This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.

The lattice Boltzmann method has become a popular tool for simulating complex flows, including incompressible turbulent flows; however, as an artificial compressibility method, it can generate spurious pressure oscillations whose impact on the statistics of incompressible turbulence has not been systematically examined. In this work, we propose a theoretical approach to analyse the origin of compressibility-induced oscillations (CIOs) and explore ways to suppress or remove them. We begin by decomposing the velocity field and pressure field each into the solenoidal component and the compressive component, and then study the evolution of these two components analytically and numerically. The analysis yields an evolution equation of the mean-square pressure fluctuation which reveals several coupling effects of the two components. The evolution equation suggests that increasing the bulk-to-shear viscosity ratio can suppress CIOs, which is confirmed by numerical simulations. Furthermore, based on the derived evolution equation and data from the simulation, a model is developed to predict the long-term behaviours of the mean-square pressure fluctuations. In the case of decaying turbulence in a periodic domain, we show that the Helmholtz–Hodge decomposition can be used to obtain the solenoidal components reflecting the true evolution of incompressible turbulent flow, from the mesoscopic artificial compressibility approach. The study provides general theoretical guidelines to understand, suppress and even remove CIOs in other related pseudo-compressibility methods.

Item replenishing is essential for item bank maintenance in cognitive diagnostic computerized adaptive testing (CD-CAT). In regular CAT, online calibration is commonly used to calibrate the new items continuously. However, until now no reference has publicly become available about online calibration for CD-CAT. Thus, this study investigates the possibility to extend some current strategies used in CAT to CD-CAT. Three representative online calibration methods were investigated: Method A (Stocking in Scale drift in on-line calibration. Research Rep. 88-28, 1988), marginal maximum likelihood estimate with one EM cycle (OEM) (Wainer & Mislevy In H. Wainer (ed.) Computerized adaptive testing: A primer, pp. 65–102, 1990) and marginal maximum likelihood estimate with multiple EM cycles (MEM) (Ban, Hanson, Wang, Yi, & Harris in J. Educ. Meas. 38:191–212, 2001). The objective of the current paper is to generalize these methods to the CD-CAT context under certain theoretical justifications, and the new methods are denoted as CD-Method A, CD-OEM and CD-MEM, respectively. Simulation studies are conducted to compare the performance of the three methods in terms of item-parameter recovery, and the results show that all three methods are able to recover item parameters accurately and CD-Method A performs best when the items have smaller slipping and guessing parameters. This research is a starting point of introducing online calibration in CD-CAT, and further studies are proposed for investigations such as different sample sizes, cognitive diagnostic models, and attribute-hierarchical structures.

Multidimensional-Method A (M-Method A) has been proposed as an efficient and effective online calibration method for multidimensional computerized adaptive testing (MCAT) (Chen & Xin, Paper presented at the 78th Meeting of the Psychometric Society, Arnhem, The Netherlands, 2013). However, a key assumption of M-Method A is that it treats person parameter estimates as their true values, thus this method might yield erroneous item calibration when person parameter estimates contain non-ignorable measurement errors. To improve the performance of M-Method A, this paper proposes a new MCAT online calibration method, namely, the full functional MLE-M-Method A (FFMLE-M-Method A). This new method combines the full functional MLE (Jones & Jin in Psychometrika 59:59–75, 1994; Stefanski & Carroll in Annals of Statistics 13:1335–1351, 1985) with the original M-Method A in an effort to correct for the estimation error of ability vector that might otherwise adversely affect the precision of item calibration. Two correction schemes are also proposed when implementing the new method. A simulation study was conducted to show that the new method generated more accurate item parameter estimation than the original M-Method A in almost all conditions.

This study revisits the parameter estimation issues in multidimensional item response theory more thoroughly and investigates some computation details that have seldom been addressed previously when implementing the expectation-maximization (EM) algorithm for finite mixtures (EM–FM). Two research questions are: Should we rescale after each EM cycle or after the final EM cycle? How to adapt the supplemented EM algorithm to the EM–FM framework to estimate standard errors (SEs) of all unknown parameters? Analytic details of the methods are provided, and a comprehensive simulation study is conducted to provide supporting evidence. Results reveal that rescaling after each EM cycle accelerates convergence without affecting the calibration accuracy. Moreover, the SEs of all model parameters, including item parameters and population mixing proportions, recover well when the sample size is relatively large (e.g., 2000).

