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We report non-monotonic wettability effects on displacement efficiency in heterogeneous porous structures at the post-breakthrough stage, in contrast to the monotonic ones in homogeneous porous structures. Experiments on designed microfluidic chips show that there exists a critical wettability to attain the highest efficiency of displacement in the porous matrix structure combined with a preferential flow pathway, while a stronger wettability of the displacing fluid leads to a higher displacement efficiency on the same matrix structure only. The porous structure with or without a preferential flow pathway results in totally different topological characteristics of phase distribution during displacement. Pore-scale mechanisms are identified to elucidate the formation of this non-monotonic wettability rule: cooperative pore filling under weakly water-wet conditions yields the best displacement; corner flow under strongly water-wet conditions and Haines events under strongly oil-wet conditions decrease the displacement efficiency. The pore-scale findings may provide unique insights into the joint effects of both wettability and flow heterogeneity on fluid displacement in porous media.
To determine if limb lengths, as markers of early life environment, are associated with the risk of diabetes in China.
Design:
We performed a cohort analysis using data from the China Health and Retirement Longitudinal Study (CHARLS), and multivariable-adjusted Cox proportional hazard regression models were used to examine the associations between baseline limb lengths and subsequent risk of diabetes.
Setting:
The CHARLS, 2011–2018.
Participants:
The study confined the eligible subject to 10 711 adults aged over 45 years from the CHARLS.
Results:
During a mean follow-up period of 6·13 years, 1358 cases of incident diabetes were detected. When controlling for potential covariates, upper arm length was inversely related to diabetes (hazard ratio (HR) 0·95, 95 % CI (0·91, 0·99), P = 0·028), and for every 1-cm difference in knee height, the risk of diabetes decreased by about 4 % (HR 0·96, 95 % CI (0·93, 0·99), P = 0·023). The association between upper arm length and diabetes was only significant among females while the association between knee height and diabetes was only significant among males. In analyses stratified by BMI, significant associations between upper arm length/knee height and diabetes only existed among those who were underweight (HR 0·91, 95 % CI (0·83, 1·00), P = 0·049, HR 0·92, 95 % CI (0·86, 0·99), P = 0·031).
Conclusions:
Inverse associations were observed between upper arm length, knee height and the risk for diabetes development in a large Asian population, suggesting early life environment, especially infant nutritional status, may play an important role in the determination of future diabetes risk.
This study evaluated the association between inflammatory diets as measured by the dietary inflammatory index (DII), and inflammation biomarkers, and the development of preeclampsia among the Chinese population. We followed the reporting guidelines of the STROBE statement for observational studies. A total of 466 preeclampsia cases aged over 18 years were recruited between March 2016 and June 2019, and 466 healthy controls were 1:1 ratio matched by age (± 3 years), week of gestation (± 1 week), and gestational diabetes mellitus. The energy-adjusted DII (E-DII) was computed based on dietary intake assessed using a 79-item semiquantitative food frequency questionnaire (FFQ). Inflammatory biomarkers were analyzed by ELISA kits. The mean E-DII scores were -0.65 ± 1.58 for cases and -1.19 ± 1.47 for controls (P value <0.001). E-DII scores positively correlated with IFN-γ (rs = 0.194, P value = 0.001) and IL-4 (rs = 0.135, P value = 0.021). After multivariable adjustment, E-DII scores were positively related to preeclampsia risk (P trend <0.001). The highest tertile of E-DII was 2.18 times the lowest tertiles (95% CI = 1.52, 3.13). The odds of preeclampsia increased by 30% (95% CI= 18%, 43%, P value <0.001) for each E-DII score increase. The preeclampsia risk was positively associated with IL-2 (OR = 1.07, 95% CI = 1.03, 1.11), IL-4 (OR = 1.26, 95% CI = 1.03, 1.54) and TGF-β (OR = 1.17, 95% CI = 1.06, 1.29). Therefore, proinflammatory diets, corresponding to higher IL-2, IL-4 and TGF-β levels, were associated with increased preeclampsia risk.
