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Objective To investigate the clinical application value of blood heparin-binding protein (HBP), procalcitonin (PCT), and C-reactive protein(CRP) in the early diagnosis of childhood sepsis. Methods A retrospective analysis was performed for 20 children with general sepsis (general sepsis group), 16 children with severe sepsis (severe sepsis group), and 12 children with septic shock (septic shock group) who were admitted to the pediatric intensive care unit and the neonatal intensive care unit of our hospital from November 2017 to May 2019, and 22 non-sepsis children with local infection (local infection control group) and 18 children with non-infectious disease (non-infection control group) who were admitted to the general ward during the same period of time were enrolled as control group. The levels of blood HBP, PCT, and CRP were measured and compared between groups, and the receiver operating characteristic (ROC) curve was used to investigate the value of each index in the early diagnosis of sepsis. Results The septic shock group had significantly higher levels of blood HBP and PCT than the severe sepsis group and the general sepsis group (P0.05), but all these three groups had a significantly higher level of blood CRP than the non-infection control group (P

The effect of 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47), a persistent environmental pollutant commonly used as a flame retardant in various consumer products, on pancreatitis has not been clearly elucidated, although it has been reported to be toxic to the liver, nervous system, and reproductive system. Acute pancreatitis (AP) and chronic pancreatitis (CP) models were induced in this study by intraperitoneal injection of caerulein. The aim was to investigate the impact of BDE-47 on pancreatitis by exposing the animals to acute (1 week) or chronic (8 weeks) doses of BDE-47 (30 mg/kg in the low-concentration group and 100 mg/kg in the high-concentration group). Additionally, BDE-47 was utilized to stimulate mouse bone marrow-derived macrophages, pancreatic primary stellate cells, and acinar cells in order to investigate the impact of BDE-47 on pancreatitis. In vivo experiments conducted on mice revealed that chronic exposure to BDE-47, rather than acute exposure, exacerbated the histopathological damage of AP and CP, leading to elevated fibrosis in pancreatic tissue and increased infiltration of inflammatory cells in the pancreas. In vitro experiments showed that BDE-47 can promote the expression of the inflammatory cytokines Tnf-α and Il-6 in M1 macrophages, as well as promote acinar cell apoptosis through the activation of the PERK and JNK pathways via endoplasmic reticulum stress. The findings of this study imply chronic exposure to BDE-47 may exacerbate the progression of both AP and CP by inducing acinar cell apoptosis and dysregulating inflammatory responses. [ABSTRACT FROM AUTHOR]

Distribution of landslide is controlled by various causative factors that have different impacts on the occurrence of landslide in different regions. Using one single model to build the hazard assessment is not enough to fully reflect the spatial differences of landslide controlling factors especially for large area. Landslide hazard assessment based on zonation was therefore proposed in this study with an attempt to take effective measures to address this problem. The China–Pakistan Economic Corridor was taken as the study area where landslide hazard assessment was carried out. Based on the features of geological structure, topography, and climate, the study area was divided into three zones. The controlling factors were further analyzed by the geographical detectors method. It was found that the main controlling factors for landslides in these three zones were related to the site’s topography (altitude, slope gradient, and relief amplitude), land use, and distance to an earthquake epicenter. Furthermore, different factors for landslide hazard assessment were selected based on the result of a controlling factor analysis. An artificial neural network model was employed to build the hazard assessment models, and hazard assessment maps were generated. Validations were conducted, showing that the accuracy of hazard assessment maps by zones was higher than that by the whole study area, despite there was no significant difference during the modeling process.

Microbially induced calcium carbonate precipitation (MICP) is an environmentally friendly technology that improves soil permeability resistance through biocementation. In this study, 2D microscopic analysis and 3D volume reconstruction were performed on river sand after 24 cycles of bio-treatment based on stacked images and computed tomography (CT) scanning data, respectively, to extract biocementation patterns between particles. Based on the mutual validation findings of the two techniques, three patterns in the biocemented sand were identified as G-C-G, G-C, and G-G. Specifically, 2D microscopic analysis showed that G-C-G featured multi-particle encapsulation and bridging, with a pore filling ratio of 81.2%; G-C was characterized by locally coated particle layers, with a pore filling ratio of 19.7%; and the G-G was marked by sporadic filling of interparticle pores, with a pore filling ratio of 11.7%. G-C-G had the best cementation effect and permeability resistance (effective sealing rate of 68.5%), whereas G-C (effective sealing rate of 2.4%) had a relatively minor contribution to pore-filling and flow sealing. 3D volume reconstruction showed that G-C-G had the highest pore filling rate, followed by G-G and G-C. The average filling ratios of area and volume for G-C-G were 83.979% and 77.257%, respectively; for G-G 20.360% and 23.600%; and for G-C 11.545% and 11.250%. The analysis of the representative element volume (REV) was conducted, and the feasibility and reliability of the micro-scale pattern extraction results were confirmed to guide the analysis of macro-scale characteristics. The exploration of the effectiveness of cementation patterns in fluid sealing provides valuable insights into effective biocementation at the pore scale of porous media, which may inspire future research. [ABSTRACT FROM AUTHOR]

