Search

Abstract Background Bone defects, resulting from substantial bone loss that exceeds the natural self-healing capacity, pose significant challenges to current therapeutic approaches due to various limitations. In the quest for alternative therapeutic strategies, bone tissue engineering has emerged as a promising avenue. Notably, excretory proteins from Toxoplasma gondii (TgEP), recognized for their immunogenicity and broad spectrum of biological activities secreted or excreted during the parasite’s lifecycle, have been identified as potential facilitators of osteogenic differentiation in human bone marrow mesenchymal stem cells (hBMSCs). Building on our previous findings that TgEP can enhance osteogenic differentiation, this study investigated the molecular mechanisms underlying this effect and assessed its therapeutic potential in vivo. Methods We determined the optimum concentration of TgEP through cell cytotoxicity and cell proliferation assays. Subsequently, hBMSCs were treated with the appropriate concentration of TgEP. We assessed osteogenic protein markers, including alkaline phosphatase (ALP), Runx2, and Osx, as well as components of the BMP/Smad signaling pathway using quantitative real-time PCR (qRT-PCR), siRNA interference of hBMSCs, Western blot analysis, and other methods. Furthermore, we created a bone defect model in Sprague-Dawley (SD) male rats and filled the defect areas with the GelMa hydrogel, with or without TgEP. Microcomputed tomography (micro-CT) was employed to analyze the bone parameters of defect sites. H&E, Masson and immunohistochemical staining were used to assess the repair conditions of the defect area. Results Our results indicate that TgEP promotes the expression of key osteogenic markers, including ALP, Runx2, and Osx, as well as the activation of Smad1, BMP2, and phosphorylated Smad1/5—crucial elements of the BMP/Smad signaling pathway. Furthermore, in vivo experiments using a bone defect model in rats demonstrated that TgEP markedly promoted bone defect repair. Conclusion Our results provide compelling evidence that TgEP facilitates hBMSC osteogenic differentiation through the BMP/Smad signaling pathway, highlighting its potential as a therapeutic approach for bone tissue engineering for bone defect healing.

The degradation of concrete caused by sulfate attack poses a significant challenge to its durability. Using nanomaterials to enhance the mechanical and durability properties of concrete is a promising solution. A study of the durability of nano-alumina (NA)-modified concrete by sulfate erosion was carried out. The results showed that the compressive strength, quality, and permeability of concrete to chloride ions decreased during its long-term erosion by a sodium sulfate solution. The NA-modified concrete exhibited higher resistance to erosion by the sodium sulfate than ordinary concrete (OPC), the rate of reduction in its tensile strength was low, and the resistance of sample NA1 to penetration by chloride ions decreased only by one-fifth compared with that of OPC. The results of mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) tests showed that erosion had severely damaged the pore characteristics and micromorphology of concrete. The total porosities of the OPC and NA1 samples increased from 12.68% and 10.29% to 16.03% and 12.71%, respectively. Their microscopic morphology revealed loose particles and poor compactness. The leading causes of damage to concrete due to erosion by the sodium sulfate were its crystallization pressure and the swelling-induced stress caused by the deposition of crystals in its pores. This study demonstrates that NA can significantly enhance the durability of concrete against sulfate attack, offering valuable insights for strategic applications of NA in concrete materials.

The purpose of this research is to solve the problem of concrete performance deterioration caused by low temperatures in cold regions. Based on the theoretical method of improving the performance of concrete with nanomaterials, the effect of nano-alumina (NA) on the properties of concrete under low- temperature curing is studied from the macro and micro scales. Through the compressive strength test, it is found that low-temperature curing reduces the compressive strength of concrete by more than 15%. Additionally, the incorporation of NA can make up for the adverse effects of low temperatures. Nevertheless, with the increase in the amount of inclusion, the compensation effect is decreasing, and 1% is the optimal amount of NA in concrete. Microscopic test methods such as mercury intrusion porosimetry (MIP), X-ray diffractometry (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM) are used to explore the improvement mechanism of NA on concrete. The test results show that under low-temperature curing conditions, NA can still reduce the total porosity of the mortar in concrete, promote the hydration reaction of cement, consume more calcium hydroxide, generate more calcium silicate hydrate, thereby optimizing the microstructure and improving the performance of the concrete. In the future, the results and methodology of this study will provide guidance and reference for the scientific construction of concrete engineering in cold region environments.