The maintenance of item bank is essential for continuously implementing adaptive tests. Calibration of new items online provides an opportunity to efficiently replenish items for the operational item bank. In this study, a new optimal design for online calibration (referred to as D-c) is proposed by incorporating the idea of original D-optimal design into the reformed D-optimal design proposed by van der Linden and Ren (Psychometrika 80:263–288, 2015) (denoted as D-VR design). To deal with the dependence of design criteria on the unknown item parameters of new items, Bayesian versions of the locally optimal designs (e.g., D-c and D-VR) are put forward by adding prior information to the new items. In the simulation implementation of the locally optimal designs, five calibration sample sizes were used to obtain different levels of estimation precision for the initial item parameters, and two approaches were used to obtain the prior distributions in Bayesian optimal designs. Results showed that the D-c design performed well and retired smaller number of new items than the D-VR design at almost all levels of examinee sample size; the Bayesian version of D-c using the prior obtained from the operational items worked better than that using the default priors in BILOG-MG and PARSCALE; and Bayesian optimal designs generally outperformed locally optimal designs when the initial item parameters of the new items were poorly estimated.

Turbulent circular pipe flows subjected to axial system rotation are studied using direct numerical simulations (DNS) for a wide range of rotation numbers of $Ro_b = 0\unicode{x2013}20$ at a fixed Reynolds number. To ensure that energetic turbulent eddy motions are captured at high rotation numbers, long pipes up to $L_z = 180{\rm \pi} R$ are used in DNS. Two types of energy-containing flow structures have been observed. The first type is hairpin structures that are characteristic of the turbulent boundary layer developing over the pipe wall for both non-rotating and axially rotating flows. The second type is Taylor columns forming at moderate and high rotation numbers. Based on the study of two-point autocorrelation coefficients, it is observed that Taylor columns exhibit quasi-periods in both axial and azimuthal directions. According to the premultiplied spectra, Taylor columns feature one single characteristic axial length scale at the moderate rotation numbers but two at high rotation numbers. It is discovered that the axial system rotation suppresses the sweep events systematically and impedes the formation of hairpin structures. As the rotation number is increased, the turbulence kinetic energy held by Taylor columns enhances rapidly associated with significant increases in their axial length scales.

Compacted bentonite, used as an engineering barrier for permanent containment of high-level radioactive waste, is susceptible to mineral evolution resulting in compromise of the expected barrier performance due to alkaline–thermal chemical interaction in the near-field. To elucidate the mineral-evolution mechanisms within bentonite and the transformation of the nuclide adsorption properties during that period, experimental evolution of bentonite was conducted in a NaOH solution with a pH of 14 at temperatures ranging from 60 to 120°C. The results showed that temperature significantly affects the stability of minerals in bentonite under alkali conditions. The dissolution rate of fine-grained cristobalite in bentonite exceeds that of smectite, with the phase-transition products of smectite being temperature-dependent. As the temperature rises, smectite experiences a three-stage transformation: initially, at 60°C, the lattice structure thins due to the collapse of the octahedral sheets; at 80°C, the lattice disintegrates and reorganizes into a loose framework akin to albite; and by 100°C, it further reorganizes into a denser framework resembling analcime. The adsorption properties of bentonite exhibit a peak inflection point at 80°C, where the dissolution of the smectite lattice eliminates interlayer pores and exposes numerous polar or negatively charged sites which results in a decrease in specific surface area and an increase in cation exchange capacity and adsorption capacity of Eu3+. This research provides insights into the intricate evolution of bentonite minerals and the associated changes in radionuclide adsorption capacity, contributing to a better understanding of the stability of bentonite barriers and the effective long-term containment of nuclear waste.

