The sedimentary characteristics and preservation potential of lacustrine carbonates provide fundamental information on climate change. The lacustrine carbonate deposition in the Eocene Dongying Depression was investigated using a combination of mineralogical, petrological and geochemical analyses. Micritic calcite/dolomite, granular calcite, columnar calcite, calcareous shell fragments and reworked detrital calcite were identified. Varying patterns of carbonates (VPC) including lithofacies, geochemical indicators and carbonate distribution were revealed in the Dongying Depression: (i) carbonates hardly precipitate in the nearshore area (average 12 wt %); (ii) carbonate content is high (average 53 wt %) in the shallow lake and (iii) gradually decreases to reach a minimum (average 24 wt %) in the deeper part of the lake. Comparison of VPC in four Holocene lakes (the Qinghai Lake and Barkol Lake in China, Oro Lake in Canada and Montcortès Lake in Spain) with the Dongying Depression suggests that four distinct lake stages were developed, namely the terrigenous clastic/gypsum-rich, carbonate-rich, carbonate-decreasing and carbonate-poor stages. A depositional model of lacustrine carbonates influenced by detrital influx, climate, palaeoproductivity and salinity is developed. This study contributes to the understanding of the genetic mechanisms of lacustrine carbonate deposition to reconstruct environmental changes.

Listeriosis is a rare but serious foodborne disease caused by Listeria monocytogenes. This matched case–control study (1:1 ratio) aimed to identify the risk factors associated with food consumption and food-handling habits for the occurrence of sporadic listeriosis in Beijing, China. Cases were defined as patients from whom Listeria was isolated, in addition to the presence of symptoms, including fever, bacteraemia, sepsis and other clinical manifestations corresponding to listeriosis, which were reported via the Beijing Foodborne Disease Surveillance System. Basic patient information and possible risk factors associated with food consumption and food-handling habits were collected through face-to-face interviews. One hundred and six cases were enrolled from 1 January 2018 to 31 December 2020, including 52 perinatal cases and 54 non-perinatal cases. In the non-perinatal group, the consumption of Chinese cold dishes increased the risk of infection by 3.43-fold (95% confidence interval 1.27–9.25, χ2 = 5.92, P = 0.02). In the perinatal group, the risk of infection reduced by 95.2% when raw and cooked foods were well-separated (χ2 = 5.11, P = 0.02). These findings provide important scientific evidence for preventing infection by L. monocytogenes and improving the dissemination of advice regarding food safety for vulnerable populations.

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.

The most important issue for the clinical application of sarcopenic obesity (SO) is the lack of a consensus definition. The aim of the present study was to determine the best measurement for SO by estimating the association between various definitions and the risk of falls and metabolic syndrome (MS). We studied a community of 765 adults aged 65 years and older in 2015–2017. Sarcopenia obesity was measured by sarcopenia (defined by low muscle mass with either low handgrip strength or low gait speed or both) plus obesity (defined by waist circumference, body fat percentage and BMI). The MS was defined according to the National Cholesterol Education Program ATP III. Logistic regression models were constructed to examine the relationships between sarcopenia obesity and risk of fall and MS. In the analysis of the fall risk with SO defined by waist circumference, the participants with non-sarcopenia/non-obesity were treated as the reference group. The OR to fall in participants with SO was 10·16 (95 % CI 2·71, 38·13) after adjusting for confounding covariates. In the analysis of the risk of the MS between participants with individual components of sarcopenia coupled with obesity defined by waist circumference, the risk was statistically significant for low gait speed (OR: 7·19; 95 % CI 3·61, 14·30) and low grip strength (OR: 9·19; 95 % CI 5·00, 16·91). A combination of low grip strength and abdominal obesity for identifying SO may be a more precise and practical method for predicting target populations with unfavourable health risks, such as falls risk and MS.

