In this paper, a novel foam-filled ellipse tube (FET) is proposed and compared with other hollow and foam-filled tubes with different cross-sections under multiple loading angles, which include ...square, circle and rectangle. First, finite element analyses of these tubes reveal that the FET tube has the best crashworthiness under multiple loading angles. Second, design of experiments (DOE) was used to analyze the parameters that radial rate f, thickness of wall t and foam density ρf. Third, the Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to optimize the FET tube, in which the optimal parameter variation is sought for maximizing specific energy absorption (SEA) and minimizing peak crush force (PCF) under multiple loading angles. The optimized FET tube exhibits better crashworthiness than the origin FET tube and other tubes with different cross-section, indicating that the FET tube can be a potential energy absorber especially under oblique impact loading.
•We proposed a novel foam-filled ellipse (FET) tube.•The crashworthiness of the foam-filled ellipse tube under oblique impact loading was considered.•The design of experiments (DOE) method provided the means to select the sampling points.•Non-dominated Sorting Genetic Algorithm (NSGA-II) was used to optimize the FET tube.
This paper describes the mechanical properties of the three-dimensional(3D) double-V honeycomb intersected by a two-dimensional double-V structure with negative Poisson's ratio. Considering the ...effect of the adjacent unit cells, the Poisson's ratio and Young's modulus of the honeycomb under axial loading are derived theoretically. The finite element (FE)model of the 3D double-V honeycomb (DVH) is conducted to verify the theoretical solutions. It is found that the constraint of the adjacent cells does not affect the negative Poisson's ratio but enhance Young's modulus a lot, and the two properties are determined by the stuffer/tensor angles. Then, the prototypes of the 3D DVH is manufactured to carry out the quasi-static experiments. The stiffness and the collapse stress of the theoretical, numerical and experimental solutions are compared, and it is evident that these results agree very well which indicates the analyses of these solutions are convinced. And the quasi-static collapse stress increases with the increment of tensor angle θ1and the reduction of stuffer angle θ2.
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•The new theoretical model considering boundary effect can accurately predict the mechanical properties of double-V honeycomb.•When stuffer angle is fixed, there exists a minimum value of Young’s modulus when the tensor angle is around 35°.•The static collapse stress rises with an increment of stuffer and tensor angles.
Quantum Hamiltonian identification (QHI) is important for characterizing the dynamics of quantum systems, calibrating quantum devices, and achieving precise quantum control. In this paper, an ...effective two-step optimization (TSO) QHI algorithm is developed within the framework of quantum process tomography. In the identification method, different probe states are input into quantum systems and the output states are estimated using the quantum state tomography protocol via linear regression estimation. The time-independent system Hamiltonian is reconstructed based on the experimental data for the output states. The Hamiltonian identification method has computational complexity O(d 6 ), where d is the dimension of the system Hamiltonian. An error upper bound O( d 3 /√N ) is also established, where N is the resource number for the tomography of each output state, and several numerical examples demonstrate the effectiveness of the proposed TSO Hamiltonian identification method.
► Heavy metals were found coexisting with antibiotics in manures and manure-amended agricultural soils. ► The relative abundance of sulfonamide and tetracycline ARGs were high in manures and soils. ► ...Positive but weak correlations were found between ARGs and their corresponding antibiotics. ► Significant positive correlations were found between some ARGs and typical heavy metals such as Cu, Zn, and Hg. ► Metals able to induce the SOS response may accelerate the dissemination of antibiotic resistance.
Eight antibiotic resistance genes (ARGs), 7 heavy metals, and 6 antibiotics were quantified in manures and soils collected from multiple feedlots in Shanghai. The samples were analyzed to determine if ARG abundances were associated with heavy metal concentration and independent of antibiotics. The results revealed the presence of chloramphenicol, sulfonamides and tetracyclines at concentration ranges of 3.27–17.85, 5.85–33.37 and 4.54–24.66mgkg−1, respectively. Typical heavy metals, such as Cu, Zn, and As, were detected at concentration ranges of 32.3–730.1, 75.9–4333.8, and 2.6–617.2mgkg−1. All ARGs tested were detected in the collected samples except tetB(P), which was absent in animal manures. Overall, sulfonamide ARGs were more abundant than tetracycline ARGs. Except for sulII, only a weak positive correlation was found between ARGs and their corresponding antibiotics. On the contrary, significant positive correlations (p<0.05) were found between some ARGs and typical heavy metals. For example, sulA and sulIII were strongly correlated with levels of Cu, Zn and Hg. The data demonstrated that the presence of ARGs was relatively independent of their respective antibiotic inducer. In addition to antibiotics, toxic heavy metals, such as Hg, Cu, and Zn, exerted a strong selection pressure and acted as complementary factors for ARG abundance.