Abstract The severe Zn‐dendrite growth and insufficient carbon‐based cathode performance are two critical issues that hinder the practical applications of flexible Zn‐ion micro‐ssupercapacitors (FZCs). Herein, a self‐adaptive electrode design concept of the synchronous improvement on both the cathode and anode is proposed to enhance the overall performance of FZCs. Polypyrrole doped with anti‐expansion graphene oxide and acrylamide (PPy/GO‐AM) on the cathode side can exhibit remarkable electrochemical performance, including decent capacitance and cycling stability, as well as exceptional mechanical properties. Meanwhile, a robust protective polymeric layer containing reduced graphene oxide and polyacrylamide is self‐assembled onto the Zn surface (rGO/PAM@Zn) at the anode side, by which the “tip effect” of Zn small protuberance can be effectively alleviated, the Zn‐ion distribution homogenized, and dendrite growth restricted. Benefiting from these advantages, the FZCs deliver an excellent specific capacitance of 125 mF cm−2 (125 F cm−3) at 1 mA cm−2, along with a maximum energy density of 44.4 µWh cm−2, and outstanding long‐term durability with 90.3% capacitance remained after 5000 cycles. This conformal electrode design strategy is believed to enlighten the practical design of high‐performance in‐plane flexible Zn‐based electrochemical energy storage devices (EESDs) by simultaneously tackling the challenges faced by Zn anodes and capacitance‐type cathodes.

Abstract It is a challenge to assemble an enormous amount of metagenome data in metagenomics. Usually, metagenome cluster sequence before assembly accelerates the whole process. In SpaRC, sequences are defined as nodes and clustered by a parallel label propagation algorithm (LPA). To address the randomness of label selection from the parallel LPA during clustering and improve the completeness of metagenome sequence clustering, Spark-based parallel label diffusion and label selection community detection algorithm is proposed in the paper to obtain more accurate clustering results. In this paper, the importance of sequence is defined based on the Jaccard similarity coefficient and its degree. The core sequence is defined as the one with the largest importance in its located community. Three strategies are formulated to reduce the randomness of label selection. Firstly, the core sequence label diffuses over its located cluster and becomes the initial label of other sequences. Those sequences that do not receive an initial label will select the sequence label with the highest importance in the neighbor sequences. Secondly, we perform improved label propagation in order of label frequency and sequence importance to reduce the randomness of label selection. Finally, a merge small communities step is added to increase the completeness of clustered clusters. The experimental results show that our proposed algorithm can effectively reduce the randomness of label selection, improve the purity, completeness, and F-Measure and reduce the runtime of metagenome sequence clustering.

Abstract In the mountainous permafrost area, most thaw slumps are distributed in north or northeast-facing shady slope areas. It is commonly known that there is a heterogeneity in permafrost between different slope aspects, but there has been a lack of detailed measured data to quantitatively evaluate their relationships, and in-depth understandings on how the slope aspects are linked to the distribution of thaw slumps. This study examined the heterogenous thermal regime, soil moisture content, and surface radiation at two slope sites with opposing aspects in a warming permafrost region on the Qinghai-Tibet Plateau (QTP). The results indicate that similar air temperatures (Ta) were monitored on the two slopes, but there were significant differences in ground temperature and moisture content in the active layer from 2016 to 2021. The sunny slope exhibited a higher mean annual ground surface temperature (Ts), and over the five years the mean annual temperature at the top of permafrost was 1.3–1.4℃ warmer on the sunny slope than the shady slope. On the contrary, the near-surface soil moisture content was about 10–13% lower on the sunny slope (~22–27%) than the shady slope (~35–38%) during the thawing season (June–September). Radiation data indicate that significantly higher shortwave downward radiation (DR) appeared at the sunny slope site. However, due to the greater surface albedo, the net radiation (Rn) was lower on the sunny slope. Slope aspect also affects the ground ice content due to its influence on ground temperature, freeze-thaw cycles, and soil moisture. Shady slopes have a shallower burial of ice-rich permafrost compared to sunny slopes. The results highlight greatly different near-surface ground thermal conditions at the two slope sites with different aspects in a mountainous permafrost region. This helps identify the slope-related causes of increasing thaw slumps and provides a basis for predicting their future development.

