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High-strength engineered cementitious composites (HS-ECCs) have garnered significant attention for their superior mechanical properties and ductility. However, their high autogenous shrinkage, caused by a low water-to-binder ratio, high cementitious content, and lack of coarse aggregate, often results in early-age cracking, limiting their broader use in civil engineering. Incorporating iron sand in HS-ECCs has enhanced their mechanical properties, reduced the carbon footprint, and moderately decreased shrinkage strain compared to traditional silica sand; however, the shrinkage strain remains substantial. This study aims to reduce the autogenous shrinkage of HS-ECCs further by incorporating united expanding admixtures (UEAs)—calcium oxide-based (CEA) and magnesium oxide-based (MEA) expansive agents—in varying amounts (3% to 10% by mass of cement). This study also examines the impact of these admixtures on the workability and mechanical properties of HS-ECCs. The results show that increasing the UEA content significantly reduces autogenous shrinkage strain, achieving a 40.66% reduction at 10% UEA, from 1007.31 με to 647.18 με. While higher UEA content decreases workability, as indicated by lower fluidity and penetration depth, the compressive strength remains largely unaffected. The tensile strength peaks at 12.38 MPa with 3% UEA but declines at higher contents, with higher UEA content effectively minimizing crack formation. The novelty of this research lies in the combined use of waste iron sand and UEA, optimizing the balance between workability, mechanical properties, and autogenous shrinkage reduction in HS-ECCs. These findings support the broader application of HS-ECCs in civil engineering projects requiring high mechanical properties and low shrinkage. [ABSTRACT FROM AUTHOR]

Solar greenhouses provide a favorable climate environment for the production of counter-seasonal crops in northern China. The greenhouse environment is a key factor affecting crop growth, so accurate prediction of greenhouse environment changes helps to precisely regulate the crop growth environment and helps to promote the growth of fruits and vegetables. In this study, an environmental prediction model based on the combination of a gradient boosting tree and the Harris hawk optimization algorithm (IHHO-Catboost) is constructed, and in response to the problems of the HHO algorithm, such as the fact that the adjustment of the search process is not flexible enough, it cannot be targeted to carry out a stage search, and sometimes it will fall into the local optimum to make the algorithm's search accuracy relatively poor, an algorithm based on the improved Harris hawk optimization (IHHO) algorithm-based parameter identification method is constructed. The model considers the internal and external environmental and regulatory factors affecting crop growth, which include indoor temperature and humidity, light intensity, carbon dioxide concentration, soil temperature and humidity, outdoor temperature and humidity, light intensity, carbon dioxide concentration, wind direction, wind speed, and opening and closing of upper and lower air openings of the cotton quilt, and is input into a prediction model with a time series for training and testing. The experimental results show that the MAE (mean absolute error) values of temperature, relative humidity, carbon dioxide concentration, and light intensity of the model are reduced to 49.8%, 35.3%, 72.7%, and 32.1%, respectively, compared with LSTM (Long Short-Term Memory), which is a significant decrease in error. It shows that the proposed multi-parameter prediction model for solar greenhouse environments presents an effective method for accurate prediction of environmental data in solar greenhouses. The model not only improves prediction accuracy but also reduces dependence on large data volumes, reduces computational costs, and improves the transparency and interpretability of the model. Through this approach, an effective tool for greenhouse agriculture is provided to help farmers optimize the use of resources, reduce waste, and improve crop yield and quality, ultimately leading to a more efficient and environmentally friendly agricultural production system. [ABSTRACT FROM AUTHOR]

Since China declared that the post-epidemic era would begin in April 2020, the prevention and control of epidemics have become routine. The capacity of cities to respond to future public health emergencies will be enhanced if the resilience of cities is accurately measured and an emphasis is placed on improving resilience levels. Under the 4R framework, this study quantifies and analyzes the level of resilience of the cities in Jiangsu Province from both subjective and objective perspectives. By selecting explanatory variables and developing a GWR model, the spatial distribution characteristics of the quantified scores of resilience and the spatial characteristics of the influencing factors are analyzed. The results indicate that cities in southern Jiangsu should invest more in economic development and medical resources in the post-epidemic period. Northern Jiangsu should prioritize boosting the health and social work sector's gross domestic product. Coastal cities must enhance their capacity for innocuous waste treatment. [ABSTRACT FROM AUTHOR]

