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Ensuring the safety of oil tank farms is essential to maintaining energy security and minimizing the impact of potential accidents. This paper develops a quantitative regional risk model designed to assess both individual and societal risks in oil tank farms, with particular attention to energy-related risks such as leaks, fires, and explosions. The model integrates factors like day–night operational variations, weather conditions, and risk superposition to provide a comprehensive and accurate evaluation of regional risks. By considering the cumulative effects of multiple hazards, including those tied to energy dynamics, and the stability and validity of the model are researched through Monte Carlo simulations and case application. The results show that the model enhances the reliability of traditional risk assessment methods, making it more applicable to oil tank farm safety concerns. Furthermore, this study introduces a practical tool that simplifies the risk assessment process, allowing operators and decision-makers to evaluate risks without requiring in-depth technical expertise. The methodology improves the ability to safeguard oil tank farms, ensuring the stability of energy supply chains and contributing to broader energy security efforts. This study provides a valuable method for researchers and engineers seeking to enhance regional risk calculation efficiency, with a specific focus on energy risks.

The surface material of an object is a key factor that affects non-line-of-sight (NLOS) imaging. In this paper, we introduce the bidirectional reflectance distribution function (BRDF) into NLOS imaging to study how the target surface material influences the quality of NLOS images. First, the BRDF of two surface materials (aluminized insulation material and white paint board) was modeled using deep neural networks and compared with a five-parameter empirical model to validate the method’s accuracy. The method was then applied to fit BRDF data for different common materials. Finally, NLOS target simulations with varying surface materials were reconstructed using the confocal diffusion tomography algorithm. The reconstructed NLOS images were classified via a convolutional neural network to assess how different surface materials impacted imaging quality. The results show that image clarity improves when decreasing the specular reflection and increasing the diffuse reflection, with the best results obtained for surfaces exhibiting a high diffuse reflection and no specular reflection.

Methane emissions from ruminants significantly contribute to greenhouse gases. This study explores the methane mitigation effect and mechanism of S. mcclurei through in vitro rumen fermentation, aiming to establish its potential as a feed additive. We investigated the effects of freeze-dried and dried S. mcclurei at supplementation levels of 2%, 5%, and 10% of dry matter on nutrient degradation, ruminal fermentation, methane inhibition, and microbial community structure in in vitro rumen fermentation. The freeze-dried S. mcclurei at 2% supplementation significantly reduced CH4 emissions by 18.85% and enhanced crude protein degradability. However, total VFA and acetate concentrations were lower in both treatments compared to the control. The microbial shifts included a decrease in Lachnospiraceae_NK3A20_group and Ruminococcus and an increase in Selenomonas, Succinivibrio, and Saccharofermentans, promoting propionate production. Additionally, a significant reduction in Methanomicrobium was observed, indicating direct methane mitigation. Freeze-dried S. mcclurei at a 2% supplementation level shows potential as an effective methane mitigation strategy with minimal impact on rumen fermentation, supported by detailed insights into microbial community changes.

To systematically study the influence of a propensity for a particular driving style on car-following risk, a safety potential field risk-quantification method that considers driving style is proposed. First, we classify driving behaviors and construct a field-based safety potential car-following model via analogy with intermolecular interactions; second, we establish a risk-quantification model by considering driving style, risk exposure, and risk severity and classify the consequent risk into four levels, high risk, medium risk, low risk, and safe, using the fuzzy C-means algorithm. Finally, we predict the car-following risk using the LightGBM algorithm in real time. The experimental results show that the LightGBM algorithm can recognize up to 86% of medium–high risk levels compared to the Decision Tree and Random Forest Algorithms. It can achieve effective prediction of car-following risk, which provides sufficient warning information to drivers and helps improve the overall safety of vehicle operation.