Abstract Background Cancer subtype classification is helpful for personalized cancer treatment. Although, some approaches have been developed to classifying caner subtype based on high dimensional gene expression data, it is difficult to obtain satisfactory classification results. Meanwhile, some cancers have been well studied and classified to some subtypes, which are adopt by most researchers. Hence, this priori knowledge is significant for further identifying new meaningful subtypes. Results In this paper, we present a combined parallel random forest and autoencoder approach for cancer subtype identification based on high dimensional gene expression data, ForestSubtype. ForestSubtype first adopts the parallel RF and the priori knowledge of cancer subtype to train a module and extract significant candidate features. Second, ForestSubtype uses a random forest as the base module and ten parallel random forests to compute each feature weight and rank them separately. Then, the intersection of the features with the larger weights output by the ten parallel random forests is taken as our subsequent candidate features. Third, ForestSubtype uses an autoencoder to condenses the selected features into a two-dimensional data. Fourth, ForestSubtype utilizes k-means++ to obtain new cancer subtype identification results. In this paper, the breast cancer gene expression data obtained from The Cancer Genome Atlas are used for training and validation, and an independent breast cancer dataset from the Molecular Taxonomy of Breast Cancer International Consortium is used for testing. Additionally, we use two other cancer datasets for validating the generalizability of ForestSubtype. ForestSubtype outperforms the other two methods in terms of the distribution of clusters, internal and external metric results. The open-source code is available at https://github.com/lffyd/ForestSubtype . Conclusions Our work shows that the combination of high-dimensional gene expression data and parallel random forests and autoencoder, guided by a priori knowledge, can identify new subtypes more effectively than existing methods of cancer subtype classification.

This research presents the improvement effect and influence mechanism of nano-Al2O3 (NA) and nano-SiO2 (NS) on concrete performance from the macro and micro scales. The crucial parameter investigated in this research is the various concentrations of the nano-reinforcement 1, 2, and 3 wt% of cement, the results show that NA and NS can improve the compressive strength and resistance to chloride penetration (RCP) ability of concrete, the amount of 1 and 2 wt% exhibiting the best effect, especially in terms of compressive strength, which can be increased by more than 20 %. As nanoscale particles, NA and NS can fill the capillary pores in concrete and can also promote the cement hydration to produce more C-S-H gel, thereby reducing the total porosity of concrete by about 2 %, making its internal pores and cracks less and the microstructure denser. Based on the correlation analysis, the most important factors affecting the compressive strength and RCP ability of concrete were found, and the linear relationship equation between compressive strength and RCP ability was obtained.

