the applicability of the model was verified based on data from the literature.

A key and urgent scientific issue is how to characterize the complex intergranular contact state and mechanical behavior evolution of sand–fines mixed materials and then show how this state contributes to the static and dynamic properties of such materials. Both theoretical analyses and experimental data suggest that the mixes have different intergranular contact states as the fines content (FC) increases, and the mixed materials can be classified as sand-like, in-transition, or fines-like. The capability of the Rahman semi-empirical formula to predict the threshold fines content FCth—which distinguishes the regime of “fines in sand” (sand-dominated behavior) from that of “sand in fines” (fines-dominated behavior)—is verified using the basic material and mechanical properties of mixed materials from the literature. Developed from the method for determining the theoretical minimum void ratio, a new method that allows unified characterization of the critical intergranular contact state parameters FCin-min and FCin-max for in-transition soils is established based on the binary packing model, and FCin-min and FCin-max can be determined simply through explicit expressions that use some material physical indices of pure-sand and pure-fines materials. The proposed procedure offers significant advantages for evaluating the critical intergranular contact state and mechanical properties of sand–fines mixed materials in geotechnical engineering practice.

Drosophila suzukii (Diptera: Drosophilidae), spotted-wing drosophila, poses a significant threat to soft-skinned fruit crops in the Americas, Europe, Africa, and Oceania, as well as in Asia. The application of chemical insecticides is the primary control strategy for D. suzukii; however, resistance has developed with the indiscriminate use of chemical insecticides. Essential oils, considered potential alternatives to pesticidal strategies, exhibit potent toxic and sublethal behavioral effects against numerous pests, including D. suzukii. Clary sage oil repels a variety of agricultural and household pests; however, whether it has a repellent effect against D. suzukii remains unknown. Here, we found that clary sage oil exhibited dose-dependent repellency against D. suzukii adults in a T-maze assay, a two-choice assay and a two-choice attraction assay. Also, clary sage oil showed a significant repellent effect against D. suzukii larvae. Next, we explored the chemical constituents of clary sage oil by GC-MS and identified two major constituents, linalyl acetate (40.03%) and linalool (23.02%). Furthermore, the behavioral assays of linalyl acetate and linalool showed that both compounds conferred comparable repellency against D. suzukii adults and larvae. Finally, we found clary sage oil, linalyl acetate, and linalool elicited EAG responses in D. suzukii, especially clary sage oil, suggesting the repellency was mediated by the olfactory system. These findings indicate that D. suzukii shows olfactory-based behavioral avoidance of clary sage oil, linalyl acetate, and linalool. Clary sage oil and its major constituents may be possible alternatives in the management of D. suzukii.

Regional characterization of soil properties requires not only geostatistical models considering the spatial variability of soil properties but also methods that account for various sources of heterogeneous information. This paper presents a multi-conditional random field approach to characterize the regional characteristics of the average shear-wave velocity in the top 30 meters of subsoil (vs30) based on hybrid geotechnical and geological data. The workflow for integrating multiple sources of soil properties information in a random field model for regional vs30 mapping is developed. A detailed two-dimensional (2D) synthetic digital soil field is generated to assess and verify this workflow. With the generated synthetic field, parametric studies on the investigation plans, the value of Markov Bayes coefficient B, element size, and a predefined grid of secondary data are performed. Practice on whether to incorporate secondary data for vs30 mapping and the determination of coefficient B are provided.

The low hardness and poor wear resistance of laser-cladding 316L stainless steel impose significant constraints on its practical applications. In this study, a strategy for strengthening laser-cladding 316L stainless steel with WMoTaNb refractory high-entropy alloy as a reinforcement material is proposed. The results confirm that the coating primarily comprises a body-centered cubic (BCC) Fe-based solid solution, a network-distributed hexagonal Fe2X (X = W, Mo, Ta, and Nb) Laves phase, and a diffusely distributed face-centered cubic (FCC) (Ta, Nb)C phase. The Fe-based solid solution distributes along columnar and fine dendrites, while the Laves phase and (Ta, Nb)C phase are in the inter-dendrites. The presence of a significant number of network Laves phases exhibiting high strength and hardness is the primary factor contributing to the enhancement of coating microhardness. The hardness of the composite coating is increased by nearly twice compared to that of the 316L coating, resulting in an improved wear resistance. The present work can shed light on designing and fabricating 316L stainless steel coating with enhanced hardness and wear resistance.