This study is performed to figure out how the presence of diabetes affects the infection, progression and prognosis of 2019 novel coronavirus disease (COVID-19), and the effective therapy that can treat the diabetes-complicated patients with COVID-19. A multicentre study was performed in four hospitals. COVID-19 patients with diabetes mellitus (DM) or hyperglycaemia were compared with those without these conditions and matched by propensity score matching for their clinical progress and outcome. Totally, 2444 confirmed COVID-19 patients were recruited, from whom 336 had DM. Compared to 1344 non-DM patients with age and sex matched, DM-COVID-19 patients had significantly higher rates of intensive care unit entrance (12.43% vs. 6.58%, P = 0.014), kidney failure (9.20% vs. 4.05%, P = 0.027) and mortality (25.00% vs. 18.15%, P < 0.001). Age and sex-stratified comparison revealed increased susceptibility to COVID-19 only from females with DM. For either non-DM or DM group, hyperglycaemia was associated with adverse outcomes, featured by higher rates of severe pneumonia and mortality, in comparison with non-hyperglycaemia. This was accompanied by significantly altered laboratory indicators including lymphocyte and neutrophil percentage, C-reactive protein and urea nitrogen level, all with correlation coefficients >0.35. Both diabetes and hyperglycaemia were independently associated with adverse prognosis of COVID-19, with hazard ratios of 10.41 and 3.58, respectively.
Modern low-altitude unmanned aircraft (UA) detection and surveillance systems mostly adopt the multi-sensor fusion technology scheme of radar, visible light, infrared, acoustic and radio detection. Firstly, this paper summarises the latest research progress of UA and bird target detection and recognition technology based on radar, and provides an effective way of detection and recognition from the aspects of echo modeling and micro motion characteristic cognition, manoeuver feature enhancement and extraction, motion trajectory difference, deep learning intelligent classification, etc. Furthermore, this paper also analyses the target feature extraction and recognition algorithms represented by deep learning for other kinds of sensor data. Finally, after a comparison of the detection ability of various detection technologies, a technical scheme for low-altitude UA surveillance system based on four types of sensors is proposed, with a detailed description of its main performance indicators.
The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global health crisis that may cause mental health problems and heighten suicide risk. We investigated the impact of the COVID-19 pandemic on trends in suicide attempts and suicide deaths in New Taipei City, Taiwan.
Methods
The current study used the official daily data on suicide attempts and deaths in New Taipei City, Taiwan (4 million inhabitants) between 2015 and 2020 from the Taiwan National Suicide Prevention Reporting System. Interrupted time-series (ITS) analyses with parameters corrected by the estimated autocorrelations were applied on weekly aggregated data to examine whether the suicide trends during the early COVID-19 pandemic (late January to July 2020) deviated from previous trends (January 2015 to late January 2020). The impact due to the suicide prevention policy change was also examined (since August 2020).
Results
ITS analyses revealed no significant increases in both mean and trend on weekly suicide deaths during the COVID-19 pandemic and after the policy change. In contrast, there was a significant increasing trend in weekly suicide attempts since the COVID-19 outbreak at the rate of 1.54 attempts per week (95% confidence interval 0.49–2.60; p = 0.004). Sex difference analysis revealed that, however, this increasing trend was observed only in females not in males.
Conclusions
The COVID-19 pandemic has different impacts on suicides attempts and deaths during the early pandemic in New Taipei City, Taiwan. The COVID-19 outbreak drastically increased the trend of suicide attempts. In contrast, the number of suicide deaths had remained constant in the investigated periods.
The apple buprestid, Agrilus mali Matsumura, that was widespread in north-eastern China, was accidently introduced to the wild apple forest ecosystem in mountainous areas of Xinjiang, China. This invasive beetle feeds on domesticated apples and many species of Malus and presents a serious threat to ancestral apple germplasm sources and apple production worldwide. Estimating the potential area at risk of colonization by A. mali is crucial for instigating appropriate preventative management strategies, especially under global warming. We developed a CLIMEX model of A. mali to project this pest's potential distribution under current and future climatic scenarios in 2100 using CSIRO-Mk 3.0 GCM running the SRES A1B emissions scenario. Under current climate, A. mali could potentially invade neighbouring central Asia and eventually the mid-latitude temperate zone, and some subtropical areas and Pampas Steppe in the Southern Hemisphere. This potential distribution encompasses wild apples species, the ancestral germplasm for domesticated apples. With global warming, the potential distribution shifts to higher latitudes, with the potential range expanding slightly, though the overall suitability could decline in both hemispheres. In 2100, the length of the growing season of this pest in the mid-latitude temperature zone could increase by 1–2 weeks, with higher growth rates in most sites compared with current climate in mid-latitudes, at least in China. Our work highlights the need for strategies to prevent the spread of this pest, managing the threats to wild apples in Tian Shan Mountain forests in Central Asia, and commercial apple production globally. We discuss practical management tactics to reduce the spread of this pest and mitigate its impacts.