With the aging of the social population structure, the number of empty-nesters is also increasing. Therefore, it is necessary to manage empty-nesters with data mining technology. This paper proposed an empty-nest power user identification and power consumption management method based on data mining. Firstly, an empty-nest user identification algorithm based on weighted random forest was proposed. Compared with similar algorithms, the results indicate that the performance of the algorithm is the best, and the identification accuracy of empty-nest users is 74.2%. Then a method for analyzing the electricity consumption behavior of empty-nest users based on fusion clustering index adaptive cosine K-means was proposed, which can adaptively select the optimal number of clusters. Compared with similar algorithms, the algorithm has the shortest running time, the smallest Sum of the Squared Error (SSE), and the largest mean distance between clusters (MDC), which are 3.4281 s, 31.6591 and 13.9513, respectively. Finally, an anomaly detection model with an Auto-regressive Integrated Moving Average (ARIMA) algorithm and an isolated forest algorithm was established. The case analysis shows that the recognition accuracy of abnormal electricity consumption for empty-nest users was 86%. The results indicate that the model can effectively detect the abnormal behavior of empty-nest power users and help the power department to better serve empty-nest users. [ABSTRACT FROM AUTHOR]

Zucchini (Cucurbita pepo L.) is one of the main vegetable crops grown under protected cultivation in northern China. Low-temperature (LT) stress severely inhibits the growth of zucchini seedlings, resulting in reductions in yield and quality. Here, using three kinds of different humic acids, including coal-based humic acid (CHA), fulvic acid (FA), and biochemical humic acid (BHA), we investigated the effects of humic acids against LT stress (5 °C) in zucchini seedlings. Treatment with all three kinds of humic acids improves LT stress tolerance by decreasing oxidative damage through increases in antioxidative enzyme activities and the contents of soluble sugar and proline in zucchini seedlings, especially after BHA application. Comparative transcriptomic analysis revealed that a total of 17 differentially expressed genes (DEGs) were commonly induced in the leaves of FA-, CHA-, and BHA-treated zucchini seedlings under LT stress, including calmodulin, ethylene-responsive transcription factors (TFs), peroxidases, and 10 TFs, including two NAC and seven WRKY genes. Altogether, these results indicated that supplementation with humic acids reprograms plant metabolism and modulates the expression of genes involved in ROS scavenging, phytohormone metabolism, or signaling pathways, finally improving LT stress tolerance in zucchini seedlings. [ABSTRACT FROM AUTHOR]

To combat climate change and meet energy conservation and emission reduction goals, the building sector must adopt low-carbon technologies and low-carbon management methods. To systematically explore existing research areas and track future research trends of carbon emission in the construction stage (CECS), this study conducts a bibliometric and content analysis of CECS studies. 563 relevant publications published between 2000 and 2022 are examined and analyzed using data from the Web of Science (WoS) core collection database. The findings reveal that studies of CECS have evolved through three stages: preliminary exploratory period, stable development period, and rapid development period. In addition, the literature co-citation network and content analysis classify the 13 found co-citation clusters into four knowledge domains: sources definition, data statistics, assessment methods, and carbon reduction strategies. Finally, a knowledge map of CECS studies is presented, outlining significant aspects of research, existing gaps in knowledge, and directions for future study. This work will make it easier for academics and professionals to pinpoint promising areas of study, fill in knowledge gaps, and broaden the scope of existing research on CECS. [ABSTRACT FROM AUTHOR]

