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Leizhou Peninsula, a main crop producing area in South China, is majorly restricted by drought in terms of economic development because most of the rivers in this region are unbranched and the capacity of engineering regulation and storage is insufficient. In this paper, the standardized precipitation and evapotranspiration index (SPEI) at different time scales was calculated to analyze the variation characteristics of meteorological drought in the Leizhou Peninsula and to explore the influence of precipitation, temperature and teleconnection factors on the drought in the Leizhou Peninsula. The results show that: ①The frequency of annual drought in the Leizhou Peninsula is close to 20%, and the northern part shows a significant trend of wetting, while the southern part shows no significant trend of wetting. The northern part is more extreme drought-prone.②Precipitation and temperature are significantly correlated with SPEI, with a stronger correlation between precipitation and drought.③There is a significant negative correlation between the ocean Nino index (ONI) and the SPEI of the following year, indicating that ENSO is closely related to drought, and there is a difference in the impact on drought when the eastern and central ENSO warm events occur. The research results can provide references for the Leizhou Peninsula Irrigation District project to be implemented soon.

This study investigated the behavior of reinforced concrete columns using high-performance concrete (HPC) filled in prefabricated steel tubes to serve as reinforcement. The experimental setup involved HPC with a compressive strength of 1,515 kg/cm², filled into steel tubes with diameters of ¾, 1, and 1¼ inches, replacing the reinforcement in concrete columns sized 150x150x600 mm. The concrete used for casting the sample columns had a compressive strength of 257 kg/cm². The columns were tested for axial and eccentric loading at displacements of 20, 40, and 60 mm to determine the maximum compressive strength, bending moment, interaction diagrams, and failure patterns of the steel-reinforced concrete columns. The experimental results showed that the axial compressive strength of columns using HPC in steel tubes as reinforcement was higher than that of the control concrete columns. The compressive strength at various eccentricities showed a slight increase compared to the control columns. The comparison between experimental compressive strengths and bending moments with calculated values indicated a consistent trend. Furthermore, the failure patterns of the concrete columns revealed both compression and tension failures.

This paper presents the application of the artificial neural network model (ANN) to predict the expansion of ground bottom ash mortar due to sodium sulfate. Portland cement type I was replaced by ground bottom ash at ratios of 0, 10, 20, 30, 40, 50 and 60 percent by weight of binder. The expansion of mortar which immersed in 5% sodium sulfate at various ages was measured. To show the efficiency of the proposed model, the prediction results of the ANN model are compared with the multiple linear regression (MLR) and the multiple second order polynomial regression (MSPR) models through statistical values. From the prediction results, it was found that the ANN model has a very high expansion prediction accuracy and more effective than the MLR and MSPR. The ANN model has a statistical value of absolute variance higher than 0.99. Therefore, it is concluded that the ANN model has a strong prediction capability of expansion due to sulfate of ground bottom ash mortar.

Objective: This study aimed to investigate the effect of Eurotium Cristatum fermentation broth mixed with tea polyphenols on the immune indexes of cyclophosphamide immunosuppressive mice. Methods: Immunosuppressive model was established by intraperitoneal injection of cyclophosphamide with 80 mg/kg for 3 days. High, middle and low dose E. Cristatum fermentation broth mixed with tea polyphenols was administrated to immunosuppressive mice intragastrically for 15 days. The blood index, spleen index, macrophage phagocytic index, half hemolysis value, delayed-type hypersensitivity, the content of IL-2 and tumor necrosis factor-α (TNF-α) were measured. Results: E. Cristatum fermentation broth mixed with tea polyphenols significantly increased the number of white blood cells, red blood cells, hemoglobin, serum hemolysin and IL-2 on immunosuppressive mice, enhanced the spleen index and monocyte-phagocytic index, and improved the delayed type hypersensitivity on mice. Conclusion: E. Cristatum fermentation broth mixed with tea polyphenols can enhance immunity on mice.

Complementary label learning (CLL) is a type of weakly supervised learning method that utilizes the category of samples that do not belong to a certain class to learn their true category. However, current CLL methods mainly rely on rewriting classification losses without fully leveraging the supervisory information in complementary labels. Therefore, enhancing the supervised information in complementary labels is a promising approach to improve the performance of CLL. In this paper, we propose a novel framework called Complementary Label Enhancement based on Knowledge Distillation (KDCL) to address the lack of attention given to complementary labels. KDCL consists of two deep neural networks: a teacher model and a student model. The teacher model focuses on softening complementary labels to enrich the supervision information in them, while the student model learns from the complementary labels that have been softened by the teacher model. Both the teacher and student models are trained on the dataset that contains only complementary labels. To evaluate the effectiveness of KDCL, we conducted experiments on four datasets, namely MNIST, F-MNIST, K-MNIST and CIFAR-10, using two sets of teacher-student models (Lenet-5+MLP and DenseNet-121+ResNet-18) and three CLL algorithms (PC, FWD and SCL-NL). Our experimental results demonstrate that models optimized by KDCL outperform those trained only with complementary labels in terms of accuracy.