Sweet potato (Ipomoea batatas (L.) Lam.) is one of the most widely cultivated crops in the world, with outstanding stress tolerance, but drought stress can lead to a significant decrease in its yield. To reveal the response mechanism of sweet potato to drought stress, an integrated physiological, transcriptome and metabolome investigations were conducted in the leaves of two sweet potato varieties, drought-tolerant zhenghong23 (Z23) and a more sensitive variety, jinong432 (J432). The results for the physiological indexes of drought showed that the peroxidase (POD) and superoxide dismutase (SOD) activities of Z23 were 3.68 and 1.21 times higher than those of J432 under severe drought, while Z23 had a higher antioxidant capacity. Transcriptome and metabolome analysis showed the importance of the amino acid metabolism, respiratory metabolism, and antioxidant systems in drought tolerance. In Z23, amino acids such as asparagine participated in energy production during drought by providing substrates for the citrate cycle (TCA cycle) and glycolysis (EMP). A stronger respiratory metabolism ability could better maintain the energy supply level under drought stress. Drought stress also activated the expression of the genes encoding to antioxidant enzymes and the biosynthesis of flavonoids such as rutin, resulting in improved tolerance to drought. This study provides new insights into the molecular mechanisms of drought tolerance in sweet potato.

This study simulated the wind energy density distribution in the Jiaodong Peninsula region using the Weather Research and Forecasting (WRF) Model. The impacts of different boundary-layer and near-surface parameterization schemes on the simulated wind speed and direction were investigated. The results indicate that the Yonsei University (YSU) scheme and the Quasi-Normal Scale Elimination (QNSE) scheme performed optimally for wind speed and wind direction. We also conducted a sensitivity test of the simulation results for atmospheric pressure, air temperature, and relative humidity. The statistical analysis showed that the YSU scheme performed optimally, while the MRF and BL schemes performed poorly. Following this, the wind energy distribution in the coastal hilly areas of the Jiaodong Peninsula was simulated using the YSU boundary-layer parameterization scheme. The modeled wind energy density in the mountainous and hilly areas of the Jiaodong Peninsula were higher than that in other regions. The wind energy density exhibits a seasonal variation, with the highest values in spring and early summer and the lowest in summer. In spring, the wind energy density over the Bohai Sea is higher than over the Yellow Sea, while the opposite trend is modeled in summer.

The high resistance connection fault of the stator is a common fault in doubly fed induction generators, which causes a three-phase imbalance in the stator circuit. Since the stator winding is directly connected to the power grid, interference from the asymmetric power grid must be eliminated in order to achieve the accurate diagnosis of stator resistance imbalance faults. Therefore, a new diagnosis method based on filter shunt capacitor banks is proposed in this paper. By introducing shunt capacitor banks, an artificial neutral point is constructed to replace the neutral point of the power grid. Then, the neutral point voltage of the stator winding relative to the artificial neutral point is selected as a fault characteristic signal. In this paper, the change in three-phase stator currents after a high-resistance connection fault is analyzed in detail, and by comparing the fault characteristic signal with three-phase stator currents, the fault phase location and fault severity of high-resistance connection can be accurately obtained. Finally, simulations are carried out via the field-circuit coupling method to validate the effectiveness of the proposed method.

When the direct visible-light channel is affected by people walking or other obstacles, the shadow effect formed in the receiver space affects communication performance and can even lead to communication interruption. In this paper, two numerical methods for calculating the shadow area of the human body were proposed for an indoor multi-light communication system. The influence of shadows on system performance was analyzed using the mean square errors of illuminance and signal-to-noise ratio, as well as the interrupt probability, as parameters. The results showed that shadows had a great influence on the performance of the visible-light communication system. When the number of light sources was fixed, the shadow effect could be effectively reduced by optimizing the layout of the light sources. These research results can provide a theoretical basis for improving the stability of visible-light communication systems.

Stem nematode disease can seriously reduce the yield of sweet potato (Ipomoea batatas (L.) Lam). To explore resistance mechanism to stem nematode in sweet potato, transcriptomes and metabolomes were sequenced and compared between two sweet potato cultivars, the resistant Zhenghong 22 and susceptible Longshu 9, at different times after stem nematode infection. In the transcriptional regulatory pathway, mitogen-activated protein kinase signaling was initiated in Zhenghong 22 at the early stage of infection to activate genes related to ethylene production. Stem nematode infection in Zhenghong 22 also triggered fatty acid metabolism and the activity of respiratory burst oxidase in the metabolic pathway, which further stimulated the glycolytic and shikimic pathways to provide raw materials for secondary metabolite biosynthesis. An integrated analysis of the secondary metabolic regulation pathway in the resistant cultivar Zhenghong 22 revealed the accumulation of tryptophan, phenylalanine, and tyrosine, leading to increased biosynthesis of phenylpropanoids and salicylic acid and enhanced activity of the alkaloid pathway. Stem nematode infection also activated the biosynthesis of terpenoids, abscisic acid, zeatin, indole, and brassinosteroid, resulting in improved resistance to stem nematode. Finally, analyses of the resistance regulation pathway and a weighted gene co-expression network analysis highlighted the importance of the genes itf14g17940 and itf12g18840, encoding a leucine-rich receptor-like protein and 1-aminocyclopropane-1-carboxylate synthase, respectively. These are candidate target genes for increasing the strength of the defense response. These results provide new ideas and a theoretical basis for understanding the mechanism of resistance to stem nematode in sweet potato.