Oxidative degradation by using reactive oxygen species (ROS) is an effective method to treat pollutants. The synthesis of artificial oxidase for the degradation of dyes is a hot spot in molecular science. In this study, a nanoscale sandwich-type polyoxometalate (POM) on the basis of a tetra-nuclear cobalt cluster and trivacant B-α-Keggin-type tungstoarsenate {[Co(C8H20N4)]4}{Co4(H2O)2[HAsW9O34]2}∙4H2O (abbreviated as CAW, C8H20N4 = cyclen) has been synthesized and structurally examined by infrared (IR) spectrum, ultraviolet–visible (UV–Vis) spectrum, X-ray photoelectron spectrum (XPS), single-crystal X-ray diffraction (SXRD), and bond valence sum (Σs) calculation. According to the structural analysis, the principal element of the CAW is derived from modifying sandwich-type polyanion {Co4(H2O)2 [HAsW9O34]2}8– with four [Co(Cyclen)]2+, in which 1,4,7,10-tetraazacyclododecane (cyclen) is firstly applied to modify POM. It is also demonstrated that CAW is capable of efficiently catalyzing the production of ROS by the synergistic effects of POM fragments and Co–cyclen complexes. Moreover, CAW can interfere with the morphology and proliferation of sensitive cells by producing ROS and exhibits ability in specifically eliminating methylene blue (MB) dyes from the solution system by both adsorption and catalytic oxidation. [ABSTRACT FROM AUTHOR]

The structural discontinuities in the form of air gaps in transformer cores cause the concentration of electromagnetic force, which is an important source of transformer vibration and noise. In this paper, an engineering model of magnetic flux density and electromagnetic force density on transformer core discontinuities is analytically developed. Based on a reasonable structural simplification and assumptions, magnetic flux density and electromagnetic force density are deduced as explicit functions of the geometric, material, and electrical excitation characteristics of the gap region and the transformer core. The accuracy of the established model is validated by the finite element method (FEM) combined with a magnetic measurement experiment. According to this engineering model, the electromagnetic force density can be reduced by decreasing the gap ratio and increasing the gap thickness to a reasonable level. The outcome of this paper can help to understand the physical mechanism of the electromagnetic force generated by core air gap discontinuities, which is meaningful for noise control and the condition monitoring of transformers. [ABSTRACT FROM AUTHOR]

For design for safety (DFS), automated compliance checking methods have received extensive attention. Although many research efforts have indicated the potential of BIM and ontology for automated compliance checking, an efficient methodology is still required for the interoperability and semantic representation of data from different sources. Therefore, a natural language processing (NLP)-based semantic framework is proposed in this paper, which implements rules-based automated compliance checking for building information modeling (BIM) at the design stage. Semantic-rich information can be extracted from safety regulations by NLP methods, which were analyzed to generate conceptual classes and individuals of ontology and provide a corpus basis for rule classification. The data on BIM was extracted from Revit to a spreadsheet using the Dynamo tool and then mapped to the ontology using the Cellfie tool. The interoperability of different source data was well improved through the isomorphism of information in the framework of semantic integration, causing data processed by the semantic web rule language to be transformed from safety regulations to achieve the purpose that automated compliance checking is implemented in the design documents. The practicability and scientific feasibility of the proposed framework was verified through a 95.21% recall and a 90.63% precision in compliance checking of a case study in China. Compared with traditional compliance checking methods, the proposed framework had high efficiency, response speed, data interoperability, and interaction. [ABSTRACT FROM AUTHOR]

Featured Application: The grille-type steel plate concrete composite wall (GSPCW) is an innovative shear wall system that has recently been developed. This type of shear wall is characterized by large vertical and lateral load capacity while maintaining large deformation capability. Since barely any traditional reinforcing bars are needed, the structural measures for wall construction are simple and can be easily implemented. Based on both experimental and numerical investigations of the GSPCW wall components, the seismic performance of GSPCW walls have been verified to be satisfactory in terms of load-bearing capacity, stiffness and deformation capacity, energy dissipation, etc. Moreover, further analysis on the application of GSPCW walls in a super-high-rise building as a case study show the excellent performance of the system. Based on these findings, it can be inferred that GSPCW wall could be used as an alternative system for conventional steel concrete composite wall, and is expected to be a promising system for high-rise buildings in seismic regions. The grille-type steel plate concrete composite wall (GSPCW) is an innovative shear wall system that mainly consists of steel faceplates, steel tie plates and infilled concrete. Compared to traditional steel plate concrete composite shear walls, the advantages of GSPCW walls include: (1) relatively high lateral and buckling resistance; and (2) simple structural measures for convenient construction and implementation. This paper presents the results of extensive numerical investigations regarding GSPCW systems, examining both GSPCW wall components and their application in a super-high-rise building as a case study. First, typical GSPCW wall models are established using DIANA software, and the numerical models are validated on the basis of comparison with results from previously reported experimental tests. The verified models are further used to perform parametric analyses with the aim of further understanding the effects of various design parameters on the seismic performance of GSPCW systems, including steel ratio, axial load ratio, height-to-width ratio, aspect ratio of the grille steel plate, and concrete compressive strength. Second, a super-high-rise building was selected for application to perform a case study of a GSPCW system. The seismic performance of the tall building in the case study was comparatively evaluated on the basis of both nonlinear time history analysis and modal pushover analysis (MPA), and the results from both of these methods validated the use of GSPCW is an efficient structural wall system appropriate for use in super-high-rise buildings. Finally, a simple economic assessment of the GSPCW building was performed, and the results were compared with those obtained for conventional reinforced concrete wall buildings. [ABSTRACT FROM AUTHOR]