The permeability of coal reservoir is generally low in China, how to effectively improve the permeability of coal reservoir is a key and difficult point of coalbed methane exploitation, Liquid nitrogen fracturing technology as a kind waterless fracturing technology has received extensive attention in recent years. In order to reveal the influence of liquid nitrogen freezing and freeze-thaw on the mechanical properties of coal, the temperature distribution of coal samples was monitored by infrared thermal imaging technology, and uniaxial compression and acoustic emission tests were performed on the coal samples after the liquid nitrogen freezing and freezethaw, the P-wave velocity, porosity, acoustic emission and energy evolution characteristics of coal samples before and after the freezing and freeze thaw were analyzed. The research result showed that: ①After 360 min freezing and 12 freeze-thaw cycles, the P-wave velocity of coal samples decreased by 58.2% and 64.7%, respectively. The P-wave velocity does not decrease significantly during the initial freezing and freeze-thaw cycle stages, the velocity gradually decreases with the increase of freezing time and freeze-thaw cycles. ②The temperature of the coal sample gradually decreases with increase of freezing times. The surface temperature of the coal sample drops below -60°C after the liquid nitrogen frozen for 180s, the temperature distribution fluctuations at the center of the coal sample occurs due to the different thermal conduction coefficient of the coal particles. ③After liquid nitrogen freezing and freezethaw, the elastic modulus of coal sample decreases exponentially, while the porosity gradually increases. The increase in porosity of the coal sample after liquid nitrogen freeze-thaw is greater than that after liquid nitrogen freezing. ④The acoustic emission activity of coal samples during uniaxial loading is divided into development phase, active phase and severe phase, the maximum acoustic emission ringing count and cumulative acoustic emission ringing count of coal samples increase with the increase of freezing time and freeze-thaw cycles. ⑤Liquid nitrogen freezing and freeze-thaw will weaken the energy storage limit of coal sample, resulting in the reduction of the total energy, elastic energy and dissipated energy at the peak point during the uniaxial loading process.

Heterogeneous ground thermal conditions caused by slope orientation are significant in Qinghai-Tibet Plateau because of the high altitude and strong solar radiation. Variation in solar radiation may result in contrasting thermal and upper boundary conditions, causing engineering problems at infrastructure with sloped embankments. Quantitative research on conditions on different man-made slopes is insufficient in permafrost regions, and consequently, planning for long-term effects on linear infrastructure is challenging. Net radiation, heat flux, near-surface temperature, soil moisture content, were recorded for one whole year (2021) at a field platform with eight slopes. Slope orientation affected net radiation (Rn) and ground heat flux (G), resulting in different energy balances between slopes. The north facing slope had a lowest Rn (174 W m-2), while the south slope had a maximum (239.8 W m-2). The north slope had a negative annual heat flux (-0.7 W m-2), while a maximum positive flux (1.5 W m-2) was recorded on the southeast slope. The annual mean surface temperature (Ts) was highest on the south slope and lowest on the north slope. The maximum difference of ground temperatures (within 30 cm depth) (Tg), was close to differences in Ts of over 4 °C. The maximum difference in soil moisture content during the thawing season (May–October) was 11% between the W and E slopes. Due to the different ground temperatures and soil moisture conditions, the annual number of freeze-thaw cycles was variable, and the maximum freeze-thaw cycles were 106 times in south slope and the minimum were 18 times in west slope. Those different thermal conditions between different slope orientations were significant, and pertinent to planning and maintenance of infrastructure. The results provide accurate boundary conditions for modeling to support development of new infrastructure that have embankment slopes in any direction, and for ensuring the stability of existing structures on Qinghai-Tibet Plateau.

Hericium erinaceus, an edible and medicinal mushroom, has been utilized since ancient China due to its delicious taste and health benefits. The polysaccharide from H. erinaceus (HEP) is supposed to be one of the major bioactive compounds, which garnered widespread attention in seeking innovative applications for precision nutrition. Both in vitro and in vivo studies have shown that HEP possesses antioxidant and anti-aging, gastrointestinal protecting, anti-tumor, hypolipidemic and hypoglycemic, immune-enhancing, neuroprotective, and hepatoprotective activities, verifying its functional benefits to human health. This review provides an overview of the extraction and structure of HEP, and concluded that HEP had different structures with different sources of H. erinaceus and extraction methods. Besides, the biochemical and pharmacological properties of HEP as well as the relative mechanism were highlighted and summarized on the basis of in vivo and in vitro studies, which could be helpful for the healthy application of HEP. Finally, the research prospects of HEP for specific populations or precision nutrition were proposed.