This study conducts particle-resolved direct numerical simulations to analyse how finite-size spherical particles affect the decay rate of turbulent kinetic energy in non-sustained homogeneous isotropic turbulence. The decaying particle-laden homogeneous isotropic turbulence is generated with two set-ups, i.e. (1) releasing particles into a single-phase decaying homogeneous isotropic turbulence and (2) switching off the driving force of a sustained particle-laden homogeneous isotropic turbulence. With both set-ups, the decay of turbulent kinetic energy follows a power-law when the flow is fully relaxed, similar to their single-phase counterparts. The dependence of the power-law decay exponent $n$ on the particle-to-fluid density ratio, particle size and volume fraction is also investigated, and a predictive model is developed. We find that the presence of heavier particles slows down the long-time power-law decay exponent.

To develop more economical and efficient heavy metal adsorbents, natural bentonite was employed as a raw material, and triethoxyvinylsilane served as a grafting agent to achieve the grafting bonding of sodium polyacrylate and bentonite. Structural alterations in the modified bentonite were analyzed through thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The adsorption and desorption characteristics of SAPAS-Bentonite and raw bentonite were compared and tested under various conditions, including time, temperature, pH, and lead ion concentration. The adsorption and desorption properties of sodium polyacrylate-grafted bentonite (SAPAS-Bentonite) were compared under various conditions (time, temperature, pH, and lead ion concentration). The results revealed that the modified method successfully achieved nano-scale coating of bentonite particles with sodium polyacrylate, leading to an increase in the maximum adsorption capacity of lead ions by 47.5%, reaching 165.73 mg g. A greater adsorption affinity for lead ions was exhibited by the outer sodium polycarboxylate portion of SAPAS-Bentonite compared with the inner bentonite. The adsorption of internal bentonite was limited by blocking when the adsorption of sodium polyacrylate did not reach the upper limit. The adsorption isotherm shifted from the Langmuir monolayer characteristic of the original bentonite to the S-shaped isotherm, reflecting the sodium polycarboxylate properties of SAPAS-Bentonite. Both bentonites demonstrated strong retention capacity for lead, with SAPAS-Bentonite surpassing raw bentonite in performance. This study provides valuable insights into the potential of SAPAS-Bentonite in the treatment of heavy metal pollution.

Malnutrition significantly hampers wound healing processes. This study aimed to compare the effectiveness of the Global Leadership Initiative on Malnutrition (GLIM) and Subjective Global Assessment (SGA) in diagnosing malnutrition and predicting wound healing in patients with diabetic foot ulcers (DFU). GLIM criteria were evaluated for sensitivity (SE), specificity (SP), positive predictive value, negative predictive value and kappa (κ) against SGA as the reference. Modified Poisson regression model and the DeLong test investigated the association between malnutrition and non-healing ulcers over 6 months. This retrospective cohort study included 398 patients with DFU, with a mean age of 66·3 ± 11·9 years. According to SGA and GLIM criteria, malnutrition rates were 50·8 % and 42·7 %, respectively. GLIM criteria showed a SE of 67·3 % (95 % CI 60·4 %, 73·7 %) and SP of 82·7 % (95 % CI 76·6 %, 87·7 %) in identifying malnutrition, with a positive predictive value of 80·0 % and a negative predictive value of 71·1 % (κ = 0·50) compared with SGA. Multivariate analysis demonstrated that malnutrition, as assessed by SGA, was an independent risk factor for non-healing (relative risk (RR) 1·84, 95 % CI 1·45, 2·34), whereas GLIM criteria were associated with poorer ulcer healing in patients with estimated glomerular filtration rate ≥ 60 ml/min/1·73m2 (RR: 1·46, 95 % CI 1·10, 1·94). SGA demonstrated a superior area under the receiver’s operating characteristic curve for predicting non-healing compared with GLIM criteria (0·70 (0·65–0·75) v. 0·63 (0·58–0·65), P < 0·01). These findings suggest that both nutritional assessment tools effectively identify patients with DFU at increased risk, with SGA showing superior performance in predicting non-healing ulcers.