To date, a comprehensive understanding of the influence of the Prandtl number ($Pr$) on flow topology in turbulent Rayleigh–Bénard convection (RBC) remains elusive. In this study, we present an experimental investigation into the evolution of flow topology in quasi-two-dimensional turbulent RBC with $7.0 \leq Pr \leq 244.2$ and $2.03\times 10^{8} \leq Ra \leq 2.81\times 10^{9}$. Particle image velocimetry (PIV) measurements reveal the flow transitions from multiple-roll state to single-roll state with increasing $Ra$, and the transition is hindered with increasing $Pr$, i.e. the transitional Rayleigh number $Ra_t$ increases with $Pr$. We mapped out a phase diagram on the flow topology change on $Ra$ and $Pr$, and identified the scaling of $Ra_t$ on $Pr$: $Ra_t \sim Pr^{0.93}$ in the low $Pr$ range, and $Ra_t \sim Pr^{3.3}$ in the high $Pr$ range. The scaling in the low $Pr$ range is consistent with the model of balance of energy dissipation time and plume travel time that we proposed in our previous study, while the scaling in the high $Pr$ range implies a new governing mechanism. For the first time, the scaling of $Re$ on $Ra$ and $Pr$ is acquired through full-field PIV velocity measurement, $Re \sim Ra^{0.63}\,Pr^{-0.87}$. We also propose that increasing horizontal velocity promotes the formation of the large-scale circulation (LSC), especially for the high $Pr$ case. Our proposal was verified by achieving LSC through introducing horizontal driving force $Ra_H$ by tilting the convection cell with a small angle.

In order to clarify and visualize the real state of the structural performances of ships in operation and establish a more optimal, data-driven framework for ship design, construction and operation, an industry-academia joint R&D project on the digital twin for ship structures (DTSS) was conducted in Japan. This paper presents the major achievements of the project. The DTSS aims to grasp the stress responses over the whole ship structure in waves by data assimilation that merges hull monitoring and numerical simulation. Three data assimilation methods, namely, the wave spectrum method, Kalman filter method, and inverse finite element method were used, and their effectiveness was examined through model and full-scale ship measurements. Methods for predicting short-term extreme responses and long-term cumulative fatigue damage were developed for navigation and maintenance support using statistical approaches. In comparison with conventional approaches, response predictions were significantly improved by DTSS using real response data in encountered waves. Utilization scenarios for DTSS in the maritime industry were presented from the viewpoints of navigation support, maintenance support, rule improvement, and product value improvement, together with future research needs for implementation in the maritime industry.

We report an experimental study about the effect of an obstructed centre on heat transport and flow reversal by inserting an adiabatic cylinder at the centre of a quasi-two-dimensional Rayleigh–Bénard convection cell. The experiments are carried out in a Rayleigh number ($Ra$) range of $2\times 10^7 \leq Ra \leq 2\times 10^9$ and at a Prandtl number ($Pr$) of $5.7$. It is found that for low $Ra$, the obstructed centre leads to a heat transfer enhancement of up to 21 $\%$, while as $Ra$ increases, the magnitude of the heat transfer enhancement decreases and the heat transfer efficiency ($Nu$) eventually converges to that of the unobstructed normal cell. Particle image velocimetry measurements show that the heat transfer enhancement originates from the change in flow topology due to the presence of the cylindrical obstruction. In the low-$Ra$ regime the presence of the obstruction promotes the transition of the flow topology from the four-roll state to the abnormal single-roll state then to the normal single-roll state with increasing obstruction size. While in the high-$Ra$ regime, the flow is always in the single-roll state regardless of the obstruction size, although the flow becomes more coherent with the size of the obstruction. We also found that in the presence of the cylindrical obstruction, the stability of the corner vortices is significantly reduced, leading to a large reduction in the frequency of flow reversals.