La0.6Ca0.4Co1–xFexO3–d in its various compositions has proven to be an excellent CO2-resistant oxygen transport membrane that can be used in plasma-assisted CO2 conversion. With the goal of incorporating green hydrogen into the CO2 conversion process, this work takes a step further by investigating the compatibility of La0.6Ca0.4Co1–xFexO3–d membranes with hydrogen fed into the plasma. This will enable plasma-assisted conversion of the carbon monoxide produced in the CO2 reduction process into green fuels, like methanol. This requires the La0.6Ca0.4Co1–xFexO3–d membranes to be tolerant towards reducing conditions of hydrogen. The hydrogen tolerance of La0.6Ca0.4Co1–xFexO3–d (x = 0.8) was studied in detail. A faster and resource-efficient route based on ultrasonic spray synthesis was developed to synthesise the La0.6Ca0.4Co0.2Fe0.8O3–d membranes. The La0.6Ca0.4Co0.2Fe0.8O3–d membrane developed using ultrasonic spray synthesis showed similar performance in terms of its oxygen permeation when compared with the ones synthesised with conventional techniques, such as co-precipitation, sol–gel, etc., despite using 30% less cobalt.

Three ecotypes of rapeseed, winter, spring, and semi-winter, have been formed to enable the plant to adapt to different geographic areas. Although several major loci had been found to contribute to the flowering divergence, the genomic footprints and associated dynamic plant architecture in the vegetative growth stage underlying the ecotype divergence remain largely unknown in rapeseed. Here, a set of 41 dynamic i-traits and 30 growth-related traits were obtained by high-throughput phenotyping of 171 diverse rapeseed accessions. Large phenotypic variation and high broad-sense heritability were observed for these i-traits across all developmental stages. Of these, 19 i-traits were identified to contribute to the divergence of three ecotypes using random forest model of machine learning approach, and could serve as biomarkers to predict the ecotype. Furthermore, we analyzed genomic variations of the population, QTL information of all dynamic i-traits, and genomic basis of the ecotype differentiation. It was found that 213, 237, and 184 QTLs responsible for the differentiated i-traits overlapped with the signals of ecotype divergence between winter and spring, winter and semi-winter, and spring and semi-winter, respectively. Of which, there were four common divergent regions between winter and spring/semi-winter and the strongest divergent regions between spring and semi-winter were found to overlap with the dynamic QTLs responsible for the differentiated i-traits at multiple growth stages. Our study provides important insights into the divergence of plant architecture in the vegetative growth stage among the three ecotypes, which was contributed to by the genetic differentiation, and might contribute to environmental adaption and yield improvement.

When the sliding bearing is fixed only at the top of the middle column of the underground structure, the cracks at the side end of the middle plate should be aggravated while the seismic damage of the mid-column should be alleviated. To enhance the seismic performance of the mid-plate, a new isolation design method has been mentioned while the elastic sliding bearings are set at the top of the mid-columns and between the side end of the mid-plate and the side wall at the same time. By establishing a nonlinear finite element analysis model for the static-dynamic coupling interaction system, the seismic response characteristics of the cast-in-place station structure without a sliding bearing have been analyzed and compared with those of the station structure with the sliding bearing fixed only at the top of the middle columns, and those of the station structure with sliding bearing be fixed between the mid-plate and the sidewall at the same time. The results show that the new isolation station structures suffer fewer earthquake damages at the mid-plate and mid-columns at the same time, which can improve the overall seismic performance of the subway station structure.

Panicle number is directly related to rice yield, so panicle detection and counting has always been one of the most important scientific research topics. Panicle counting is a challenging task due to many factors such as high density, high occlusion, and large variation in size, shape, posture et.al. Deep learning provides state-of-the-art performance in object detection and counting. Generally, the large images need to be resized to fit for the video memory. However, small panicles would be missed if the image size of the original field rice image is extremely large. In this paper, we proposed a rice panicle detection and counting method based on deep learning which was especially designed for detecting rice panicles in rice field images with large image size. Different object detectors were compared and YOLOv5 was selected with MAPE of 3.44% and accuracy of 92.77%. Specifically, we proposed a new method for removing repeated detections and proved that the method outperformed the existing NMS methods. The proposed method was proved to be robust and accurate for counting panicles in field rice images of different illumination, rice accessions, and image input size. Also, the proposed method performed well on UAV images. In addition, an open-access and user-friendly web portal was developed for rice researchers to use the proposed method conveniently.