In vivo transparent vessel segmentation is important to life science research. However, this task remains very challenging because of the fuzzy edges and the barely noticeable tubular characteristics of vessels under a light microscope. In this paper, we present a new machine learning method based on blood flow characteristics to segment the global vascular structure in vivo. Specifically, the videos of blood flow in transparent vessels are used as input. We use the machine learning classifier to classify the vessel pixels through the motion features extracted from moving red blood cells and achieve vessel segmentation based on a region-growing algorithm. Moreover, we utilize the moving characteristics of blood flow to distinguish between the types of vessels, including arteries, veins, and capillaries. In the experiments, we evaluate the performance of our method on videos of zebrafish embryos. The experimental results indicate the high accuracy of vessel segmentation, with an average accuracy of 97.98%, which is much more superior than other segmentation or motion-detection algorithms. Our method has good robustness when applied to input videos with various time resolutions, with a minimum of 3.125 fps.
The Lancang-Mekong River Basin (LMRB) is Asia's most important transboundary river. The precipitation-dependent agriculture and the world's largest inland fishery in the basin feed more than 70 million people. Floods are the main natural disasters which pose a serious threat to the local agriculture and human life. In the future, climate change will affect the streamflow and lead to changes in flood events. Based on the GMDF and GCM data, the SPI and the VIC model were used to assess the impact of climate change on streamflow and flood events during the historical (1985–2016) and future periods (2020–2050) in the LMRB. The results show that the LMRB will become more humid in the future and annual precipitation will change from about -2 to 6 per cent under RCP4.5 and RCP8.5. In the future, this basin should experience a higher flood risk, with more flood events and a relative increase in the flood peak and frequency reaching up to +15 and +58 per cent, respectively. This study contributes to improve our understanding of the role of climate change on streamflow and flood events and provides a scientific reference for the development of local water resources management in the LMRB.
The present study investigated the foreign language effect within an altruistic decision making process. Chinese–English bilinguals made altruistic decisions in their native (L1: Chinese) and second language (L2: English). The decisions were framed in two ways: either as “not to harm” (harm frame) or as “to help” the other person (help frame) at one's economic cost. Behavioral results suggest that bilinguals might behave more altruistically in the harm frame than the help frame (i.e., framing effect) in their native language but not in their foreign language. Electrophysiological results show that the modulation of the framing effect in the native versus foreign language originated in the early ERP components (N1 and N2) and did not present in the late positive potential (LPP). These findings suggest the foreign language effect most likely results from the reduced emotional reaction in a foreign compared to the native language.
Athetis lepigone Möschler (Lepidoptera, Noctuidae) is a common maize pest in Europe and Asia. However, there is no long-term effective management strategy is available yet to suppress its population. Adults rely heavily on olfactory cues to locate their optimal host plants and oviposition sites. Pheromone-binding proteins (PBPs) are believed to be responsible for recognizing and transporting different odorant molecules to interact with receptor membrane proteins. In this study, the ligand-binding specificities of two AlepPBPs (AlepPBP2 and AlepPBP3) for sex pheromone components and host plant (maize) volatiles were measured by fluorescence ligand-binding assay. The results demonstrated that AlepPBP2 had a high affinity with two pheromones [(Z)-7-dodecenyl acetate, Ki = 1.11 ± 0.1 μM, (Z)-9-tetradecenyl acetate, Ki = 1.32 ± 0.15 μM] and ten plant volatiles, including (-)-limonene, α-pinene, myrcene, linalool, benzaldehyde, nonanal, 2-hexanone, 3-hexanone, 2-heptanone and 6-methyl-5-hepten-2-one. In contrast, we found that none of these chemicals could bind to AlepPBP3. Our results clearly show no significant differences in the functional characterization of the binding properties between AlepPBP2 and AlepPBP3 to sex pheromones and host plant volatiles. Furthermore, molecular docking was employed for further detail on some crucial amino acid residues involved in the ligand-binding of AlepPBP2. These findings will provide valuable information about the potential protein binding sites necessary for protein-ligand interactions which appear as attractive targets for the development of novel technologies and management strategies for insect pests.
The wheat aphid Sitobion miscanthi (CWA) is an important harmful pest in wheat fields. Insecticide application is the main method to effectively control wheat aphids. However, CWA has developed resistance to some insecticides due to its extensive application, and understanding resistance mechanisms is crucial for the management of CWA. In our study, a new P450 gene, CYP4CJ6, was identified from CWA and showed a positive response to imidacloprid and thiamethoxam. Transcription of CYP4CJ6 was significantly induced by both imidacloprid and thiamethoxam, and overexpression of CYP4CJ6 in the imidacloprid-resistant strain was also observed. The sensitivity of CWA to these two insecticides was increased after the knockdown of CYP4CJ6. These results indicated that CYP4CJ6 could be associated with CWA resistance to imidacloprid and thiamethoxam. Subsequently, the posttranscriptional regulatory mechanism was assessed, and miR-316 was confirmed to participate in the posttranscriptional regulation of CYP4CJ6. These results are crucial for clarifying the roles of P450 in the resistance of CWA to insecticides.
