To accurately calculate the turbulent exchange coefficient, the contribution of multi-scale turbulent transportation needs to be considered, especially in the complex terrain of the coastal area. In September 2019, a comprehensive observation experiment on the offshore atmospheric boundary layer was carried out at the Yangmeikeng Ecological Monitoring Station and Sai Chung Gulf. Through scale decomposition, it is shown that the turbulent motion in the atmospheric boundary layer in the coastal area is affected by the underlying surface, such as that of the coastal land or the sea–land boundary. This is the main reason behind the phenomenon whereby different scales make different contributions to momentum flux. Different multi-scale characteristics of turbulent structures on the underlying surface affect the drag coefficient. Through wavelet transform and finite element method, the characteristics of the multi-scale flow structures produced by the complicated offshore terrain are analysed. It is found that large-scale flow structures enhance the pulsating intensity at the small scale, but the large-scale coherence characteristics are different from those at the small scale. In summary, in comparing these three sites, the flux exchange on the roof is greatest, followed by that on the tower. In the Gulf, the flux exchange is mainly dependent on small-scale structures, which are linked with the smallest values.

We present the results of two population surveys conducted 10 years apart (December 2010–February 2011 and December 2020–January 2021) of the Critically Endangered white-headed langur Trachypithecus leucocephalus in the Chongzuo White-Headed Langur National Nature Reserve, Guangxi Province, China. In the first survey, we recorded 818 individuals in 105 groups and 16 solitary adult males. In the second survey, we recorded 1,183 individuals in 128 groups and one solitary adult male. As a result of government policies, poaching for food and traditional medicine is no longer a primary threat to these langurs. However, severe forest loss and fragmentation caused by human activities could limit any future increase of this langur population.

The physics of leading-edge vortex (LEV) stability on flapping wings and autorotating seeds is still underexplored due to its complex dependency on Reynolds number ($\textit {Re}$), aspect ratio (AR) and Rossby number (Ro). Our previous study observed an interesting dual-stage vortex tilting between radial and tangential components in a stable LEV. Here, the establishment of this novel mechanism, i.e. dual-stage radial–tangential vortex tilting (DS-VT$_{r-t}$), is investigated and explained in detail using numerical methods. The contributions of other tangential vorticity transport terms are also considered. It is shown that the stable LEV region coincides mostly with a constant ratio of tangential and radial vorticity components. The DS-VT$_{r-t}$ mechanism functions as a negative feedback loop for radial vorticity, thereby contributing to the LEV stability at $\textit {Re} > 500$. Specifically, this mechanism involves a dual-stage vortex tilting starting from negative radial component to positive tangential component, and then back to positive radial component, thereby leading to a $180^{\circ }$ reversal of radial vorticity. The radial Coriolis acceleration can also assist the DS-VT$_{r-t}$ by enhancing the tangential vorticity component and the reduction of radial vorticity inside the LEV via the second stage of DS-VT$_{r-t}$. The effects of $\textit {Re}$, AR and Ro on the constant radial–tangential vorticity ratio and DS-VT$_{r-t}$ are then analysed. The coupled effects of AR and Ro are separated into rotational effects and those of tip and root vortices. Our results establish an evident relationship among the LEV stability, the constant radial–tangential vorticity ratio, and the DS-VT$_{r-t}$, thereby deepening the understanding in the vorticity transport of LEV formation and stability.

People tend to prefer smaller and sooner (SS) rewards over larger and later (LL) ones even when the latter are much larger. Previous research have identified several ways to enhance people’s patience. Adding to this literature, the current paper demonstrates that introduction of upfront losses as well as gains to both SS and LL rewards can decrease people’s impatience. This effect is incompatible with both the normative exponential and descriptive hyperbolic discounting models, which agree on the additive assumption and the independence assumption. We also exculde the integration explanation which assumes subjects integrate upfront money with final rewards and make a decision with bottom line at the end. We consider several possible explanations, including the salience hypothesis, which states that introducing upfront money makes the money dimension more salient than not and thus increases the attractiveness of LL options.