With the strengthening of worldwide counter-terrorism initiatives, it is increasingly important to detect contrabands such as controlled knives and flammable materials hidden in clothes and bags. Terahertz (THz) imaging technology is widely used in the field of contraband detection due to its advantages of high imaging speed and strong penetration. However, the terahertz images are of poor qualities and lack texture details. Traditional target detection methods suffer from low detection speeds, misdetection, and omission of contraband. This work pre-processes the original dataset using a variety of image processing methods and validates the effect of these methods on the detection results of YOLOv7. Meanwhile, the lightweight and multi-object detection YOLOv7 (LWMD-YOLOv7) algorithm is proposed. Firstly, to meet the demand of real-time for multi-target detection, we propose the space-to-depth mobile (SPD_Mobile) network as the lightweight feature extraction network. Secondly, the selective attention module large selective kernel (LSK) network is integrated into the output of the multi-scale feature map of the LWMD-YOLOv7 network, which enhances the effect of feature fusion and strengthens the network’s attention to salient features. Finally, Distance Intersection over Union (DIOU) is used as the loss function to accelerate the convergence of the model and to have a better localisation effect for small targets. The experimental results show that the YOLOv7 algorithm achieves the best detection results on the terahertz image dataset after the non-local mean filtering process. The LWMD-YOLOv7 algorithm achieves a detection accuracy P of 98.5%, a recall R of 97.5%, and a detection speed of 112.4 FPS, which is 26.9 FPS higher than that of the YOLOv7 base network. The LWMD-YOLOv7 achieves a better balance between detection accuracy and detection speed. It provides a technological reference for the automated detection of contraband in terahertz images.

Cereal and oil video surveillance data play a vital role in food traceability, which not only helps to ensure the quality and safety of food, but also helps to improve the efficiency and transparency of the supply chain. Traditional video surveillance systems mainly adopt a centralized storage mode, which is characterized by the deployment of multiple monitoring nodes and a large amount of data storage. It is difficult to guarantee the data security, and there is an urgent need for a solution that can achieve the safe and efficient storage of cereal and oil video surveillance data. This study proposes a blockchain-based abnormal data storage model for cereal and oil video surveillance. The model introduces a deep learning algorithm to process the cereal and oil video surveillance data, obtaining images with abnormal behavior from the monitoring data. The data are stored on a blockchain after hash operation, and InterPlanetary File System (IPFS) is used as a secondary database to store video data and alleviate the storage pressure on the blockchain. The experimental results show that the model achieves the safe and efficient storage of cereal and oil video surveillance data, providing strong support for the sustainable development of the cereal and oil industry.

Permafrost areas are sensitive to climate change and have a significant impact on energy and water cycles. Ground ice is a crucial component on the Qinghai–Tibetan Plateau (QTP). Understanding the environmental characteristics of ground ice is vital for accurately modeling its distribution and evolution. In this study, we analyzed 15 environmental characteristics of high ice-content permafrost sites. These attributes were extracted from 400 high ice-content permafrost datasets including 300 drilling boreholes and 100 thaw slumps collected throughout the entire plateau using large-scale remote sensing data and their products. The results are as follows: The mean annual air temperature in areas where high ice-content permafrost exists ranges from −5 to −3.5 °C, with an average warming rate of 0.08 °C/a. Additionally, there was an average increase in precipitation of about 25 mm/10a and an increase in soil moisture of about 4%/10a. Geomorphology strongly influences the occurrence of high ice content permafrost, with 85% of high ice-content permafrost development at altitudes between 4400 and 5100 m. Approximately 86% of high ice-content permafrost were developed in lowland or relatively flat areas, preferably in gently sloping and shady slope regions. Soils exhibit less variability in clay particles and more variability in silt and sand. Key indicators in the high ice content permafrost region include warming rate, active layer thickness, elevation, bulk density, soil thickness, clay content, precipitation, soil moisture, and NDVI. High ice-content permafrost is the result of a combination of environmental factors and is expected to undergo significant changes in the future. This study provides a foundation for comprehending the environmental changes in the high ice-content permafrost areas and modeling the distribution of ground ice. It underscores the urgent need to address the significant environmental changes faced by high ice-content permafrost regions.