External modulation on thermal convection has been studied extensively to achieve the control of flow structures and heat-transfer efficiency. In this paper, we carry out direct numerical simulations on Rayleigh–Bénard convection accounting for both the modulation of wall shear and roughness over the Rayleigh number range $1.0 \times 10^6 \le Ra \le 1.0 \times 10^8$, the wall shear Reynolds number range $0 \le Re_w \le 5000$, the aspect-ratio range $2 \le \varGamma \le 4{\rm \pi}$, and the dimensionless roughness height range $0 \le h \le 0.2$ at fixed Prandtl number $Pr = 1$. Under the combined actions of wall shear and roughness, with increasing $Re_w$, the heat flux is initially enhanced in the buoyancy-dominant regime, then has an abrupt transition near the critical shear Reynolds number $Re_{w,cr}$, and finally enters the purely diffusion regime dominated by shear. Based on the crossover of the kinetic energy production between the buoyancy-dominant and shear-dominant regimes, a physical model is proposed to predict the transitional scaling behaviour between $Re_{w,cr}$ and $Ra$, i.e. $Re_{w,cr} \sim Ra^{9/14}$, which agrees well with our numerical results. The reason for the observed heat-transport enhancement in the buoyancy-dominant regime is further explained by the fact that the moving rough plates introduce an external shear to strengthen the large-scale circulation (LSC) in the vertical direction and serve as a conveyor belt to increase the chances of the interaction between the LSC and secondary flows within cavities, which triggers more thermal plumes, efficiently transports the trapped hot (cold) fluids outside cavities.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
Aims
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
Method
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
Results
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
Conclusions
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
A direct numerical simulation database of a weakly compressible turbulent channel flow with bulk Mach number 1.56 is studied in detail, including the geometrical relationships between the pressure-Hessian tensor and the vorticity/strain-rate tensor, as well as the mechanism of the pressure-Hessian tensor contributing to the evolution of invariants of the velocity gradient tensor. The results show that the geometrical relationships between the pressure-Hessian tensor and the vorticity/strain-rate tensor in the central region of the channel are consistent with that of isotropic turbulence. However, in the buffer layer with relatively stronger inhomogeneity and anisotropy, the vorticity tends to be aligned with the first or second eigenvector of the pressure-Hessian tensor in the unstable focus/compressing topological region, and tends to be aligned with the first eigenvector of the pressure-Hessian tensor in the stable focus/stretching topological region. In the unstable node/saddle/saddle and stable node/saddle/saddle topological regions, the vorticity prefers to lie in the plane of the first and second eigenvectors of the pressure-Hessian tensor. The strain-rate and the pressure-Hessian tensors tend to share their second principal direction. Moreover, for the coupling between the pressure-Hessian tensor and the principal strain rates, we clarify the influence on dissipation, the nonlinear generation of dissipation and the enstrophy generation. The decomposition of the pressure-Hessian tensor further shows that the slow pressure-related term dominates the pressure-Hessian tensor's contribution, and the influence of inhomogeneity and anisotropy mainly originates from the inhomogeneity and anisotropy of the fluctuating velocity. These statistical properties would be instructive in formulating dynamical models of the velocity gradient tensor for wall turbulence.
Extrinsic mortality risks calibrating fast life history (LH) represent a species-general principle that applies to almost all animals including humans. However, empirical research also finds exceptions to the LH principle. The present study proposes a maternal socialization hypothesis, whereby we argue that the more human-relevant attachment system adds to the LH principle by up- and down-regulating environmental harshness and unpredictability and their calibration of LH strategies. Based on a longitudinal sample of 259 rural Chinese adolescents and their primary caregivers, the results support the statistical moderating effect of caregiver–child attachment on the relation between childhood environmental adversities (harshness and unpredictability) and LH strategies. Our theorizing and findings point to an additional mechanism likely involved in the organization and possibly the slowdown of human LH.