Recently, Scholten and Read (2014) found new violations of dominance in intertemporal choice. Although adding a small receipt before a delayed payment or adding a small delayed receipt after an immediate receipt makes the prospect objectively better, it decreases the preference for that prospect (better is worse). Conversely, although adding a small payment before a delayed receipt or adding a small delayed payment after an immediate payment makes the prospect objectively worse, it increases the preference for that prospect (worse is better). Scholten and Read explained these violations in terms of a preference for improvement. However, to produce violations such as these, we find that the temporal sequences need not be constructed as Scholten and Read suggested. In this study, adding a small receipt before a dated receipt (thus constructed as improving) or adding a receipt after a dated payment (thus constructed as improving) decreases preferences for those prospects. Conversely, adding a small payment after a dated receipt (thus constructed as deteriorating) or adding a small payment before a delayed payment (thus constructed as deteriorating) increases preferences for those prospects.

Recognition of obstacle type based on visual sensors is important for navigation by unmanned surface vehicles (USV), including path planning, obstacle avoidance, and reactive control. Conventional detection techniques may fail to distinguish obstacles that are similar in visual appearance in a cluttered environment. This work proposes a novel obstacle type recognition approach that combines a dilated operator with the deep-level features map of ResNet50 for autonomous navigation. First, visual images are collected and annotated from various different scenarios for USV test navigation. Second, the deep learning model, based on a dilated convolutional neural network, is set and trained. Dilated convolution allows the whole network to learn deep features with increased receptive field and further improves the performance of obstacle type recognition. Third, a series of evaluation parameters are utilised to evaluate the obtained model, such as the mean average precision (mAP), missing rate and detection speed. Finally, some experiments are designed to verify the accuracy of the proposed approach using visual images in a cluttered environment. Experimental results demonstrate that the dilated convolutional neural network obtains better recognition performance than the other methods, with an mAP of 88%.

The mechanisms of leading-edge vortex (LEV) formation and its stable attachment to revolving wings depend highly on Reynolds number ($\textit {Re}$). In this study, using numerical methods, we examined the $\textit {Re}$ dependence of LEV formation dynamics and stability on revolving wings with $\textit {Re}$ ranging from 10 to 5000. Our results show that the duration of the LEV formation period and its steady-state intensity both reduce significantly as $\textit {Re}$ decreases from 1000 to 10. Moreover, the primary mechanisms contributing to LEV stability can vary at different $\textit {Re}$ levels. At $\textit {Re} <200$, the LEV stability is mainly driven by viscous diffusion. At $200<\textit {Re} <1000$, the LEV is maintained by two distinct vortex-tilting-based mechanisms, i.e. the planetary vorticity tilting and the radial–tangential vorticity balance. At $\textit {Re}>1000$, the radial–tangential vorticity balance becomes the primary contributor to LEV stability, in addition to secondary contributions from tip-ward vorticity convection, vortex compression and planetary vorticity tilting. It is further shown that the regions of tip-ward vorticity convection and tip-ward pressure gradient almost overlap at high $\textit {Re}$. In addition, the contribution of planetary vorticity tilting in LEV stability is $\textit {Re}$-independent. This work provides novel insights into the various mechanisms, in particular those of vortex tilting, in driving the LEV formation and stability on low-$\textit {Re}$ revolving wings.

As the corona virus disease 2019 (COVID-19) pandemic continues around the world, understanding the transmission characteristics of COVID-19 is vital for prevention and control. We conducted the first study aiming to estimate and compare the relative risk of secondary attack rates (SARs) of COVID-19 in different contact environments. Until 26 July 2021, epidemiological studies and cluster epidemic reports of COVID-19 were retrieved from SCI, Embase, PubMed, CNKI, Wanfang and CBM in English and Chinese, respectively. Relative risks (RRs) were estimated in pairwise comparisons of SARs between different contact environments using the frequentist NMA framework, and the ranking of risks in these environments was calculated using the surface under the cumulative ranking curve (SUCRA). Subgroup analysis was performed by regions. Thirty-two studies with 68 260 participants were identified. Compared with meal or gathering, transportation (RR 10.55, 95% confidence interval (CI) 1.43–77.85), medical care (RR 11.68, 95% CI 1.58–86.61) and work or study places (RR 10.15, 95% CI 1.40–73.38) had lower risk ratios for SARs. Overall, the SUCRA rankings from the highest to the lowest were household (95.3%), meal or gathering (81.4%), public places (58.9%), daily conversation (50.1%), transportation (30.8%), medical care (18.2%) and work or study places (15.3%). Household SARs were significantly higher than other environments in the subgroup of mainland China and sensitive analysis without small sample studies (<100). In light of the risks, stratified personal protection and public health measures need to be in place accordingly, so as close contacts categorising and management.