The structure of the grain-and-oil-food-supply chain has the characteristics of complexity, cross-regionality, a long cycle, and numerous participants, making it difficult to maintain the safety of supply. In recent years, some phenomena have emerged in the field of grain procurement and sale, such as topping the new with the old, rotating grains, the pressure of grades and prices, and counterfeit oil food, which have seriously threatened grain-and-oil-food security. Blockchain technology has the advantage of decentralization and non-tampering Therefore, this study analyzes the characteristics of traceability data in the grain-and-oil-food-supply chain, and presents a blockchain-based traceability model for the grain-and-oil-food-supply chain. Firstly, a new method combining blockchain and machine learning is proposed to enhance the authenticity and reliability of blockchain source data by constructing anomalous data-processing models. In addition, a lightweight blockchain-storage method and a data-recovery mechanism are proposed to reduce the pressure on supply-chain-data storage and improve fault tolerance. The results indicate that the average query delay of public data is 0.42 s, the average query delay of private data is 0.88 s, and the average data-recovery delay is 1.2 s. Finally, a blockchain-based grain-and-oil-food-supply-chain traceability system is designed and built using Hyperledger Fabric. Compared with the existing grain-and-oil-food-supply chain, the model constructed achieves multi-source heterogeneous data uploading, lightweight storage, data recovery, and traceability in the supply chain, which are of great significance for ensuring the safety of grain-and-oil food in China.

The Jiaopenba landslide, which represents a typical large basalt high-speed remote landslide, is located in Emeishan City, southwestern Sichuan province, China. Based on the field investigation, the characteristics of the Jiaopenba landslide have been revealed. The Jiaopenba landslide occurred on the steep Mount Emei. Landslide materials with a volume of approximately 6.75×108 m3 slid down from a high position, forming a large-scale high-speed remote debris flow, with the farthest sliding distance of about 7.5 km. The landslide area is located in the west wing of the Emeishan anticline, which is cut by faults to form a monoclinal fault-block mountain. Although the shear outlet of the landslide is near the slope toe and does not have good free conditions, there are faults passing through the slope toe of the bedding slope of the fault hanging wall, the landslide is affected by the fault activity, and the integrity of the layered slope is poor. When the foot of the slope is empty, the fault zone is compressed and plastic extrusion, which leads to bedding slip of the slope rock mass and greatly weakens the interlayer bonding force. When coupled with long structural planes on both sides to form side crack planes, a large-scale inclined plate structure is formed. Under the action of a strong earthquake and other external forces, the rock mass near the fault can be damaged by tension, and a large-scale high-position landslide can be formed by the mode of compression-slip-tension fracture.

The complex mechanical properties of deep water-sensitive rocks during construction bring great challenges to the construction and stability analysis of underground engineering in water-sensitive strata. Taking Xianglu Mountain Tunnel in the Central Yunnan Water Diversion Project as the engineering background, the mechanical properties of two types of water-sensitive rocks including limestone and silty mudstone were studied through laboratory tests, and a nonlinear strength model based on Hoek-Brown criterion was proposed. The results show that (1) the stress-strain curves of deep limestone and silty mudstone have significant strain softening characteristics and brittle-ductile transformation trend. Compared with limestone, silty mudstone has stronger ductility and lower critical confining pressure for brittle-ductile transformation; (2) the dilation effect of rock is affected by both confining pressure and plastic deformation. Under the same confining pressure and plastic deformation, the dilation characteristic of limestone is more evident than that of silty mudstone; (3) the Hoek-Brown criterion can describe the nonlinear strength characteristics of deep rock well. The evolution law of strength parameters mb and s with modified plastic shear strain conforms to the negative exponential function, while the relationship between strength parameter a and modified plastic shear strain satisfies cubic polynomial function; (4) the simulation results based on the nonlinear strength model are consistent with the test results, and the established strength model has high reliability. The research results can provide a basis for the stability analysis of the Xianglu Mountain Tunnel and the optimal design of the supporting structure and can also provide a reference for the study of the mechanical characteristics of the deep rocks in water-sensitive strata.