Hypertension represents one of the most common pre-existing conditions and comorbidities in Coronavirus disease 2019 (COVID-19) patients. To explore whether hypertension serves as a risk factor for disease severity, a multi-centre, retrospective study was conducted in COVID-19 patients. A total of 498 consecutively hospitalised patients with lab-confirmed COVID-19 in China were enrolled in this cohort. Using logistic regression, we assessed the association between hypertension and the likelihood of severe illness with adjustment for confounders. We observed that more than 16% of the enrolled patients exhibited pre-existing hypertension on admission. More severe COVID-19 cases occurred in individuals with hypertension than those without hypertension (21% vs. 10%, P = 0.007). Hypertension associated with the increased risk of severe illness, which was not modified by other demographic factors, such as age, sex, hospital geological location and blood pressure levels on admission. More attention and treatment should be offered to patients with underlying hypertension, who usually are older, have more comorbidities and more susceptible to cardiac complications.

Rare earth elements (REE) in marine minerals have been widely used as proxies for the redox status of depositional and/or diagenetic environments. Phosphate nodules, which are thought to grow within decimetres below the sediment–water interface and to be able to scavenge REE from the ambient pore water, are potential archives of subtle changes in REE compositions. Whether their REE signals represent specific redox conditions or they can be used to track the overlying water chemistry is worth exploring. Through in situ laser ablation – inductively coupled plasma – mass spectrometry (LA-ICP-MS), we investigate the REE compositions of a drill-core-preserved phosphate nodule from the lower Cambrian Niutitang Formation in the Daotuo area, northeastern Guizhou Province, South China. REE distributions of the nodule show concentric layers with systematic decreases in Ce anomalies (Ce/Ce*) from the core to the rim. The lowest Ce/Ce* appears in the outer rim where REE concentrations are relatively high. These results are interpreted to reflect REE exchange with pore water at a very early stage or bathymetric variation during apatite precipitation. The origin of the shale-normalized middle REE (MREE) enrichment in our sample is less constrained. Possible driving factors include preferential MREE substitution for Ca in the apatite lattice, degradation of organic matter and deposition beneath a ferruginous zone. Although speculative, the last possibility is consistent with the chemically stratified model for early Cambrian oceans, in which dynamic fluctuations of the chemocline provided an ideal depositional context for phosphogenesis.

Witherite originates from the biochemical sedimentation of barium in sea water. Due to the complexity of the metallogenic environment, witherite appears in many morphologies. However, the relationship between its diverse morphologies and its mineralisation environment is not well understood. In this paper, Ca2+, a common substitute for Ba2+, and mixed protein (egg white) were used to simulate the inorganic and organic environments of witherite mineralisation, respectively. Comparison of samples prepared under different conditions showed that Ca2+ and egg white have relatively independent regulatory effects on the mineralisation of witherite particles. Egg white primarily limits the growth of the nanocrystals, while Ca2+ directs their non-isodiametric growth. Results shows that Ca2+ is distributed along a gradient in nanocrystalline witherite particles, with the Ca2+ content being proportional to the diameter of the nanocrystals. The results of this study shed light on the different roles of organic matter and inorganic ions in the formation of witherite and offer insight into the genesis of its various morphologies.

The sedimentologic fingerprinting in detrital deposit is vital to reconstruct sedimentary environments and discriminate sources. In this study, grain size and microtextural characteristics of quartz from the late Pleistocene hard clay in the Yangtze River delta (YRD) were analyzed by using a laser particle size analyzer and a scanning electron microscope. Subaqueous quartz from the Yangtze River and Yellow River sediments and eolian quartz from the Chinese Loess Plateau loess were also analyzed by scanning electron microscopy to obtain the microtextural characteristics. Quartz grains of the hard clay were characterized by poor sorting, fine skew, bimodal grain-size distributions, and numerous eolian microtextures. The comparison of the quartz grain characteristics of the hard clay with these in eolian loess indicated that the hard clay belonged to an eolian deposition. Moreover, the fine quartz grains of the hard clay were dominated by eolian microtextural characteristics, representing long-distance transportation. The coarse quartz grains of the hard clay exhibited more subaqueous microtextural characteristics, which indicated that the coarse fraction of the hard clay was derived from the proximal source regions in the YRD. The determination of buried eolian deposition with multiple sources in the YRD implies a southward westerly jet stream, strengthened eolian dust transportation, and extensive aridification in the YRD due to the increased Northern Hemisphere ice sheets in Marine Oxygen Isotope Stage 2.