Tissue infection typically results from blood transmission or the direct inoculation of bacteria following trauma. The pathogen-induced destruction of tissue prevents antibiotics from penetrating the infected site, and severe inflammation further impairs the efficacy of conventional treatment. The current study describes the size-dependent induction of macrophage polarization using gold nanoparticles. Gold nanoparticles with a diameter of 50 ​nm (Au50) can induce M2 polarization in macrophages by inhibiting the NF-κB signaling pathway and stimulate an inflammatory response in the environment by inhibiting the MAPK signaling pathway LPS. Furthermore, the induced polarization and anti-inflammatory effects of the Au50 nanoparticles promoted the osteogenic differentiation of BMSCs in vitro. In addition, the overexpression of TREM2 in macrophage induced by Au50 nanoparticles was found to promote macrophage phagocytosis of Staphylococcus aureus, enhance the fusion of autophagosomes and lysosomes, accelerate the intracellular degradation of S. aureus, in addition to achieving an effective local treatment of osteomyelitis and infectious skin defects in conjunction with inflammatory regulation and accelerating bone regeneration. The findings, therefore, demonstrate that Au50 nanoparticles can be utilized as a promising nanomaterial for in vivo treatment of infections.

Purpose: In order to improve the accuracy of liquid level detection in intravenous left auxiliary vein infusion and reduce the pain of patients with blood returning from intravenous infusion, we propose a deep learning based liquid level detection model of infusion levels to facilitate this operation. Method: We implemented a Yolo v3-based detection model of infusion level images in intravenous infusion, and at the same time, compare it with SURF image processing technique, RCNN, and Fast-RCNN methods. Results: The model in this paper is better than the comparison algorithm in Intersection over Union (IoU), precision, recall and test time. The liquid level detection model based on Yolo v3 has a precision of 0.9768, a recall rate of 0.9688, an IoU of 0.8943, and a test time of 2.9 s. Conclusion: The experimental results prove that the liquid level detection method based on deep learning has the characteristics of high accuracy and good real-time performance. This method can play a certain auxiliary role in the hospital environment and improve work efficiency of medical workers.

Crack dynamic propagation and arrest behaviors have received extensive attention over the years. However, there still remain many questions, e.g. under what conditions will a running crack come to arrest? In this paper, drop weight impact (DWI) tests were conducted to investigate crack arrest mechanism using single cleavage triangle (SCT) rock specimens. Green sandstone was selected to prepare the SCT specimens. Dynamic stress intensity factors (DSIFs) were calculated by ABAQUS code, and the critical DSIFs were determined by crack propagation speeds and fracture time measured by crack propagation gauges (CPGs). The test results show that the critical DSIF at propagation decreases with crack propagation speed. Numerical simulation for SCT specimens under different loading waves was performed using AUTODYN code. The reflected compressive wave from the incident and transmitted plates can induce crack arrests during propagation, and the number of arrest times increases with the wave length. In order to eliminate the effect of the incident and transmitted plates, models consisting of only one SCT specimen without incident and transmitted plates were established, and the same trapezoid-shaped loading wave was applied to the SCT specimen. The results show that for the SCT specimen with transmitted boundary (analogous to an infinite plate), the trapezoid-shaped loading wave cannot induce crack arrest anymore. The numerical results can well describe the occurrence of crack arrest in the experiments.

Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) has become one of the most popular methods for the rapid and cost-effective detection of clinical pathogenic microorganisms. This study aimed to evaluate and compare the diagnostic performance of MALDI-TOF MS with that of conventional approaches for the direct identification of pathogens from urine samples. A systematic review was conducted based on a literature search of relevant databases. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and area under the summary receiver operating characteristic (SROC) curve of the combined studies were estimated. Nine studies with a total of 3920 subjects were considered eligible and included in the meta-analysis. The pooled sensitivity was 0.85 (95% CI 0.79-0.90), and the pooled specificity was 0.93 (95% CI 0.82-0.97). The PLR and NLR were 11.51 (95% CI 4.53-29.26) and 0.16 (95% CI 0.11-0.24), respectively. The area under the SROC curve was 0.93 (95% CI 0.91-0.95). Sensitivity analysis showed that the results of this meta-analysis were stable. MALDI-TOF MS could directly identify microorganisms from urine samples with high sensitivity and specificity.

Defects such as voids, pores, and joints will transform into big scale cracks in the rock of tunnel surrounding under dynamic load like blasting and earthquake. In this paper, three kinds of symmetrical cracks were chosen as an example, and experiments and numerical simulations were conducted to study the effect of symmetric cracks on a blast-induced crack. The relationship of main crack propagation characteristic and distribution of symmetrical cracks was investigated. Some circular specimens using two kinds of material, PMMA and sandstone, including a center hole charged with a detonator and pre-existing cracks were used in the experiments. The test system consisted of an oscilloscope and an ultradynamic strain amplifier and crack propagation gauges (CPGs) were employed in monitoring propagation velocity. AUTODYN code was applied in numerical simulation to investigate the propagation behavior of main crack between symmetrical cracks. Linear equation of state and a modified major principal stress failure criterion was utilized to describe the status of rock material. Based on experimental and numerical results, it can be concluded that (1) the pre-existing symmetrical cracks have arrest effect on main crack propagation, (2) compressive stress in y-direction plays very important roles in crack arrest, and (3) the spacing of parallel cracks has a great influence on crack propagation length and velocity.