We construct an autoregressive moving average (ARMA) model consisting of the history and random effects for the streamwise velocity fluctuation in boundary-layer turbulence. The distance to the wall and the boundary-layer thickness determine the time step and the order of the ARMA model, respectively. Based on the autocorrelation's analytical expression of the ARMA model, we obtain a global analytical expression for the second-order structure function, which asymptotically captures the inertial, dynamic and large-scale ranges. Specifically, the exponential autocorrelation of the ARMA model arises from the autoregressive coefficients and is modified to logarithmic behaviour by the moving-average coefficients. The asymptotic expressions enable us to determine model coefficients by existing parameters, such as the Kolmogorov and the Townsend–Perry constants. A consequent double-log expression for the characteristic length scale is derived and is justified by direct numerical simulation data with $Re_\tau \approx 5200$ and field-measured neutral atmospheric surface layer data with $Re_\tau \sim O(10^6)$ from the Qingtu Lake Observation Array site. This relation is robust because it applies to $Re_\tau$ from $O(10^4)$ to $O(10^6)$, and even when the statistics of natural ASL deviate from those of canonical boundary-layer turbulence, e.g. in the case of imbalance in energy production and dissipation, and when the Townsend–Perry constant deviates from traditional values.

Functional montmorillonite can be dispersed in polymer coatings and organic species and polymers can be intercalated into the interlayer space or grafted onto the surface of the functional montmorillonite. The addition of functional montmorillonite into polymer-based coatings can significantly improve anti-corrosion, refractory, super-hydrophobicity, antibacterial activity, and absorption of solar radiation by the resulting montmorillonite/polymer coatings. Montmorillonite can be functionalized for this purpose by ion exchange, intercalation, exfoliation, or combinations of these treatments. The rigid montmorillonite layers interspersed within the polymer matrix inhibit the penetration of corrosive substances, minimize the impact of high-temperature airflow, and thereby lead to strong resistance of the coating to corrosion and fire. The combination of polymers and dispersed montmorillonite nanolayers, which are modified by metal ions, metal oxides, and hydrophobic organic species, allows the resulting  composite coating to have quite a rough surface and a much smaller surface free energy so that the montmorillonite/polymer coating possesses superhydrophobicity. The interlayer space of functional montmorillonite can also host or encapsulate antibacterial substances, phase-change materials, and solar energy-absorbing materials. Moreover, it can act as a template to make these guest species exist in a more stable and ordered state. Literature surveys suggest that future work on the functional montmorillonite/polymer coatings should be targeted at the manufacture of functional montmorillonite nanolayers by finding more suitable modifiers and tuning the dispersion and funtionalities of montmorillonite in the coatings.

Clear cell renal cell carcinoma (ccRCC) is the main type of malignancy in kidney related to glucose metabolism. Primary single cell culture and single cell sequencing are novel research technologies. In this study, we explored the differentiation status of ccRCC cells and its significance in prognosis and immunotherapeutic response through bioinformatics. We characterized distinct differentiation states and differentiation-related genes (DRGs) in ccRCC cells through single cell RNA sequencing (scRNA-seq) analysis. Combined with bulk RNA-seq data, we classified patients into two clusters and found that this classification was closely correlated with patient prognosis and immunotherapeutic responses. Based on machine learning, we identified a prognostic risk model composed of 14 DRGs, including BTG2, CDKN1A, COL6A1, CPM, CYB5D2, FOSB, ID2, ISG15, PLCG2, SECISBP2, SOCS3, TES, ZBTB16, and ZNF704, to predict the survival rate of patients and then constructed a nomogram model integrating clinicopathological characteristics and risk score for clinical practice. In the study of immune checkpoints, we found that patients in the high-risk group had a disposition to get worse prognosis and better effects of immune checkpoint blocking therapies. Finally, we found the expression level of model DRGs was associated with a tumor-immune microenvironment (TIME) pattern and the response of 83 compounds or inhibitors was significantly different in the two risk groups. In a word, our study highlights the potential contribution of cell differentiation in prognosis judgment and immunotherapy response and offers promising therapeutic options for ccRCC patients.