Direct numerical simulation of spanwise-rotation-driven flow transitions in viscoelastic plane Couette flow from a drag-reduced inertial to a drag-enhanced elasto-inertial turbulent flow state followed by full relaminarization is reported for the first time. Specifically, this novel flow transition begins with a drag-reduced inertial turbulent flow state at a low rotation number $0\leqslant Ro \leqslant 0.1$, and then transitions to a rotation/polymer-additive-driven drag-enhanced inertial turbulent regime, $0.1\leqslant Ro \leqslant 0.3$. In turn, the flow transitions to a drag-enhanced elasto-inertial turbulent state, $0.3\leqslant Ro \leqslant 0.9$, and eventually relaminarizes at $Ro=1$. In addition, two novel rotation-dependent drag enhancement mechanisms are proposed and substantiated. (1) The formation of large-scale roll cells results in enhanced convective momentum transport along with significant polymer elongation and stress generated in the extensionally dominated flow between adjacent roll cells at $Ro\leqslant 0.2$. (2) Coriolis-force-generated turbulent vortices cause strong incoherent transport and homogenization of significant polymer stress in the bulk via their vortical circulations at $Ro=0.5 - 0.9$.
The thin set theorem for n-tuples and k colors (
$\operatorname {\mathrm {\sf {TS}}}^n_k$
) states that every k-coloring of
$[\mathbb {N}]^n$
admits an infinite set of integers H such that
$[H]^n$
avoids at least one color. In this paper, we study the combinatorial weakness of the thin set theorem in reverse mathematics by proving neither
$\operatorname {\mathrm {\sf {TS}}}^n_k$
, nor the free set theorem (
$\operatorname {\mathrm {\sf {FS}}}^n$
) imply the Erdős–Moser theorem (
$\operatorname {\mathrm {\sf {EM}}}$
) whenever k is sufficiently large (answering a question of Patey and giving a partial result towards a question of Cholak Giusto, Hirst and Jockusch). Given a problem
$\mathsf {P}$
, a computable instance of
$\mathsf {P}$
is universal iff its solution computes a solution of any other computable
$\mathsf {P}$
-instance. It has been established that most of Ramsey-type problems do not have a universal instance, but the case of Erdős–Moser theorem remained open so far. We prove that Erdős–Moser theorem does not admit a universal instance (answering a question of Patey).
Primitive lamprophyres in orogenic belts can provide crucial insights into the nature of the subcontinental lithosphere and the relevant deep crust–mantle interactions. This paper reports a suite of relatively primitive lamprophyre dykes from the North Qiangtang, central Tibetan Plateau. Zircon U–Pb ages of the lamprophyre dykes range from 214 Ma to 218 Ma, with a weighted mean age of 216 ± 1 Ma. Most of the lamprophyre samples are similar in geochemical compositions to typical primitive magmas (e.g. high MgO contents, Mg no. values and Cr, with low FeOt/MgO ratios), although they might have experienced a slightly low degree of olivine crystallization, and they show arc-like trace-element patterns and enriched Sr–Nd isotopic composition ((87Sr/86Sr)i = 0.70538–0.70540, ϵNd(t) = −2.96 to −1.65). Those geochemical and isotopic variations indicate that the lamprophyre dykes originated from partial melting of a phlogopite- and spinel-bearing peridotite mantle modified by subduction-related aqueous fluids. Combining with the other regional studies, we propose that slab subduction might have occurred during Late Triassic time, and the rollback of the oceanic lithosphere induced the lamprophyre magmatism in the central Tibetan Plateau.
Accurate predetermination of the quantum yield ratio (QA/QD) and the extinction coefficient ratio (KA/KD) between acceptor and donor is a prerequisite for quantitative fluorescence resonance energy transfer (FRET) imaging. We here propose a method to measure KA/KD and QA/QD by measuring the excitation–emission spectra (ExEm-spectra) of one dish of cells expressing m (≥3) kinds of FRET constructs. The ExEm-spectra images are unmixed to obtain the weight maps of donor (WD), acceptor (WA), and acceptor sensitization (WS). For each cell, the frequency distribution plots of the WS/WD and WS/WA images are fitted by using a single-Gaussian function to obtain the peak values of WS/WD (SD) and WS/WA (SA). The statistical frequency-SD/SA plots from all cells are fitted by using a multi-Gaussian function to obtain the peak values of both SD and SA, and then the ranges of WS/WD (RSD) and WS/WA (RSA) for each FRET construct are predetermined. Based on the predetermined RSD and RSA values of FRET constructs, our method is capable of automatically classifying cells expressing different FRET constructs. Finally, the WS/WD–WA/WD plot from different kinds of cells is linearly fitted to obtain KA/KD and QA/QD values.