This study aimed to determine the effect of circulating fluidised bed bottom ash (CFB-BA) content on the mechanical properties and drying shrinkage of cement-stabilised soil. Experiments were ...performed to study the changes in unconfined compressive strength and expansibility of cement-stabilised soil with different CFB-BA contents and the underlying mechanisms based on microscopic properties. The results show that CFB-BA can effectively increase the unconfined compressive strength of the specimen and reduce the amount of cement in the soil. When the combined content of CFB-BA and cement in the soil was 30%, the unconfined compressive strength of the specimen with C/CFB = 2 after 60 days of curing was 10.138 MPa, which is 1.4 times that of the pure cement specimen. However, the CFB-BA does not significantly improve the strength of the soil and cannot be added alone as a cementing material to the soil. Additionally, swelling tests showed that the addition of CFB-BA to cement-stabilised soil can significantly reduce the drying shrinkage. This research project provides reference values for the application of CFB-BA in cement-soil mixing piles, including compressive strength and the reduction in the shrinkage deformation of specimens.
•Negative Poisson's ratio jounce bumper (NPRJB) was assembled into suspension and vehicle models in Adams/Car.•NPRJB achieved better suspension stiffness curve without adjusting free travel.•NPRJB ...had considerable positive influences on the vehicle ride comfort travelling through bump.
Comparing with traditional honeycomb structures, Negative Poisson's Ratio (NPR) structures had better mechanical performances in some certain respects, especially the shear modulus and fracture toughness. However, few publications focused on the cylinder-shape NPR structure, which influence the diversity and possibility of NPR structure applications. In this paper, a cylindrical NPR structure was introduced and applied as a suspension jounce bumper in order to solve the issue that the ideal uniaxial compression load-displacement curve sometimes cannot be realized by traditional Polyurethane (PU) jounce bumper. The load-displacement curve of NPR jounce bumper was proved to be smoother and more ideal than that of traditional jounce bumper. Nevertheless, the influences of NPR jounce bumper on the suspension mechanical performance and vehicle ride comfort were not comprehended yet. In this study, the traditional and NPR jounce bumpers were both assembled into virtual prototypes of Macpherson, double wishbone and multi-link suspensions to conduct single wheel travel virtual tests. The results indicated that NPR jounce bumper can achieve more ideal wheel force vs. jounce height curve without adjusting free travel, which is beneficial to spare precise suspension space. Furthermore, a jounce bumper evaluation method using pulse ride comfort was proposed in this paper. The virtual ride comfort tests of travelling through bump and pothole were conducted using established vehicle virtual prototype. The maximum vertical accelerations and weighted root mean square (RMS) of acceleration of vehicle centroid at most speeds were reduced applying NPR jounce bumper. Thus, the NPR jounce bumper can apparently improve vehicle ride comfort.
Full quantum state tomography (FQST) plays a unique role in the estimation of the state of a quantum system without a priori knowledge or assumptions. Unfortunately, since FQST requires ...informationally (over)complete measurements, both the number of measurement bases and the computational complexity of data processing suffer an exponential growth with the size of the quantum system. A 14-qubit entangled state has already been experimentally prepared in an ion trap, and the data processing capability for FQST of a 14-qubit state seems to be far away from practical applications. In this paper, the computational capability of FQST is pushed forward to reconstruct a 14-qubit state with a run time of only 3.35 hours using the linear regression estimation (LRE) algorithm, even when informationally overcomplete Pauli measurements are employed. The computational complexity of the LRE algorithm is first reduced from ∼1019 to ∼1015 for a 14-qubit state, by dropping all the zero elements, and its computational efficiency is further sped up by fully exploiting the parallelism of the LRE algorithm with parallel Graphic Processing Unit (GPU) programming. Our result demonstrates the effectiveness of using parallel computation to speed up the postprocessing for FQST, and can play an important role in quantum information technologies with large quantum systems.