In continuation of our earlier work (Chen & Sreenivasan, J. Fluid Mech., vol. 908, 2021, R3; Chen & Sreenivasan, J. Fluid Mech., vol. 933, 2022a, A20 – together referred to as CS hereafter), we present a self-consistent Reynolds number asymptotics for wall-normal profiles of variances of streamwise and spanwise velocity fluctuations as well as root-mean-square pressure, across the entire flow region of channel and pipe flows and flat-plate boundary layers. It is first shown that, when normalized by peak values, the Reynolds number dependence and wall-normal variation of all three profiles can be decoupled, in excellent agreement with available data, sharing the common inner expansion of the type $\phi (y^+)=f_0(y^+)+f_1(y^+)/Re^{1/4}_\tau$, where $\phi$ is one of the quantities just mentioned, the functions $f_0$ and $f_1$ depend only on $y^+$, and $Re_\tau$ is the friction Reynolds number. Here, the superscript $+$ indicates normalization by wall variables. We show that this result is completely consistent with CS. Secondly, by matching the above inner expansion and the outer flow similarity form, a bounded variation $\phi (y^\ast )=\alpha _\phi -\beta _{\phi }y^{{\ast {1}/{4}}}$ is derived for the outer region where, for each $\phi$, the constants $\alpha _\phi$ and $\beta _{\phi }$ are independent of $Re_\tau$ and $y^\ast$ $\equiv y^+/Re_\tau$ – also in excellent agreement with simulations and experimental data. One of the predictions of the analysis is that, for asymptotically high Reynolds numbers, a finite plateau $\phi \approx \alpha _\phi$ appears in the outer region. This result sheds light on the intriguing issue of the outer shoulder of the variance of the streamwise velocity fluctuation, which should be bounded by the asymptotic plateau of approximately 10.

Previous studies show that even though monolingual children find subject relatives easier than object relatives, their comprehension of object relatives can be facilitated by morphological cues. Given that in heritage contexts functional morphology is a vulnerable domain, a question that needs to be addressed is whether bilingual children, who are heritage speakers of their L1, will also be able to use morphological cues to comprehend complex syntax. To contribute to this line of research, we focused on monolingual (N = 18; Mean Age: 11.43) and bilingual/first generation (N = 108; Mean Age: 11.98), Syrian Arabic-speaking children in Canada, and examined their ability to use gender morphology in their comprehension of relative clauses, while taking into consideration cognitive, environmental, and age-related variables. To this end, we used two offline sentence-picture matching tasks targeting relative clauses and gender (as encoded in SV agreement and object clitics). Results showed that, like monolingual children, first-generation, Arabic-speaking children living in Canada used morphological cues to comprehend complex syntax in their L1. Furthermore, even though there was an association between comprehension of gender agreement and comprehension of relative clauses, performance in gender agreement was higher than performance in relative clauses, suggesting that challenges with complex syntactic structures are not necessarily an epiphenomenon of a morphological deficit.

Emergent bilinguals (EBs) who are exposed to societal language at school but use another language at home may experience difficulties in mastering the societal language, especially those at risk for language and reading disabilities. Learning phonologically specific new words that discriminate between phonemes may foster phonological awareness and word reading. This study examined the effectiveness of a lexical specificity intervention program that targeted phoneme discrimination in EBs at risk for reading disabilities. EBs who scored below the 25th percentile on the screening measures were selected and randomly assigned to one of two conditions: at-risk intervention or at-risk control. Of the 76 EBs in the at-risk group, 40 were randomly assigned to receive the intervention. A group of 51 typically developing EBs who did not meet the risk criteria were selected as typical controls. The pre- and post-tests include phoneme discrimination, phonological awareness, rapid automatized naming, fluency, and decoding. The at-risk intervention group showed improvement on the phoneme discrimination task after the intervention and outperformed the at-risk control group but not the typical control group. In addition, growth was observed during both the training and testing sessions of the intervention. The lexical specificity intervention could be a good resource to enhance a key precursor to literacy development for at-risk EBs.