Abstract Background Hepatocellular carcinoma (HCC) remains a medical challenge due to its high proliferation and metastasis. Although deubiquitinating enzymes (DUBs) play a key role in regulating protein degradation, their pathological roles in HCC have not been fully elucidated. Methods By using biomass spectrometry, co-immunoprecipitation, western blotting and immunofluorescence assays, we identify ribosomal protein S16 (RPS16) as a key substrate of ubiquitin-specific peptidase 1 (USP1). The role of USP1-RPS16 axis in the progression of HCC was evaluated in cell cultures, in xenograft mouse models, and in clinical observations. Results We show that USP1 interacts with RPS16. The depletion of USP1 increases the level of K48-linked ubiquitinated-RPS16, leading to proteasome-dependent RPS16 degradation. In contrast, overexpression of USP1-WT instead of USP1-C90A (DUB inactivation mutant) reduces the level of K48-linked ubiquitinated RPS16, thereby stabilizing RPS16. Consequently, USP1 depletion mimics RPS16 deficiency with respect to the inhibition of growth and metastasis, whereas transfection-enforced re-expression of RPS16 restores oncogenic-like activity in USP1-deficient HCC cells. Importantly, the high expression of USP1 and RPS16 in liver tissue is a prognostic factor for poor survival of HCC patients. Conclusions These findings reveal a previously unrecognized role for the activation of USP1-RPS16 pathway in driving HCC, which may be further developed as a novel strategy for cancer treatment.

Abstract Background Bronchopleural fistula (BPF) refers to an abnormal channel between the pleural space and the bronchial tree. It is a potentially fatal postoperative complication after pulmonary resection and a complex challenge for thoracic surgeons because many patients with BPF ultimately develop refractory empyema, which is difficult to manage and has a major impact on quality of life and survival. Therefore, an operative intervention combined with conservative and endoscopic therapies may be required to control infection completely, to occlude BPF, and to obliterate the empyema cavity during treatment periods. Case presentation Two patients who suffered from BPF complicated with chronic empyema after lobectomy were treated in other hospitals for a long time and did not recover. In our department, we performed staged surgery and creatively combined an Amplatzer Septal Occluder (ASO) device (AGA Medical Corp, Golden Valley, MN, USA) with pedicled muscle flap transposition. First, open-window thoracostomy (OWT), or effective drainage, was performed according to the degree of contamination in the empyema cavity after the local infection was controlled. Second, Amplatzer device implantation and pedicled muscle flap transposition was performed at the same time, which achieved the purpose of obliterating the infection, closing the fistula, and tamponading the residual cavity. The patients recovered without complications and were discharged with short hospitalization stays. Conclusions We believe that the union of the Amplatzer device and pedicle muscle flap transposition seems to be a safe and effective treatment for BPF with chronic empyema and can shorten the length of the related hospital stay.

Due to the quick development of urbanization, it is important to provide a healthy urban environment for the dweller. Previous studies have obtained valuable conclusions of how to improve the urban airflow distribution under isothermal conditions. How to adopt and interpret those conclusions when considering the solar-induced atmospheric stability conditions have not been clarified yet. In this study, the characteristics of atmospheric stability condition and influence of diurnal varying solar-induced thermal effect on urban airflow inside the idealized building arrays were investigated at five cities located at five climate zones in China. Urban energy model, CitySim, was employed to simulate the annual distribution of solar-induced walls’ temperatures inside the idealized building arrays. The diurnal varying wall temperatures at the hottest days were set as thermal boundary conditions in computational fluid dynamic (CFD) simulations. With albedo value of 0.5, the possibility of adopting the results from isothermal condition directly ranged from 7% to 11% for the five cities in China throughout the year. The unstable condition ocuppied from 19% to 24% annually and the stable condition of more than 40% annually was observed. Under the diurnal varying solar-induced thermal effect, the spatially-averaged air speeds and airflow patterns were significantly different from the isothermal conditions. The percent of Richardson number under different atmospheric stability conditions annually based on the Citysim simulation results indicated that the atmospheric stability was most likely determined by the local climate characteristics and albedo value rather than the building layouts at the five selected cities in China, but this should be further investigated when the shadow effects of surrounding buildings were considered in simulations.