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•Micro-macro sound absorption correlations for various microstructures have been established using the JCAPL model.•Smaller porosity for better noise reduction at low frequencies, and ...the opposite at high frequencies.•As the different distributions of sound resistance and reactance, the porosity of 76.4%–82.0% has the best performance.•High porosity materials are more sensitive to changes in sound absorption properties caused by changes in prism length.
With the increasing prominence and complexity of environmental noise problems, there is an urgent need for novel acoustic materials to meet noise reduction requirements. In this paper, two auxetic microstructures and three typical lattice microstructures are established, and a microscopic-macroscopic acoustic performance study scheme is established through the Johnson-Champoux-Allard-Pride-Lafarge (JCAPL) model. Auxetic-BCC porous materials have lower acoustic resistance and reactance amplitudes than many typical porous materials through experimental verification and comparative analysis of numerical calculations. The porous material's thickness and the backing cavity's thickness have similar effects on sound absorption performance when controlling a single change in structural parameters, and there is an optimum thickness. As acoustic resistance and reactance are dominant at low and high frequencies, respectively, noise reduction is better at low (high) frequencies than at minor (large) porosity, and the porosity of 76.4%–82.0% has the best sound absorption effect. Changes in prism length of materials with high porosity are more sensitive than those with low porosity, so the prism length with porosity of 76.4%, 79.0%, and 82.6% shall be designed to be less than 1.1 mm, 0.9 mm, 0.8 mm, respectively. This study provides theoretical guidance for designing multifunctional porous materials in extreme environments.
Physical activity (PA) is known to improve physical functioning and mental health and to reduce the incidence of dementia. However, studies of the effects of non-recreational PA on the incidence of ...dementia, especially in East Asian populations, remain limited. In this study, we evaluate the association of doing housework with the risk of dementia among participants in the Chinese Longitudinal Healthy Longevity Survey (CLHLS).
The analysis was conducted with data from 7,237 CLHLS participants age over 65 obtained in 2008/2009, 2011/2012, 2014, and 2018. The frequency of housework performance was classified into four groups. A Cox proportional-hazards model was used to examine the association of the baseline housework frequency with the incidence of dementia, with adjustment for demographic and socioeconomic characteristics and lifestyle and health conditions.
The adjusted multivariate model showed that the incidence of dementia was lower among participants who did housework almost every day than among those who rarely or never did housework (hazard ratio = 0.49; 95% confidence interval, 0.39-0.61). The subgroup and sensitivity analyses yielded similar results.
A high frequency of housework performance was associated with a reduced incidence of dementia among older Chinese adults, especially those who did not exercise regularly. The encouragement of engagement in housework would be a cost-effective measure promoting healthy aging in the Chinese population.
The broad adoption of electronic health record (EHR) systems brings us a tremendous amount of clinical data and thus provides opportunities to conduct data-based healthcare research to solve various ...clinical problems in the medical domain. Machine learning and deep learning methods are widely used in the medical informatics and healthcare domain due to their power to mine insights from raw data. When adapting deep learning models for EHR data, it is essential to consider its heterogeneous nature: EHR contains patient records from various sources including medical tests (e.g. blood test, microbiology test), medical imaging, diagnosis, medications, procedures, clinical notes, etc. Those modalities together provide a holistic view of patient health status and complement each other. Therefore, combining data from multiple modalities that are intrinsically different is challenging but intuitively promising in deep learning for EHR. To assess the expectations of multimodal data, we introduce a comprehensive fusion framework designed to integrate temporal variables, medical images, and clinical notes in EHR for enhanced performance in clinical risk prediction. Early, joint, and late fusion strategies are employed to combine data from various modalities effectively. We test the model with three predictive tasks: in-hospital mortality, long length of stay, and 30-day readmission. Experimental results show that multimodal models outperform uni-modal models in the tasks involved. Additionally, by training models with different input modality combinations, we calculate the Shapley value for each modality to quantify their contribution to multimodal performance. It is shown that temporal variables tend to be more helpful than CXR images and clinical notes in the three explored predictive tasks.
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