DNA methylation is one of the most important epigenetic modifications in breast cancer (BC) development, and long-term dietary habits can alter DNA methylation. Cadherin-4 (CDH4, a member of the cadherin family) encodes Ca2+-dependent cell–cell adhesion glycoproteins. We conducted a case–control study (380 newly diagnosed BC and 439 cancer-free controls) to explore the relationship of CDH4 methylation in peripheral blood leukocyte DNA (PBL DNA), as well as its combined and interactive effects with dietary factors on BC risk. A case-only study (335 newly diagnosed BC) was conducted to analyse the association between CDH4 methylation in breast tissue DNA and dietary factors. CDH4 methylation was detected using quantitative methylation-specific PCR. Unconditional logistic regressions were used to analyse the association of CDH4 methylation in PBL DNA and BC risk. Cross-over analysis and unconditional logistic regression were used to calculate the combined and interactive effects between CDH4 methylation in PBL DNA and dietary factors in BC. CDH4 hypermethylation was significantly associated with increased BC risk in PBL DNA (ORadjusted (ORadj) = 2·70, (95 % CI 1·90, 3·83), P < 0·001). CDH4 hypermethylation also showed significant combined effects with the consumption of vegetables (ORadj = 4·33, (95 % CI 2·63, 7·10)), allium vegetables (ORadj = 7·00, (95 % CI 4·17, 11·77)), fish (ORadj = 7·92, (95 % CI 3·79, 16·53)), milk (ORadj = 6·30, (95 % CI 3·41, 11·66)), overnight food (ORadj = 4·63, (95 % CI 2·69, 7·99)), pork (ORadj = 5·59, (95 % CI 2·94, 10·62)) and physical activity (ORadj = 4·72, (95 % CI 2·87, 7·76)). Moreover, consuming milk was significantly related with decreased risk of CDH4 methylation (OR = 0·61, (95 % CI 0·38, 0·99)) in breast tissue. Our findings may provide direct guidance on the dietary intake for specific methylated carriers to decrease their risk for developing BC.

The current epidemic of type 2 diabetes mellitus (T2DM) significantly affects human health worldwide. Activation of brown adipocytes and browning of white adipocytes are considered as a promising molecular target for T2DM treatment. Mulberry leaf, a traditional Chinese medicine, has been demonstrated to have multi-biological activities, including anti-diabetic and anti-inflammatory effects. Our experimental results showed that mulberry leaf significantly alleviated the disorder of glucose and lipid metabolism in T2DM rats. In addition, mulberry leaf induced browning of inguinal white adipose tissue (IWAT) by enhancing the expressions of brown-mark genes as well as beige-specific genes, including uncoupling protein-1 (UCP1), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α), peroxisome proliferator-activated receptor alpha (PPARα), PRD1-BF-1-RIZ1 homologous domain containing protein 16 (PRDM16), cell death inducing DFFA-like effector A (Cidea), CD137 and transmembrane protein 26 (TMEM26). Mulberry leaf also activated brown adipose tissue (BAT) by increasing the expressions of brown-mark genes including UCP1, PGC-1α, PPARα, PRDM16 and Cidea. Moreover, mulberry leaf enhanced the expression of nuclear respiratory factor 1 (NRF-1) and mitochondrial transcription factor A (TFAM) genes that are responsible for mitochondrial biogenesis in IWAT and BAT. Importantly, mulberry leaf also increased the expression of UCP1 and carnitine palmitoyl transferase 1 (CPT-1) proteins in both IWAT and BAT via a mechanism involving AMP-activated protein kinase (AMPK) and PGC-1α pathway. In conclusion, our findings identify the role of mulberry leaf in inducing adipose browning, indicating that mulberry leaf may be used as a candidate browning agent for the treatment of T2DM.

The cost of recruitment and training of newcomers can be a burden for enterprises, causing adverse effects on human resources management. Although much research has addressed employee turnover, less attention has been paid to methods of improving the retention of new hires. This study is an empirical examination of the increase in predictive strength of antecedents of affective commitment for comparing newcomers’ workplace spirituality. The results of an employee survey completed by 237 newcomers with under two years of work experience indicate that socialization tactics have a direct impact on job embeddedness, which in turn has a direct effect on affective commitment. Workplace spirituality has a significant moderating effect on the relationship between socialization tactics and job embeddedness. Also, workplace spirituality has a significant moderating effect on the relationship between job embeddedness and affective commitment.