Lung adenocarcinoma (LUAD) is the main pathological subtype of non-small-cell lung cancer. Endoplasmic reticulum stress (ERS) has been found to be involved in multiple tumor-related biological processes. At present, a comprehensive analysis of ERS-related genes in LUAD is still lacking. A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. Then, LASSO Cox regression was used to construct a prognostic signature. Taking the median of signature score as the threshold, patients were separated into high-risk (HR) group and low-risk (LR) group. Tumor mutation burden (TMB), immune cell infiltration, cancer stem cell infiltration, expression of HLA, and immune checkpoints of the two risk groups were analyzed. TIDE score was used to evaluate the response of the two risk groups to immunotherapy. Finally, the gene expression was verified in clinical tissues with RT-qPCR. An eight-gene signature (ADRB2, AGER, CDKN3, GJB2, SFTPC, SLC2A1, SLC6A4, and SSR4) was constructed. TMB and cancer stem cell infiltration were higher in the HR group than the LR group. TIDE score and expression level of HLA were higher in the LR group than the HR group. Expression level of immune checkpoints, including CD28, CD27, IDO2, and others, were higher in the LR group. Multiple drugs approved by FAD, targeting ERS-related genes, were available for the treatment of LUAD. In summary, we established a stable prognostic model based on ERS-related genes to help the classification of LUAD patients and looked for new treatment strategies from aspects of immunity, tumor mutation, and tumor stem cell infiltration.

N-type half-Heusler NbCoSn is a promising thermoelectric material due to favourable electronic properties. It has attracted much attention for thermoelectric applications while the desired p-type NbCoSn counterpart shows poor thermoelectric performance. In this work, p-type NbCoSn has been obtained using Sc substitution at the Nb site, and their thermoelectric properties were investigated. Of all samples, Nb0.95Sc0.05CoSn compound shows a maximum power factor of 0.54 mW/mK2 which is the highest among the previously reported values of p-type NbCoSn. With the suppression of thermal conductivity, p-type Nb0.95Sc0.05CoSn compound shows the highest measured figure of merit ZT = 0.13 at 879 K.

The effects of nanosecond pulsed laser processing (NPLP) on the surface morphology, microstructure, and corrosion resistance properties of Fe-based metallic glass coating were investigated. It was found that after pulsed laser processing, the metallic glass coating retained its amorphous structure; however, cracks were generated on the top of the coating. The thickness of the remelted zone reached about 30 μm, and the microstructure became denser after the remelting process. In addition, most of the original defects in the coating disappeared. The corrosion resistance of Fe-based metallic glass coating after NPLP was increased in 3.5 wt.% NaCl solution.

Constructing novel van der Waals heterostructures (vdWHs) is one of the effective methods for expanding the properties and applications of single materials. In this contribution, a blue phosphorene (Blue P)/MoSi2N4 vertical bilayer vdWH was constructed, and its crystal and electronic structures as well as optical properties were systematically studied via first principles calculation. It was found that the Blue P/MoSi2N4 vdWH with good thermal and dynamic stabilities belongs to the type-II indirect bandgap semiconductor with the bandgap of 1.92 eV, which can efficiently separate electrons and holes. Additionally, the two band edges straddle the redox potential of water, and the charge transfer follows the Z-scheme mode, making the Blue P/MoSi2N4 vdWH a promising catalyst of hydrogen production through splitting water. Meanwhile, the Blue P/MoSi2N4 vdWH has higher optical absorption than its two component monolayers. Both the external electric field and vertical strain can easily tailor the bandgap of Blue P/MoSi2N4 vdWH while still preserving its type-II heterostructure characteristics. Our proposed Blue P/MoSi2N4 vdWH is a promising photovoltaic two-dimensional material, and our findings provided theoretical support for the related experimental exploration.

