Abstract With the in-depth development of the market economy and the acceleration of the process of urbanization, a large number of people have poured into the city, and a large number of residential ...communities have been developed and constructed. Design quality in the development process is often replaced by output. Some companies attach importance to quality but do not know how to control quality. Based on this, this paper uses the method of multi-sensor information fusion to study the planning and layout design methods of residential areas, and provides a design basis for solving the problems of people’s living environment deterioration and increasingly scarce land resources. Based on the Rhinoceros and Grasshopper parametric platform, this paper integrates residential information model, performance prediction technology, and multi-sensor information fusion technology, taking residential planning and layout parameters as design variables. A set of intelligent optimization system for residential planning and layout based on multi-performance objective simulation was compiled. The “internal factors” and “external factors” that affect the results of RLIOS are studied, and then the residential planning and layout design methods are studied. Experiments have proved that no matter what algorithm is used, the performance of each target can be improved, the floor area ratio performance can be improved by 35.3–3.3%, and the open space performance can be improved by 12.6–31.36%. It shows that the residential planning and layout design method based on multi-sensor information fusion proposed in this paper improves the accuracy and efficiency of the work.
The addition of hollow glass microsphere into composites is a method to improve mechanical properties. However, the interfacial debonding of hollow microsphere inevitably causes a decrease in the ...mechanical properties of the material, which ultimately leads to the failure of the composites. In the numerical simulation of such hollow particle-reinforced composites, the ordinary displacement finite element requires a large number of meshes, which undoubtedly greatly increases the computational cost. In this paper, a new VCFEM is proposed to solve this problem by establishing a two-dimensional Voronoi cell finite element model, deriving the residual energy generalized function of hollow particle-reinforced composites, and calculating the interface debonding. The simulation results are compared with the commercial software MARC, ABAQUS to verify the effectiveness of this VCFEM. The results show that this VCFEM greatly improves the computational efficiency while ensuring the accuracy. Based on this model, this paper also investigates the effect of the generation of interfacial debonding on the overall structure and the effect of different wall thickness of hollow particles on the damage of element debonding.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Smart drug delivery systems (SDDSs) for cancer treatment are of considerable interest in the field of theranostics. However, developing SDDSs with early diagnostic capability, enhanced drug delivery ...and efficient biodegradability still remains a scientific challenge. Herein, we report near-infrared light and tumor microenvironment (TME), dual responsive as well as size-switchable nanocapsules. These nanocapsules are made of a PLGA-polymer matrix coated with Fe/FeO core-shell nanocrystals and co-loaded with chemotherapy drug and photothermal agent. Smartly engineered nanocapsules can not only shrink and decompose into small-sized nanodrugs upon drug release but also can regulate the TME to overproduce reactive oxygen species for enhanced synergistic therapy in tumors. In vivo experiments demonstrate that these nanocapsules can target to tumor sites through fluorescence/magnetic resonance imaging and offer remarkable therapeutic results. Our synthetic strategy provides a platform for next generation smart nanocapsules with enhanced permeability and retention effect, multimodal anticancer theranostics, and biodegradability.
COVID-19, caused by SARS-CoV-2, presents distinct diagnostic challenges due to its wide range of clinical manifestations and the overlapping symptoms with other common respiratory diseases. This ...study focuses on addressing these difficulties by employing machine learning (ML) methodologies, particularly the XGBoost algorithm, to utilize Complete Blood Count (CBC) parameters for predictive analysis.
We performed a retrospective study involving 2114 COVID-19 patients treated between December 2022 and January 2023 at our healthcare facility. These patients were classified into fever (1057 patients) and pneumonia groups (1057 patients), based on their clinical symptoms. The CBC data were utilized to create predictive models, with model performance evaluated through metrics like Area Under the Receiver Operating Characteristics Curve (AUC), accuracy, sensitivity, specificity, and precision. We selected the top 10 predictive variables based on their significance in disease prediction. The data were then split into a training set (70% of patients) and a validation set (30% of patients) for model validation.
We identified 31 indicators with significant disparities. The XGBoost model outperformed others, with an AUC of 0.920 and high precision, sensitivity, specificity, and accuracy. The top 10 features (Age, Monocyte%, Mean Platelet Volume, Lymphocyte%, SIRI, Eosinophil count, Platelet count, Hemoglobin, Platelet Distribution Width, and Neutrophil count.) were crucial in constructing a more precise predictive model. The model demonstrated strong performance on both training (AUC = 0.977) and validation (AUC = 0.912) datasets, validated by decision curve analysis and calibration curve.