The global dairy sector is facing the challenge of reducing greenhouse gas (GHG) emissions whilst increasing productivity to feed a growing population. Despite the importance of this challenge, many developing countries do not have the required resources, specifically funding, expertise and facilities, for quantifying GHG emissions from dairy production and research. This paper aims to address this challenge by discussing the magnitude of the issue, potential mitigation approaches and benefits in quantifying GHG emissions in a developing country context. Further, the paper explores the opportunities for developing country dairy scientists to leverage resources from developed countries, such as using existing relevant GHG emission estimation models. It is clear that further research is required to support developing countries to quantify and understand GHG emissions from dairy production, as it brings significant benefits including helping to identify and implement appropriate mitigation strategies for local production systems, trading carbon credits and achieving the nationally determined contribution obligations of the Paris Agreement.

Studies have suggested an association between metabolic and cerebrocardiovascular diseases and major depressive disorder (MDD). However, the risk of metabolic and cerebrocardiovascular diseases in the unaffected siblings of patients with MDD remains uncertain. Using the Taiwan National Health Insurance Research Database, 22,438 unaffected siblings of patients with MDD and 89,752 age-/sex-matched controls were selected and followed up from 1996 to the end of 2011. Individuals who developed metabolic and cerebrocardiovascular diseases during the follow-up period were identified. Compared with the controls, the unaffected siblings of patients with MDD had a higher prevalence of metabolic diseases, such as hypertension (5.0% vs. 4.5%, p = 0.007), dyslipidemia (5.6% vs. 4.8%, p < 0.001), and obesity (1.7% vs. 1.5%, p = 0.028), and cerebrocardiovascular diseases, such as ischemic stroke (0.6% vs. 0.4%, p < 0.005) and ischemic heart disease (2.1% vs. 1.7%, p < 0.001). Logistic regression analyses revealed that the unaffected siblings of patients with MDD were more likely to develop hypertension, dyslipidemia, ischemic stroke, and ischemic heart diseases during the follow-up period than the controls. Our study revealed a familial coaggregation between MDD and metabolic and cerebrocardiovascular diseases. Additional studies are required to investigate the shared pathophysiology of MDD and metabolic and cerebrocardiovascular diseases.

The COVID-19 outbreak is ongoing in China. Here, Boltzmann function-based analyses reveal the potential total numbers of COVID-19 deaths: 3,260 (95% confidence interval [CI], 3187–3394) in China; 110 (95% CI, 109–112) in Hubei Province; 3,174 (95% CI, 3095–3270) outside Hubei; 2,550 (95% CI, 2494–2621) in Wuhan City; and 617 (95% CI, 607–632) outside Wuhan.

Recent technological advances have led to unprecedented amounts of generated data that originate from the Web, sensor networks, and social media. Analytics in terms of defeasible reasoning – for example, for decision making – could provide richer knowledge of the underlying domain. Traditionally, defeasible reasoning has focused on complex knowledge structures over small to medium amounts of data, but recent research efforts have attempted to parallelize the reasoning process over theories with large numbers of facts. Such work has shown that traditional defeasible logics come with overheads that limit scalability. In this work, we design a new logic for defeasible reasoning, thus ensuring scalability by design. We establish several properties of the logic, including its relation to existing defeasible logics. Our experimental results indicate that our approach is indeed scalable and defeasible reasoning can be applied to billions of facts.

This research communication describes associations between variation in the fatty acid binding protein 4 gene (FABP4) and milk fat composition in New Zealand Holstein-Friesian × Jersey cross dairy cows. After correcting for the effect of the amino acid substitution p.K232A in diacylglycerol O-acyltransferase 1 (DGAT1), which is associated with variation in many milk fatty acid (FA) component levels, the effect of FABP4 c.328A/G on milk FA levels was typically small. For the five genotypes analysed, the AB cows produced more medium-chain fatty acids than CC cows (P < 0.05), and more C14:0 FA than AA and AC cows (P < 0.05). The AA and AC cows produced less C22:0 FA (P < 0.01) than the BC cows, and the AC cows produced more C24:0 FA (P < 0.05) than was produced by the BC cows. Cows of genotype CC produce more long-chain fatty acids than cows of genotype BC (P < 0.05).