There is information redundancy in both spatial and spectral aspects of hyperspectral images. Considering a fixed proportion in sequential forward method may not find the optimal bands, we modify a band selection (BS) method by introducing a parameter to adjust the proportion of standard deviation to correlation, which may select key bands quickly and accurately. In addition, slant Haar type orthogonal transforms (SHTOT) have slant base vectors suitable to express the image brightness with gradual change. However, SHTOT have attracted little attention of scholars'. This paper introduces SHTOT with fast algorithm and varied parameters to the further compression of band images from a space point of view. Comparative experiments were performed with other BS strategies and state-of-the-art orthogonal transforms, such as DCT, DWT, Walsh, slant transform, Haar type orthogonal transforms. Final experimental results achieved on the commonly used data sets validate that the proposed approach has a faster speed, high compression ratio and good image quality. Additionally, it is more appropriate to choose different SHTOT for the specific application. The sparse SHTOT generated by certain parameter values are more suitable for the high requirement in image quality, but the compression ratio isn't very high, while dense SHTOT produced by another parameter values are fitter for the opposite cases. [ABSTRACT FROM AUTHOR]

As severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) variants continue to wreak havoc worldwide, the "Cytokine Storm" (CS, also known as the inflammatory storm) or Cytokine Release Syndrome has reemerged in the public consciousness. CS is a significant contributor to the deterioration of infected individuals. Therefore, CS control is of great significance for the treatment of critically ill patients and the reduction of mortality rates. With the occurrence of variants, concerns regarding the efficacy of vaccines and antiviral drugs with a broad spectrum have grown. We should make an effort to modernize treatment strategies to address the challenges posed by mutations. Thus, in addition to the requirement for additional clinical data to monitor the long‐term effects of vaccines and broad‐spectrum antiviral drugs, we can use CS as an entry point and therapeutic target to alleviate the severity of the disease in patients. To effectively combat the mutation, new technologies for neutralizing or controlling CS must be developed. In recent years, nanotechnology has been widely applied in the biomedical field, opening up a plethora of opportunities for CS. Here, we put forward the view of cytokine storm as a therapeutic target can be used to treat critically ill patients by expounding the relationship between coronavirus disease 2019 (COVID‐19) and CS and the mechanisms associated with CS. We pay special attention to the representative strategies of nanomaterials in current neutral and CS research, as well as their potential chemical design and principles. We hope that the nanostrategies described in this review provide attractive treatment options for severe and critical COVID‐19 caused by CS. [ABSTRACT FROM AUTHOR]

Three-leaf stone masonry constitutes a widespread construction typology in historical buildings, but limited reports can be found on its mechanical behaviors. This study intended to understand better the compressive behaviors of traditional Tibetan three-leaf walls (TTTLWs) constructed from stones and mud mortar by a series of laboratory experiments on the constituent materials as well as the masonry prisms and walls. The physical properties of the TTTLWs, e.g. the elastic modulus, crack strength, compressive strength, and damage evolution were investigated. A three-dimensional numerical micro model, validated by the experimental results, was proposed to discuss the compressive behavior of the walls. TTTLWs may be concluded to have medium compressive strength, low elastic modulus compared with other types of three-leaf walls. Large separation between the leaves was observed during the test, and the consequent second-order effect caused the reduction of the compressive performance. The key stones provided a transversal connection between wall leaves, resulting in a limited positive influence on the compressive strength of walls. [ABSTRACT FROM AUTHOR]

The use of solar energy has shown the fastest global growth of all renewable energy sources. Efforts towards careful evaluation are required to select optimal locations for the installation of photovoltaics (PV) because their effectiveness is strongly reliant on exposure to solar irradiation. Assessing the shadows cast by nearby buildings and vegetation is essential, especially at the city scale. Due to urban complexity, conventional methods using Digital Surface Models (DSM) overestimate solar irradiation in dense urban environments. To provide further insights into this dilemma, a new modeling technique was developed for integrated 3D city modeling and solar potential assessment on building roofs using light detection and ranging (LiDAR) data. The methodology used hotspot analysis to validate the workflow in both site and without-site contexts (e.g., trees that shield small buildings). Field testing was conducted, covering a total area of 4975 square miles and 10,489 existing buildings. The results demonstrate a considerable impact of large, dense trees on the solar irradiation received by smaller buildings. Considering the site's context, a mean annual solar estimate of 99.97 kWh/m2/year was determined. Without considering the site context, this value increased by 9.3% (as a percentage of total rooftops) to 109.17 kWh/m2/year, with a peak in July and troughs in December and January. The study suggests that both factors have a substantial impact on solar potential estimations, emphasizing the importance of carefully considering the shadowing effect during PV panel installation. The research findings reveal that 1517 buildings in the downtown area of Austin have high estimated radiation ranging from 4.7 to 6.9 kWh/m2/day, providing valuable insights for the identification of optimal locations highly suitable for PV installation. Additionally, this methodology can be generalized to other cities, addressing the broader demand for renewable energy solutions. [ABSTRACT FROM AUTHOR]