High long-term stress on the plantar fascia (PF) is the main cause of plantar fasciitis. Changes in the midsole hardness (MH) of running shoes are an important factor leading to the alteration of the PF. This study aims to establish a finite-element (FE) model of the foot–shoe, and investigates the effects of midsole hardness on PF stress and strain. The FE foot–shoe model was built in ANSYS using computed-tomography imaging data. Static structural analysis was used to simulate the moment of running push and stretch. Plantar stress and strain under different MH levels were quantitatively analyzed. A complete and valid 3D FE model was established. With an increase in MH from 10 to 50 Shore A, the overall stress and strain of the PF were decreased by approximately 1.62%, and the metatarsophalangeal (MTP) joint flexion angle was decreased by approximately 26.2%. The height of the arch descent decreased by approximately 24.7%, but the peak pressure of the outsole increased by approximately 26.6%. The established model in this study was effective. For running shoes, increasing the MH reduces the stress and strain of PF, but also imposes a higher load on the foot.

Leishmaniasis is a neglected tropical disease that seriously influences global public health. Among all the parasitic diseases, leishmaniasis is the third most common cause of morbidity after malaria and schistosomiasis. Circular RNAs (circRNAs) are a new type of noncoding RNAs that are involved in the regulation of biological and developmental processes. However, there is no published research on the function of circRNAs in leishmaniasis. This is the first study to explore the expression profiles of circRNAs in leishmaniasis. GO and KEGG analyses were performed to determine the potential function of the host genes of differentially expressed circRNAs. CircRNA–miRNA–mRNA (ceRNA) regulatory network analysis and protein–protein interaction (PPI) networks were analyzed by R software and the STRING database, respectively. A total of 4664 significant differentially expressed circRNAs were identified and compared to those in control groups; a total of 1931 were up-regulated and 2733 were down-regulated. The host genes of differentially expressed circRNAs were enriched in ubiquitin-mediated proteolysis, endocytosis, the MAPK signaling pathway, renal cell carcinoma, autophagy and the ErbB signaling pathway. Then, five hub genes (BRCA1, CREBBP, EP300, PIK3R1, and CRK) were identified. This study provides new evidence of the change of differentially expressed circRNAs and its potential function in leishmaniasis. These results may provide novel insights and evidence for the diagnosis and treatment of leishmaniasis.

The high-affinity potassium transporters (HKT) mediate K+-Na+ homeostasis in plants. However, the function of enhancing low-potassium tolerance in sweet potato [Ipomoea batatas (L.) Lam.] remains unrevealed. In this study, a novel HKT transporter homolog IbHKT-like gene was cloned from sweet potato, which was significantly induced by potassium deficiency stress. IbHKT-like overexpressing transgenic roots were obtained from a sweet potato cultivar Xuzishu8 using an Agrobacterium rhizogenes-mediated root transgenic system in vivo. Compared with the CK, whose root cells did not overexpress the IbHKT-like gene, overexpression of the IbHKT-like gene protected cell ultrastructure from damage, and transgenic root meristem cells had intact mitochondria, endoplasmic reticulum, and Golgi dictyosomes. The steady-state K+ influx increased by 2.2 times in transgenic root meristem cells. Overexpression of the IbHKT-like gene also improved potassium content in the whole plant, which increased by 63.8% compared with the CK plants. These results could imply that the IbHKT-like gene, as a high-affinity potassium transporter gene, may play an important role in potassium deficiency stress responses.