ML models that incorporate CBC parameters offer an innovative and effective tool for data analysis in COVID-19. They potentially enhance diagnostic accuracy and the efficacy of therapeutic interventions, ultimately contributing to a reduction in the mortality rate of this infectious disease.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This paper proposes a stochastic model to simulate the occurrence and levels of polychlorinated biphenyls (PCBs) in juvenile tuna. This model can calculate the transport of PCBs in the ocean ...(macroscopic phenomena) and biomagnification in fish (microscopic phenomena). The uncertainty in the concentration of the PCBs encountered by fish was treated by adopting a random sampling from the probability distribution function using Metropolis–Hastings algorithm. The model was applied to one-dimensional cases with transported PCBs and swimming fish. The simulated PCBs levels in the fish agreed well with levels observed by previous studies. Influences of PCBs spatial distribution patterns and current velocity on the PCBs levels in fish body was examined. The results showed that the model was sensitive to the distribution pattern and moderately sensitive to the current velocity. The model has the potential to be extended to more realistic situations and to serve as a tool for environmental risk assessment.
•This model can stochastically compute PCBs concentrations encountered by fish.•This models theoretically treated uncertainty in PCBs concentrations in seawater.•Dynamics of food chain and bioaccumulation was stochastically described.•The numerical calculations proved the adequate performance of this model.•Bioaccumulation of PCBs in fish was realistically simulated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Imaging-guided photothermal therapy (PTT) by combination of imaging and PTT has been emerging as a promising therapeutic method for precision therapy. However, the development of multicomponent ...nanoplatforms with stable structures for both PTT and multiple-model imaging remains a great challenge. Herein, we synthesized monodisperse Au–Fe2C Janus nanoparticles (JNPs) of 12 nm, which are multifunctional entities for cancer theranostics. Due to the broad absorption in the near-infrared range, Au–Fe2C JNPs showed a significant photothermal effect with a 30.2% calculated photothermal transduction efficiency under 808 nm laser irradiation in vitro. Owing to their excellent optical and magnetic properties, Au–Fe2C JNPs were demonstrated to be advantageous agents for triple-modal magnetic resonance imaging (MRI)/multispectral photoacoustic tomography (MSOT)/computed tomography (CT) both in vitro and in vivo. We found that Au–Fe2C JNPs conjugated with the affibody (Au–Fe2C–ZHER2:342) have more accumulation and deeper penetration in tumor sites than nontargeting JNPs (Au–Fe2C–PEG) in vivo. Meanwhile, our results verified that Au–Fe2C–ZHER2:342 JNPs can selectively target tumor cells with low cytotoxicity and ablate tumor tissues effectively in a mouse model. In summary, monodisperse Au–Fe2C JNPs, used as a multifunctional nanoplatform, allow the combination of multiple-model imaging techniques and high therapeutic efficacy and have great potential for precision theranostic nanomedicines.
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IJS, KILJ, NUK, PNG, UL, UM
Ground clutter data are usually generated using a statistical model, but they cannot effectively reflect the spatial distribution characteristics of ground objects. It is important in practical ...projects to effectively predict ground clutter when terrain data are known. In this paper, a scheme of ground clutter simulation based on the three-dimensional parabolic equation (3DPE) model is proposed. Radio wave propagation was modeled by the PE model and the spatial field distribution was solved. After the radar cross section (RCS) calculation based on space cells, the ground clutter information data were obtained. Then the radar echo was obtained and the clutter map was simulated. The simulation experimental results show that the ground clutter map simulated by the proposed method has a good reference value, meets the demand of strong clutter area prediction under known terrain conditions, and provides a theoretical basis for radar location and optimal deployment.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Paraquat is one of the most widely used herbicides in the world and is highly toxic to humans and animals. In this study, we developed a serum metabolomic method based on GC/MS to evaluate the ...effects of acute paraquat poisoning on rats. Pattern recognition analysis, including both principal component analysis and partial least squares-discriminate analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the level of octadecanoic acid, L-serine, L-threonine, L-valine, and glycerol in the acute paraquat poisoning group (36 mg/kg) increased, while the levels of hexadecanoic acid, D-galactose, and decanoic acid decreased. These findings provide an overview of systematic responses to paraquat exposure and metabolomic insight into the toxicological mechanism of paraquat. Our results indicate that metabolomic methods based on GC/MS may be useful to elucidate the mechanism of acute paraquat poisoning through the exploration of biomarkers.
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