Abstract Background Rice panicle phenotyping is important in rice breeding, and rice panicle segmentation is the first and key step for image-based panicle phenotyping. Because of the challenge of illumination differentials, panicle shape deformations, rice accession variations, different reproductive stages and the field’s complex background, rice panicle segmentation in the field is a very large challenge. Results In this paper, we propose a rice panicle segmentation algorithm called Panicle-SEG, which is based on simple linear iterative clustering superpixel regions generation, convolutional neural network classification and entropy rate superpixel optimization. To build the Panicle-SEG-CNN model and test the segmentation effects, 684 training images and 48 testing images were randomly selected, respectively. Six indicators, including Qseg, Sr, SSIM, Precision, Recall and F-measure, are employed to evaluate the segmentation effects, and the average segmentation results for the 48 testing samples are 0.626, 0.730, 0.891, 0.821, 0.730, and 76.73%, respectively. Compared with other segmentation approaches, including HSeg, i2 hysteresis thresholding and jointSeg, the proposed Panicle-SEG algorithm has better performance on segmentation accuracy. Meanwhile, the executing speed is also improved when combined with multithreading and CUDA parallel acceleration. Moreover, Panicle-SEG was demonstrated to be a robust segmentation algorithm, which can be expanded for different rice accessions, different field environments, different camera angles, different reproductive stages, and indoor rice images. The testing dataset and segmentation software are available online. Conclusions In conclusion, the results demonstrate that Panicle-SEG is a robust method for panicle segmentation, and it creates a new opportunity for nondestructive yield estimation.

Abstract With progress of genetic sequencing technology, plant genomics has experienced rapid development and subsequently triggered the progress of plant phenomics. In this study, a high-throughput hyperspectral imaging system (HHIS) was developed to obtain 1,540 hyperspectral indices at whole-plant level during tillering, heading, and ripening stages. These indices were used to quantify traditional agronomic traits and to explore genetic variation. We performed genome-wide association study (GWAS) of these indices and traditional agronomic traits in a global rice collection of 529 accessions. With the genome-level suggestive P-value threshold, 989 loci were identified. Of the 1,540 indices, we detected 502 significant indices (designated as hyper-traits) that exhibited phenotypic and genetic relationship with traditional agronomic traits and had high heritability. Many hyper-trait-associated loci could not be detected using traditional agronomic traits. For example, we identified a candidate gene controlling chlorophyll content (Chl). This gene, which was not identified based on Chl, was significantly associated with a chlorophyll-related hyper-trait in GWAS and was demonstrated to control Chl. Moreover, our study demonstrates that red edge (680–760 nm) is vital for rice research for phenotypic and genetic insights. Thus, combination of HHIS and GWAS provides a novel platform for dissection of complex traits and for crop breeding.

To study the size effect of nuclear power containment concrete (NPCC) under compressive dynamic performance, the cube concrete specimens with 3 different cube sizes were measured at 10 different loading strain rates using a hydraulic servo, and the failure mode and compressive strength of NPCC were compared and analyzed under different loading conditions. Based on the comparative analysis of experiment results, the following conclusions can be drawn: the effect of loading strain rate has caused NPCC to develop from static strain rate, mainly cement cementitious layer damage and uniform distribution of cracks, to dynamic strain rate, where there are partial coarse aggregate failures and oblique cracks as the main crack distribution. Due to the size effect, the integrity of large-scale NPCC specimen after compression failure is relatively high. With the increase of loading strain rate and decrease of cube size, compressive strength of NPCC is gradually increased, and, with the increase of loading strain rate, the size effect on the mechanical properties of NPCC becomes more significant. Moreover, this paper quantitatively analyzes the influence of the coupling effect of strain rate and size effect on the compressive strength of NPCC, and its mechanism is discussed in depth. The research results are of great significance to the safety of nuclear power concrete containment.

In order to examine the compressive dynamic performance of polypropylene fiber reinforced concrete to be used for the retaining structure under the automobile collision magnitude, an experimental study was carried out by using hydraulic servo on concrete specimens with 4 different polypropylene fiber contents under 6 loading strain rates. The failure modes and stress-strain curves of concrete under different loading conditions were obtained. Then, by comparatively analyzing the mechanical characteristic parameters of polypropylene fiber reinforced concrete under different loading conditions, the following conclusions are drawn: with the increase of the polypropylene fiber content, the integrity of concrete upon compressive failure is gradually improved. When the polypropylene fiber content is relatively high, the static and dynamic failure modes are basically similar. With the increase of the loading strain rate, the peak compressive stress and elastic modulus of the polypropylene fiber reinforced concrete gradually increase. The increase in the polypropylene fiber content gradually intensifies the effect of loading strain rate on the peak compressive stress dynamic improvement coefficient. The peak strain of polypropylene fiber reinforced concrete is gradually increased with the increase of polypropylene fiber content, while the effect of the loading strain rate on the peak strain shows an obvious discreteness characteristic. Meanwhile, we proposed a relationship equation for describing the peak compressive stress dynamic improvement coefficient based on the coupling effect of the polypropylene fiber content and loading strain rate and further discussed the underlying stress mechanism in detail. Our research findings are of important research significance for the application and promotion of polypropylene fiber reinforced concrete in the engineering practice of retaining structures.