Featured Application: The grouted sleeve lapping connector reported in this work, which is featured by a large sleeve inner diameter and low production cost, can be used to connect the components in precast concrete structures, such as a precast column and shear wall. Compared to grouted splice connectors that have been widely used in constructing precast concrete structures, grouted sleeve lapping connectors have the advantages of a large sleeve interior diameter and low manufacturing cost. In this study, 16 grouted sleeve lapping connectors and three grouted splice connectors were tested under an incremental tensile load. The differences in their tensile capacities and failure modes, especially the mechanical properties of the grouted sleeve lapping connectors, were investigated. It was found that the tensile capacities of the grouted sleeve lapping connectors were up to 2.45 times that of the grouted splice connectors when the sleeve inner surfaces were smooth. All of the grouted sleeve lapping connectors failed by a bar tensile fracture or bar-grout slip, whereas the only failure mode of the grouted splice connectors was grout-sleeve failure. The bond stress distribution around the inserted bar in the grouted sleeve lapping connector was similar to the bond stress distribution around a single bar anchored in concrete. The ultimate hoop compressive strain of the sleeve and the corresponding load increase with greater lap length. In addition, an approximate mechanical model with high reliability was put forward to describe the mechanical properties of the grouted sleeve lapping connector. [ABSTRACT FROM AUTHOR]

Bifidobacterium bifidum strains, an important component of probiotic foods, can form biofilms on abiotic surfaces, leading to increased self-resistance. However, little is known about the molecular mechanism of B. bifidum biofilm formation. A time series transcriptome sequencing and untargeted metabolomics analysis of both B. bifidum biofilm and planktonic cells was performed to identify key genes and metabolites involved in biofilm formation. Two hundred thirty-five nonredundant differentially expressed genes (DEGs) (including vanY, pstS, degP, groS, infC, groL, yajC, tadB and sigA) and 219 nonredundant differentially expressed metabolites (including L-threonine, L-cystine, L-tyrosine, ascorbic acid, niacinamide, butyric acid and sphinganine) were identified. Thirteen pathways were identified during the integration of both transcriptomics and metabolomics data, including ABC transporters; quorum sensing; two-component system; oxidative phosphorylation; cysteine and methionine metabolism; glutathione metabolism; glycine, serine and threonine metabolism; and valine, leucine and isoleucine biosynthesis. The DEGs that relate to the integration pathways included asd, atpB, degP, folC, ilvE, metC, pheA, pstS, pyrE, serB, ulaE, yajC and zwf. The differentially accumulated metabolites included L-cystine, L-serine, L-threonine, L-tyrosine, methylmalonate, monodehydroascorbate, nicotinamide, orthophosphate, spermine and tocopherol. These results indicate that quorum sensing, two-component system and amino acid metabolism are essential during B. bifidum biofilm formation. [ABSTRACT FROM AUTHOR]