A novel data-driven modal analysis method, reduced-order variational mode decomposition (RVMD), is proposed, inspired by the Hilbert–Huang transform and variational mode decomposition (VMD), to resolve transient or statistically non-stationary flow dynamics. First, the form of RVMD modes (referred to as an ‘elementary low-order dynamic process’, ELD) is constructed by combining low-order representation and the idea of intrinsic mode function, which enables the computed modes to characterize the non-stationary properties of space–time fluid flows. Then, the RVMD algorithm is designed based on VMD to achieve a low-redundant adaptive extraction of ELDs in flow data, with the modes computed by solving an elaborate optimization problem. Further, a combination of RVMD and Hilbert spectral analysis leads to a modal-based time-frequency analysis framework in the Hilbert view, providing a potentially powerful tool to discover, quantify and analyse the transient and non-stationary dynamics in complex flow problems. To provide a comprehensive evaluation, the computational cost and parameter dependence of RVMD are discussed, as well as the relations between RVMD and some classic modal decomposition methods. Finally, the virtues and utility of RVMD and the modal-based time-frequency analysis framework are well demonstrated via two canonical problems: the transient cylinder wake and the planar supersonic screeching jet.

The western Mongolian Lake Zone was a Neoproterozoic to early Paleozoic volcanic arc where tuffs, lavas, fossiliferous siliciclastics, and carbonates accumulated during the early Cambrian. An uppermost Cambrian Series 2 (upper Stage 4) trilobite assemblage is described here from the Burgasutay Formation representing a continuous lower Cambrian succession at the Seer Ridge of the Great Lake Depression. The new assemblage is dominated by dorypygids and consists of 13 trilobite genera belonging to nine families including Catinouyia heyunensis new species. These fossils comprise the youngest and richest lower Cambrian trilobite assemblage in Mongolia. The composition of the Lake Zone fauna suggests its biogeographic affinity with the Siberian Platform and Altay-Sayan Foldbelt, but the presence of inouyiids also implies a connection of this region with East Gondwana.

UUID: http://zoobank.org/fb0ebe23-144f-46ed-9543-7df9eea85fbc

Long-term exposure to extreme temperatures could threaten individuals' mental health and psychological wellbeing. This study aims to investigate the long-term impact of cumulative exposure to extreme temperature. Differently from existing literature, we define extreme temperature exposure in relative terms based on local temperature patterns. Combining the China Health and Retirement Longitudinal Study and environmental data from the U.S. National Oceanic and Atmospheric Administration from 2011 to 2015, this study demonstrates that heat and cold exposure days in the past year significantly increase the measured depression level of adults over age 45 by 1.75 and 3.00 per cent, respectively, controlling for the city, year, and individual fixed effects. The effect is heterogeneous across three components of depression symptoms as well as age, gender, and areas of residency, and air conditioning and heating equipment are effective in alleviating the adverse impact of heat and cold exposure. The estimation is robust and consistent across a variety of temperature measurements and model modifications. Our findings provide evidence on the long-term and accumulative cost of extreme temperature to middle-aged and elderly human capital, contributing to the understanding of the social cost of climate change and the consequent health inequality.

The application scopes of two different reductive perturbation methods to derive the Korteweg–de Vries (KdV) equation and coupled KdV (CKdV) equation in two-temperature-ion dusty plasma are given by using the particle-in-cell (PIC) numerical method in the present paper. It suggests that the reductive perturbation method (RPM) is valid if the amplitude of the CKdV solitary wave is small enough. However, for the KdV solitary wave, RPM is valid not only if the amplitude of the KdV solitary wave is small enough, but also if the nonlinear coefficient of the KdV equation is not tending to zero.