CAP1400 nuclear island structure is an advanced and novel nuclear power plant structure. In order to explore the seismic response characteristics of CAP1400 nuclear island structure on soft rock sites, a three-dimensional refined nonlinear seismic response analysis model was established for a soft rock foundation-nuclear island structure system using ABAQUS software. The influences of the input ground motion intensity and the frequency spectrum characteristics on the acceleration, relative displacement, and floor response spectrum, as well as the critical shear wave velocity of nonbedrock sites for CAP1400 nuclear island structure, were proposed. The results suggested that the increasing amplitude of the peak acceleration and relative displacement of nuclear island structure decreased as the soft rock site entered a nonlinear state, and the high-frequency components of the input ground motion became more abundant. Specifically, the earthquake response was the largest at the cooling water tank on the top of the shield building, which was the focus of the seismic research on nuclear island structure. Due to the influence of the ground motion frequency spectrum characteristics and the nonbedrock site effect, the peak acceleration, peak relative displacement, and acceleration response spectrum of the nuclear island structure showed different changing trends for the near-field and far-field ground motions. Based on the influence of the site shear wave velocity on the seismic response of nuclear island structure, it was recommended that the critical shear wave velocity of nonbedrock sites for CAP1400 nuclear island structure should be 1250 m/s, and the nuclear island structure-foundation dynamic interaction could be ignored at this time. The research conclusions could provide some technical support and theoretical basis for the construction and seismic performance research of CAP1400 and other nuclear power plants.

Dense, H2- and CO2-resistant, oxygen-permeable 40 wt % Ce0.9Pr0.1O2–δ–60 wt % NdxSr1−xFe0.9Cu0.1O3−δdual-phase membranes were prepared in a one-pot process. These Nd-containing dual-phase membranes have up to 60% lower material costs than many classically used dual-phase materials. The Ce0.9Pr0.1O2−δ–Nd0.5Sr0.5Fe0.9Cu0.1O3−δ sample demonstrates outstanding activity and a regenerative ability in the presence of different atmospheres, especially in a reducing atmosphere and pure CO2 atmosphere in comparison with all investigated samples. The oxygen permeation fluxes across a Ce0.9Pr0.1O2−δ–Nd0.5Sr0.5Fe0.9Cu0.1O3−δ membrane reached up to 1.02 mL min−1 cm−2 and 0.63 mL min−1 cm−2 under an air/He and air/CO2 gradient at T = 1223 K, respectively. In addition, a Ce0.9Pr0.1O2–δ–Nd0.5Sr0.5Fe0.9Cu0.1O3–δ membrane (0.65 mm thickness) shows excellent long-term self-healing stability for 125 h. The repeated membrane fabrication delivered oxygen permeation fluxes had a deviation of less than 5%. These results indicate that this highly renewable dual-phase membrane is a potential candidate for long lifetime, high temperature gas separation applications and coupled reaction–separation processes.

The significance of small-strain stiffness (Gmax) of saturated composite soils are still of great concern in practice, due to the complex influence of fines on soil fabric. This paper presents an experimental investigation conducted through comprehensive bender element tests on Gmax of marine silty sand. Special attention is paid to the influence of initial effective confining pressure ( σ c 0 ′ ), global void ratio (e) and fines content (FC) on Gmax of a marine silty sand. The results indicate that under otherwise similar conditions, Gmax decreases with decreasing e or FC, but decreases with increasing FC. In addition, the reduction rate of Gmax with e increasing is not sensitive to σ c 0 ′ , but obviously sensitive to changes in FC. The equivalent skeleton void ratio (e*) is introduced as an alternative state index for silty sand with various FC, based on the concept of binary packing material. Remarkably, the Hardin model is modified with the new state index e*, allowing unified characterization of Gmax values for silty sand with various FC, e, and σ c 0 ′ . Independent test data for different silty sand published in the literature calibrate the applicability of this proposed model.