Understanding asymptomatic moyamoya disease (aMMD), for which treatment options are currently limited, is key to the development of therapeutic strategies that will slow down the progression of this disease, as well as facilitate the discovery of therapeutic targets for symptomatic MMD. Newly found transfer RNA-derived small RNAs (tsRNAs) perform potential regulatory functions in neovascularization, which is a well-known pathological manifestation of MMD. In this study, the neutrophilic tsRNA transcriptome in aMMD was profiled using next-generation RNA sequencing in five patients and five matched healthy subjects. A negative binominal generalized log-linear regression was used to identify differentially expressed (DE)-tsRNAs in aMMD. Gene Ontology and functional pathway analyses were used to identify biological pathways involved with the targeted genes of the DE-tsRNAs. Four tsRNAs were selected and validated using quantitative reverse transcription polymerase chain reaction. In total, 186 tsRNAs were DE between the two groups. Pathophysiological events, including immune response, angiogenesis, axon guidance, and metabolism adjustment, were enriched for the DE-tsRNAs. The expression levels of the four DE-tsRNAs were consistent with those in the neutrophilic transcriptome. These aberrantly expressed tsRNAs and their targeted pathophysiological processes provide a basis for potential future interventions for aMMD. [ABSTRACT FROM AUTHOR]

Influenza A virus induces severe respiratory tract infection and results in a serious global health problem. Influenza infection disturbs the cross-talk connection between lung and gut. Probiotic treatment can inhibit influenza virus infection; however, the mechanism remains to be explored. The mice received Lactobacillus mucosae 1025, Bifidobacterium breve CCFM1026, and their mixture MIX for 19 days. Effects of probiotics on clinical symptoms, immune responses, and gut microbial alteration were evaluated. L. mucosae 1025 and MIX significantly reduced the loss of body weight, pathological symptoms, and viral loading. B. breve CCFM1026 significantly reduced the proportion of neutrophils and increased lymphocytes, the expressions of TLR7, MyD88, TRAF6, and TNF-α to restore the immune disorders. MIX increased the antiviral protein MxA expression, the relative abundances of Lactobacillus, Mucispirillum, Adlercreutzia, Bifidobacterium, and further regulated SCFA metabolism resulting in an enhancement of butyrate. The correlation analysis revealed that the butyrate was positively related to MxA expression (p < 0.001) but was negatively related to viral loading (p < 0.05). The results implied the possible antiviral mechanisms that MIX decreased viral loading and increased the antiviral protein MxA expression, which was closely associated with the increased butyrate production resulting from gut microbial alteration. [ABSTRACT FROM AUTHOR]

Accumulating evidence supports the role of PDZ-binding kinase (PBK)/T-lymphokine-activated killer-cell-originated protein kinase (TOPK) in mitosis and cell-cycle progression of mitotically active cells, especially proliferative malignant cells. PBK/TOPK was confirmed to be associated with the development, progression, and metastasis of malignancies. Therefore, it is a potential therapeutic target in cancer therapy. Many studies have been conducted to explore the clinical applicability of potent PBK/TOPK inhibitors. However, PBK/TOPK has also been shown to be overexpressed in normal proliferative cells, including sperm and neural precursor cells in the subventricular zone of the adult brain, as well as under pathological conditions, such as ischemic tissues, including the heart, brain, and kidney, and plays important roles in their physiological functions, including proliferation and self-renewal. Thus, more research is warranted to further our understanding of PBK/TOPK inhibitors before we can consider their applicability in clinical practice. In this study, we first review the findings, general features, and signaling mechanisms involved in the regulation of mitosis and cell cycle. We then review the functions of PBK/TOPK in pathological conditions, including tumors and ischemic conditions in the heart, brain, and kidney. Finally, we summarize the advances in potent and selective inhibitors and describe the potential use of PBK/TOPK inhibitors in clinical settings. [ABSTRACT FROM AUTHOR]

