Exploring the core knowledge of business intelligence

With the rapid development of data analysis, there is few research on the core knowledge of business intelligence system (BIS). In order to fill this research gap, this paper collected the 1003 articles and 31345 references from the Web of Science database, and then applied co-citation analysis and factor analysis, to analyze their core knowledge. We identified 52 highly cited articles and obtained 9 core knowledge categories in the field of BI: BI success, IT acceptance and measurement, big data analysis,dataanalysis anddecision making,business strategy, BIS,consumer behavior, knowledge management, business adoption. Research shows that BISs are still in the growing trend and core knowledge helps researchers and managers better understand the core concepts and relevance of BI, so as to quickly discover possible research directionsinthisresearchfieldandusefulapplicationsintheenterprise

Rice false smut pathogen: implications for mycotoxin contamination, current status, and future perspectives

Rice serves as a staple food across various continents worldwide. The rice plant faces significant threats from a range of fungal, bacterial, and viral pathogens. Among these, rice false smut disease (RFS) caused by Villosiclava virens is one of the devastating diseases in rice fields. This disease is widespread in major rice-growing regions such as China, Pakistan, Bangladesh, India, and others, leading to significant losses in rice plantations. Various toxins are produced during the infection of this disease in rice plants, impacting the fertilization process as well. This review paper lightens the disease cycle, plant immunity, and infection process during RFS. Mycotoxin production in RFS affects rice plants in multiple ways, although the exact phenomena are still unknown

Optimal Evacuation Route Planning of Urban Personnel at Different Risk Levels of Flood Disasters Based on the Improved 3D Dijkstra’s Algorithm

In the event of a flood, the choice of evacuation routes is vital for personnel security. This is particularly true when road factors play an important role in evacuation time. In this study, the traditional Dijkstra algorithm for route planning is improved, and the evacuation model is improved from 2D to 3D. At the same time, the Lasso regression method is adopted to take the road factors into account in the pedestrian speed, and the location of shelter is selected and optimized through the calculation results, and then based on the improved 3D Dijkstra’s algorithm, an optimal evacuation route method in different flood disasters risk levels is proposed, which can make pedestrians reach the shelters within the shortest time. After taking into account road factors (road width, slope, non-motorized lane width, and pedestrian density), through the calculation of the pedestrian speed formula, the estimated evacuation time of pedestrians is obtained. By combining available shelters with evacuation routes, the optimized algorithm improves the evacuation efficiency facing different risk levels of flood disasters. The results show that when residents are confronted with flood disasters of once-in-20-year, once-in-50-year, and once-in-100-year, the proposed optimization algorithm can save 7.59%, 11.78%, and 17.78% of the evacuation time. Finally, according to the verification of the actual effect in Meishan Town, the proposed method of optimal evacuation route planning can effectively reduce the evacuation time of pedestrians, evaluate, and optimize the location of existing shelter, and provide suggestions for urban road reconstruction

A Tailings Dam Long-Term Deformation Prediction Method Based on Empirical Mode Decomposition and LSTM Model Combined with Attention Mechanism

Tailings dams are constructed as storage dams for ore waste, serving as industrial waste piles and for drainage. The dam is negatively affected by rainfall, infiltration lines and its own gravity, which can cause its instability to gradually increase, leading to dam deformation. To predict the irregular changes of tailings dam deformation, empirical mode decomposition (EMD) is applied to the deformation data to obtain the trend and periodic components. The attention mechanism is used to assign different weights to the input variables to overcome the limitation that the long short-term memory (LSTM) model can only generate fixed-length vectors. The lagged autocorrelation coefficient is applied to each decomposed subregion to solve the lagging effect of external factors on dam deformation. Finally, the model is used to predict deformation in multiple directions to test the generalization ability. The proposed method can effectively mitigate the problems of gradient disappearance and gradient explosion. The applied results show that, compared with the control model EMD-LSTM, the evaluation indexes RMSE and MAE improve 23.66% and 27.90%, respectively. The method also has a high prediction accuracy in the remaining directions of the tailings dam, which has a wide practical application effect and provides a new idea for tailings dam deformation mechanism research

A nanoenzyme-modified hydrogel targets macrophage reprogramming-angiogenesis crosstalk to boost diabetic wound repair

Diabetic wounds has a gradually increasing incidence and morbidity. Excessive inflammation due to immune imbalance leads to delayed wound healing. Here, we reveal the interconnection between activation of the NLRP3 inflammatory pathway in endotheliocyte and polarization of macrophages via the cGAS-STING pathway in the oxidative microenvironment. To enhance the immune-regulation based on repairing mitochondrial oxidative damage, a zeolitic imidazolate framework-8 coated with cerium dioxide that carries Rhoassociated protein kinase inhibition Y-27632 (CeO2–Y@ZIF-8) is developed. It is encapsulated in a photocross-linkable hydrogel (GelMA) with cationic quaternary ammonium salt groups modified to endow the antibacterial properties (CeO2–Y@ZIF-8@Gel). CeO2 with superoxide dismutase and catalase activities can remove excess reactive oxygen species to limit mitochondrial damage and Y-27632 can repair damaged mitochondrial DNA, thus improving the proliferation of endotheliocyte. After endotheliocyte uptakes CeO2–Y@ZIF-8 NPs to degrade peroxides into water and oxygen in cells and mitochondria, NLRP3 inflammatory pathway is inhibited and the leakage of oxidatively damaged mitochondrial DNA (Ox-mtDNA, a damage-associated molecular pattern) through mPTP decreases. Futhermore, as the cGAS-STING pathway activated by Ox-mtDNA down-regulated, the M2 phenotype polarization and anti-inflammatory factors increase. Collectively, CeO2–Y@ZIF-8@Gel, through remodulating the crosstalk between macrophage reprogramming and angiogenesis to alleviate inflammation in the microenvironment and accelerates wound healing