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional genomics in future.

Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have investigated automated rice panicle counting. This paper describes a novel method for automatically and nonintrusively determining rice panicle numbers during the full heading stage by analyzing color images of rice plants taken from multiple angles. Pot-grown rice plants were transferred via an industrial conveyer to an imaging chamber. Color images from different angles were automatically acquired as a turntable rotated the plant. The images were then analyzed and the panicle number of each plant was determined. The image analysis pipeline consisted of extracting the i2 plane from the original color image, segmenting the image, discriminating the panicles from the rest of the plant using an artificial neural network, and calculating the panicle number in the current image. The panicle number of the plant was taken as the maximum of the panicle numbers extracted from all 12 multi-angle images. A total of 105 rice plants during the full heading stage were examined to test the performance of the method. The mean absolute error of the manual and automatic count was 0.5, with 95.3% of the plants yielding absolute errors within ± 1. The method will be useful for evaluating rice panicles and will serve as an important supplementary method for high-throughput rice phenotyping.

Pigments absorb light, transform it into energy, and provide reaction sites for photosynthesis; thus, the quantification of pigment distribution is vital to plant research. Traditional methods for the quantification of pigments are time-consuming and not suitable for the high-throughput digitization of rice pigment distribution. In this study, using a hyperspectral imaging system, we developed an integrated image analysis pipeline for automatically processing enormous amounts of hyperspectral data. We also built models for accurately quantifying 4 pigments (chlorophyll a, chlorophyll b, total chlorophyll and carotenoid) from rice leaves and determined the important bands (700-760 nm) associated with these pigments. At the tillering stage, the R2 values and mean absolute percentage errors of the models were 0.827–0.928 and 6.94–12.84%, respectively. The hyperspectral data and these models can be combined for digitizing the distribution of the chlorophyll with high resolution (0.11 mm/pixel). In summary, the integrated hyperspectral image analysis pipeline and selected models can be used to quantify the chlorophyll distribution in rice leaves. The use of this technique will benefit rice functional genomics and rice breeding.

For many tiller crops, the plant architecture (PA), including the plant fresh weight, plant height, number of tillers, tiller angle and stem diameter, significantly affects the grain yield. In this study, we propose a method based on volumetric reconstruction for high-throughput three-dimensional (3D) wheat PA studies. The proposed methodology involves plant volumetric reconstruction from multiple images, plant model processing and phenotypic parameter estimation and analysis. This study was performed on 80 Triticum aestivum plants, and the results were analyzed. Comparing the automated measurements with manual measurements, the mean absolute percentage error (MAPE) in the plant height and the plant fresh weight was 2.71% (1.08cm with an average plant height of 40.07cm) and 10.06% (1.41g with an average plant fresh weight of 14.06g), respectively. The root mean square error (RMSE) was 1.37cm and 1.79g for the plant height and plant fresh weight, respectively. The correlation coefficients were 0.95 and 0.96 for the plant height and plant fresh weight, respectively. Additionally, the proposed methodology, including plant reconstruction, model processing and trait extraction, required only approximately 20s on average per plant using parallel computing on a graphics processing unit (GPU), demonstrating that the methodology would be valuable for a high-throughput phenotyping platform.

Total green leaf area (GLA) is an important trait for agronomic studies. However, existing methods for estimating the GLA of individual rice plants are destructive and labor-intensive. A nondestructive method for estimating the total GLA of individual rice plants based on multi-angle color images is presented. Using projected areas of the plant in images, linear, quadratic, exponential and power regression models for estimating total GLA were evaluated. Tests demonstrated that the side-view projected area had a stronger relationship with the actual total leaf area than the top-projected area. And power models fit better than other models. In addition, the use of multiple side-view images was an efficient method for reducing the estimation error. The inclusion of the top-view projected area as a second predictor provided only a slight improvement of the total leaf area estimation. When the projected areas from multi-angle images were used, the estimated leaf area (ELA) using the power model and the actual leaf area had a high correlation coefficient (R2 > 0.98), and the mean absolute percentage error (MAPE) was about 6%. The method was capable of estimating the total leaf area in a nondestructive, accurate and efficient manner, and it may be used for monitoring rice plant growth.