Biofilm formation has evolved as an adaptive strategy for bacteria to cope with harsh environmental conditions. Currently, little is known about the molecular mechanisms of biofilm formation in bifidobacteria. A time series transcriptome sequencing analysis of both biofilm and planktonic cells of Bifidobacterium longum FGSZY16M3 was performed to identify candidate genes involved in biofilm formation. Protein–protein interaction network analysis of 1296 differentially expressed genes during biofilm formation yielded 15 clusters of highly interconnected nodes, indicating that genes related to the SOS response (dnaK, groS, guaB, ruvA, recA, radA, recN, recF, pstA, and sufD) associated with the early stage of biofilm formation. Genes involved in extracellular polymeric substances were upregulated (epsH, epsK, efp, frr, pheT, rfbA, rfbJ, rfbP, rpmF, secY and yidC) in the stage of biofilm maturation. To further investigate the genes related to biofilm formation, weighted gene co-expression network analysis (WGCNA) was performed with 2032 transcript genes, leading to the identification of nine WGCNA modules and 133 genes associated with response to stress, regulation of gene expression, quorum sensing, and two-component system. These results indicate that biofilm formation in B. longum is a multifactorial process, involving stress response, structural development, and regulatory processes. [ABSTRACT FROM AUTHOR]

Understanding the motivations that stimulate homebuyers' green purchasing behavior can increase market demand for green products, especially considering the comparably low market share of green products worldwide. In this context, various studies have been conducted examining consumers' intentions to pay for green products. Nevertheless, there is still limited research on evaluating homebuyers' purchasing behavior toward green residential buildings. This study argues that the value of green residential buildings (GRBs) affects their adoption, and thus exerts an invisible force on homebuyers' purchasing behavior. It also finds that field theory provides a scientific perspective on this phenomenon. Thus, this paper proposes a value field model for evaluating homebuyers' GRB purchasing behavior based on physical field theory and psychology field theory. In particular, physical field theory provides the measurement formula, while psychological field theory explains the effect of the force stimulating homebuyers' purchasing intention, and ultimately influencing their purchasing behavior. The initial model consisted of a field source (green perceived value), target charge (GRB demand), distance (psychological distance), and value field factor. As the value field factor was calculated to be approximately equal to 1, the final model is a composite of a field source (green perceived value), target charge (GRB demand), and distance (psychological distance). The results validate the construction of the value field model on the basis of field theory. This research contributes to the body of knowledge by analyzing GRB value and provides a clearer understanding of how GRBs and the environment combine to fulfill homebuyers' requirements and influence their GRB purchasing behavior. [ABSTRACT FROM AUTHOR]

Streptococcus suis is a zoonotic pathogen that causes great economic losses to the swine industry and severe threats to public health. A better understanding of its physiology would contribute to the control of its infections. Although copper is an essential micronutrient for life, it is toxic to cells when present in excessive amounts. Herein, we provide evidence that CopA is required for S. suis resistance to copper toxicity. Quantitative PCR analysis showed that copA expression was specifically induced by copper. Growth curve analyses and spot dilution assays showed that the ΔcopA mutant was defective in media supplemented with elevated concentrations of copper. Spot dilution assays also revealed that CopA protected S. suis against the copper-induced bactericidal effect. Using inductively coupled plasma-optical emission spectroscopy, we demonstrated that the role of CopA in copper resistance was mediated by copper efflux. Collectively, our data indicated that CopA protects S. suis against the copper-induced bactericidal effect via copper efflux. [ABSTRACT FROM AUTHOR]

In this paper, the magnetic flux density distribution on the cross-sections of a transformer core is studied. The core for this study consists of two identical U-shaped cores joint at their open surfaces with known air gaps. The magnetic flux density at one of their joint boundary surfaces was measured for different air gaps. A finite element model (FEM) was built to simulate the magnetic flux density and compared with experiment data. Using the validated FEM, the distributed magnetic flux density on the cross-section of the core structure can be obtained when the air gap approaches zero. An engineering model of the density based on the Ampere's circuit law was also developed and used to explain the relationship between air gap and mean magnetic flux density on the cross-section. The magnetic flux density on the cross-section was found to have a convex-shaped distribution and could be described by an empirical formula. Using this approach, the magnetic flux density distribution in cores with different interlayer insulation was obtained and discussed. This method could also examine the leakage of magnetic flux density in the air gap region when the distance is non-zero, and the relationship between the leakage field and the field in the core structure. The proposed method and model can provide a more detailed understanding for the magnetic field of transformer cores and potential application in designing quiet transformers and condition monitoring. [ABSTRACT FROM AUTHOR]