The coupling effect between the stress field formed by rock mass and the seepage field formed by groundwater has an important impact on the stability of underground engineering. In order to conduct the fluid-solid coupling physical model test in the laboratory, it is necessary to develop suitable analogous materials. In this study, a new type of analogous material reflecting the fluid-solid coupling effect is developed with iron powder, barite powder, and quartz sand as aggregates, white cement as a cementing agent, and silicone oil as a regulator. Through a large number of orthogonal experiments, the influence laws of different material contents on the mechanical properties and permeability characteristics of analogous materials are obtained. In addition, a method for quickly determining the proportion of components in fluid-solid coupling analogous materials is also proposed. The developed analogous material is employed in the fluid-solid coupling physical model test of a deep tunnel. The variation laws of rock stress, displacement, and seepage pressure around the tunnel during construction are obtained, which verifies the feasibility of the developed analogous material.

Flavonoids give plants their rich colors and play roles in a number of physiological processes. In this study, we identified a novel colorless maize mutant showing reduced pigmentation throughout the whole life cycle by EMS mutagenesis. E183K mutation in maize chalcone synthase C2 (ZmC2) was mapped using MutMap strategy as the causal for colorless, which was further validated by transformation in Arabidopsis. We evaluated transcriptomic and metabolic changes in maize first sheaths caused by the mutation. The downstream biosynthesis was blocked while very few genes changed their expression pattern. ZmC2-E183 site is highly conserved in chalcone synthase among Plantae kingdom and within species’ different varieties. Through prokaryotic expression, transient expression in maize leaf protoplasts and stable expression in Arabidopsis, we observed that E183K and other mutations on E183 could cause almost complete protein aggregation of chalcone synthase. Our findings will benefit the characterization of flavonoid biosynthesis and contribute to the body of knowledge on protein aggregation in plants.

The unconfined penetration test (UP test) is one of the indirect methods to measure the tensile strength of soils. Through a series of UP tests of undisturbed and remolded loess, the split angle (α) of the wedge body which was shaped in the process of the experiment was discussed. And then, the particle movement, the force transfer, and the fracture development law of the sample were studied by the distinct element method (PFC2D). The experiment and numerical simulation results show the following: (1) the split angle (α) presents an exponential decrease with tensile strength (σt) and a linear decrease with internal friction angle (φ); (2) K that can be written as tan (2α + φ) is a coefficient to calculate tensile strength, which is equal to 2.00 for remolded loess and 1.50 for undisturbed loess; (3) the distinct element simulation shows that the resisting force by the UP test comes from both tensile stress and shear stress; (4) the tensile fractures and shear fractures appear at almost the same time when the tensile stress is approximately 70% of tensile strength.

During development of substitute anode materials suitable for solid oxide fuel cell (SOFC), understanding of sintering mechanisms and effects is significant for synthesized porous structures and performance. A molecular dynamics (MD) model is developed and applied in this study for the SOFC anode sintered materials to reveal the sintering condition effects. It is predicted that, for the case of two nanoparticles of electron-conducting La-doped SrTiO3 (LST), the higher the sintering temperature, the faster the aggregation of nanoparticles and the higher the sintering degree. An increase in the nanoparticle size could delay the sintering, process but does not affect the final sintering degree. The MD model is further applied for the case of the multi-nanoparticles containing LST and ion-conducting electrolyte materials of gadolinium-doped ceria (GDC), i.e., the LST-GDC particles. The sintering conditions and effects on the LST-GDC particles are evaluated, in terms of the mean square displacement (MSD) and various structural parameters. Two important thermal properties are also calculated that agree well with the experimental values. The findings obtained from this study are useful to identify the optimized sintering parameters for development of the SOFC electrode materials.