Extensive studies have demonstrated the relationship between static street networks and dynamic pedestrian movement. Street vendors temporarily appear in a vibrant space, closely engaging with numerous pedestrians. Is street vending distribution related to street network configuration? And if so, in what ways? This study investigates the heterogeneous relationships between pedestrians, vendors and the urban and suburban places they inhabit in Yuncheng by contrasting two different types of pedestrian-driven maps. The vending distribution map was identified via semi-structured interviews with urban managers (n = 11) in 2017. The spatial network configuration was examined through space syntax segment angular analysis, containing Integration, Choice and Combined Centrality properties at macro-, meso- and micro-scales. By overlapping the distribution map to the syntactic maps in the Quantum Geographic Information System (QGIS) platform, our results show that street vending distribution is most related to the Choice property at the meso-scale. Using semi-structured interviews (n = 53) and observations at two specific sites, we further found relationships tend to be opposed in urban and suburban areas. The study provides an alternative approach to integrating quantitative and qualitative data, expanding the theoretical and empirical understanding of spatial configuration and urban street activities related to walking and vending. This understanding has the potential to contribute to the design of more liveable street spaces.

The physiological and biochemical characters of muscles derived from pasture-fed or barn-fed black goats were detected, and RNA-seq was performed to reveal the underlying molecular mechanisms to identify how the pasture feeding affected the nutrition and flavor of the meat. We found that the branched chain amino acids, unsaturated fatty acids, and zinc in the muscle of pasture-fed goats were significantly higher than those in the barn-fed group, while the heavy metal elements, cholesterol, and low-density lipoprotein cholesterol were significantly lower. RNA-seq results showed that 1761 genes and 147 lncRNA transcripts were significantly differentially expressed between the pasture-fed and barn-fed group. Further analysis found that the differentially expressed genes were mainly enriched in the myogenesis and Glycerophospholipid metabolism pathway. A functional analysis of the lncRNA transcripts further highlighted the difference in fatty acid metabolism between the two feeding models. Our study provides novel insights into the gene regulation and network organization of muscles and could be potentially used for improving the quality of mutton.

Point set is a major type of 3D structure representation format characterized by its data availability and compactness. Most former deep learning-based point set models pay equal attention to different point set regions and channels, thus having limited ability in focusing on small regions and specific channels that are important for characterizing the object of interest. In this paper, we introduce a novel model named Attention-based Point Network (AttPNet). It uses attention mechanism for both global feature masking and channel weighting to focus on characteristic regions and channels. There are two branches in our model. The first branch calculates an attention mask for every point. The second branch uses convolution layers to abstract global features from point sets, where channel attention block is adapted to focus on important channels. Evaluations on the ModelNet40 benchmark dataset show that our model outperforms the existing best model in classification tasks by 0.7% without voting. In addition, experiments on augmented data demonstrate that our model is robust to rotational perturbations and missing points. We also design a Electron Cryo-Tomography (ECT) point cloud dataset and further demonstrate our model’s ability in dealing with fine-grained structures on the ECT dataset.

The role of selenium (Se) and Ulva fasciata as potent cancer chemopreventive and chemotherapeutic agents has been supported by epidemiological, preclinical, and clinical studies. In this study, Se-containing polysaccharide-protein complex (Se-PPC), a novel organoselenium compound, a Se-containing polysaccharide-protein complex in Se-enriched Ulva fasciata, is a potent anti-proliferative agent against human lung cancer A549 cells. Se-PPC markedly inhibited the growth of cancer cells via induction of apoptosis which was accompanied by the formation of apoptotic bodies, an increase in the population of apoptotic sub-G1 phase cells, upregulation of p53, and activation of caspase-3 in A549 cells. Further investigation on intracellular mechanisms indicated that cytochrome C was released from mitochondria into cytosol in A549 cells after Se-PPC treatment. Se-PPC induced depletion of mitochondrial membrane potential (ΔΨm) in A549 cells through regulating the expression of anti-apoptotic (Bcl-2, Bcl-XL) and pro-apoptotic (Bax, Bid) proteins, resulting in disruption of the activation of caspase-9. This is the first report to demonstrate the cytotoxic effect of Se-PPC on human cancer cells and to provide a possible mechanism for this activity. Thus, Se-PPC is a promising novel organoselenium compound with potential to treat human cancers.