Under the background of a low carbon economy, this paper examines the impact of carbon tax policy on supply chain network emission reduction. The integer linear programming method is used to establish a supply chain network emission reduction such a model considers the cost of CO2 emissions, and analyses the impact of different carbon price on cost and carbon emissions in supply chains. The results show that the implementation of a carbon tax policy can reduce CO2 emissions in building supply chain, but the increase in carbon price does not produce a reduction effect, and may bring financial burden to the enterprise. This paper presents a reasonable carbon price range and provides decision makers with strategies towards realizing a low carbon building supply chain in an economical manner.

Mixed-mode fracture of construction building materials under impact loading is quite common in civil engineering. The investigation of mixed-mode crack propagation behavior is an essential work for fundamental research and engineering application. A variable angle single cleavage semi-circle (VASCSC) specimen was proposed with which the dynamic fracture test was conducted by using a Split-Hopkinson pressure bar (SHPB). Notably, the mixed-mode crack propagation velocity could be detected by the synchronized crack velocity measuring system. With experimental results, the dynamic initiation stress intensity factors KI and KII were calculated by the experimental-numerical method. Additionally, the crack path of mixed-mode I/II fracture can be predicated precisely by using numerical method. Thus, a comprehensive approach of investigation on mixed-mode I/II fracture under impact loading was illustrated in this paper. The study demonstrates that the mixed-mode I/II crack would transform from complicated mode I/II to pure mode I during crack propagation, and several velocity decelerations induced crack deflection. The dynamic initiation fracture toughness of mixed-mode crack was determined by the experimental-numerical method. The VASCSC specimen has a great potential in investigating mixed-mode fracture problems with the SHPB device.

Metal halide perovskites offer ample opportunities to develop advanced optoelectronic devices. This work showcases that the integration of metal halide perovskites into metal oxide nanoshells with controllable interior cavities can enable water-vapor-responsive dual-mode switching of fluorescence and structural color. Through a ship-in-a-bottle method to introduce a controlled amount of CsPbBr3 into MnO2 nanoshells, we have designed CsPbBr3@MnO2 yolk-shell nanostructures, which can uptake a defined amount of water to exhibit rapid (less than 1 s) and reversible (≥100 cycles) responses in both fluorescence on-off and color change when exposed to dynamic water vapor. These responses originate from the water-triggered phase transformation of CsPbBr3 to CsPb2Br5 and the structural color change of the MnO2 shell. The altered electronic and bonding structure at the oxide-halide interface, rapid water accumulation in the yolk-shell cavity, and protective effect of the oxide shell facilitate the reversible transformations. The response characteristics of the yolk-shell nanostructures have been further demonstrated in fabricating patterned films capable of multiple fluorescence/structural color responses, highlighting their potential for applications in advanced anticounterfeiting and encryption.

For the high-speed, high-maneuverability and stealthy target detection via modern radar in complicated electromagnetic environment, a novel radar signal processing approach called Space-Time-Frequency Focus-Before-Detection (STF-FBD) via multi-dimensional coherent integration is proposed. Based on space-timefrequency signal modeling for modern radar systems, the proposed method can effectively suppress the strong interference, such as clutter and active jamming, and overcome the problems of scaled effect of high-speed targets, aperture fill time, sparse frequency sub-band synthesis, across range units, across Doppler units and across beam units. The proposed methods improves radar signal processing performance on the steps like energy integration, target detection, parameter estimation, maneuver tracking, feature extraction and target recognition. It also outperforms the existing Track-Before-Detection (TBD) methods and establish a unified STF-FBD and STF-FBD-TBD radar signal processing frame work. The proposed method is suitable for high-speed, high-maneuverability and stealthy target, as well as for conventional targets. It is applicable for new-generation modern radar, as well as for conventional radars, and may find application to different field.

The objective of this paper is to investigate the complete process of dynamic crack propagation in brittle materials under different loading rates. By using Improved Single Cleavage Semi-Circle (ISCSC) specimens and Split Hopkinson Pressure Bar equipment, experiments were conducted, with the fracture phenomenon and crack propagation of tight sandstone investigated. Meanwhile, the process of crack propagation behaviour was simulated. Moreover, with the experimental−numerical method, the crack propagation dynamic stress intensity factor (DSIF) was also calculated. Then, the crack propagation toughness of tight sandstone under different loading rates was investigated and illustrated elaborately. Investigation results demonstrate that ISCSC specimens can achieve the crack arrest position unchanged, and the numerical simulation could effectively deduce the actual crack propagation, as their results were well matched. During crack propagation, the crack propagation DSIF in the whole process increases with the rising loading rate, and so does the crack propagation velocity. Several significant dynamic material parameters of tight sandstone are also given, for engineering reference.