Generating designs via machine learning has been an on-going challenge in computer-aided design. Recently, deep learning methods have been applied to randomly generate images in fashion, furniture and product design. However, such deep generative methods usually require a large number of training images and human aspects are not taken into account in the design process. In this work, we seek a way to involve human cognitive factors through brain activity indicated by electroencephalographic measurements (EEG) in the generative process. We propose a neuroscience-inspired design with a machine learning method where EEG is used to capture preferred design features. Such signals are used as a condition in generative adversarial networks (GAN). First, we employ a recurrent neural network Long Short-Term Memory as an encoder to extract EEG features from raw EEG signals; this data are recorded from subjects viewing several categories of images from ImageNet. Second, we train a GAN model conditioned on the encoded EEG features to generate design images. Third, we use the model to generate design images from a subject’s EEG measured brain activity. To verify our proposed generative design method, we present a case study, in which the subjects imagine the products they prefer, and the corresponding EEG signals are recorded and reconstructed by our model for evaluation. The results indicate that a generated product image with preference EEG signals gains more preference than those generated without EEG signals. Overall, we propose a neuroscience-inspired artificial intelligence design method for generating a design taking into account human preference. The method could help improve communication between designers and clients where clients might not be able to express design requests clearly.

Maternal supraphysiological estradiol (E2) environment during pregnancy leads to adverse perinatal outcomes. However, the influence of oocyte exposure to high E2 levels on perinatal outcomes remains unknown. Thus, a retrospective cohort study was conducted to explore the effect of high E2 level induced by controlled ovarian stimulation (COH) on further outcomes after frozen embryo transfer (FET). The study included all FET cycles (n = 10,581) between 2014 and 2017. All cycles were categorized into three groups according to the E2 level on the day of the human Chorionic Gonadotropin trigger. Odds ratios (ORs) and their confidence intervals (CIs) were calculated to evaluate the association between E2 level during COH and pregnancy outcomes and subsequent neonatal outcomes. From our findings, higher E2 level was associated with lower percentage of chemical pregnancy, clinical pregnancy, ongoing pregnancy, and live birth as well as increased frequency of early miscarriage. Preterm births were more common among singletons in women with higher E2 level during COH (aOR1 = 1.93, 95% CI: 1.22–3.06; aOR2 = 2.05, 95% CI: 1.33–3.06). Incidence of small for gestational age (SGA) was more common in both singletons (aOR1 = 2.01, 95% CI: 1.30–3.11; aOR2 = 2.51, 95% CI: 1.69–3.74) and multiples (aOR1 = 1.58, 95% CI: 1.03–2.45; aOR2 = 1.99, 95% CI: 1.05–3.84) among women with relatively higher E2 level. No association was found between high E2 level during COH and the percentage of macrosomia or large for gestational age. In summary, oocyte exposure to high E2 level during COH should be brought to our attention, since the pregnancy rate decreasing and the risk of preterm birth and SGA increasing following FET.

Wire-shaped supercapacitors (WSSCs) hold great promise in portable and wearable electronics. Herein, a novel kind of high-performance coaxial WSSCs has been demonstrated and realized by scrolling porous carbon dodecahedrons/Al foil film electrode on vertical FeOOH nanosheets wrapping carbon fiber tows (FeOOH NSs/CFTs) yarn electrode. Remarkably, ionogel is utilized as solid-state electrolyte and exhibits a high thermal/electrochemical stability, which effectively ensures the great reliability and high operating voltage of coaxial WSSCs. Benefiting from the intriguing configuration, the coaxial WSSCs with superior flexibility act as efficient energy storage devices and exhibit low resistance, high volumetric energy density (3.2 mW h/cm3), and strong durability (82% after 10,000 cycles). Importantly, the coaxial WSSCs can be effectively recharged by harvesting sustainable wind source and repeatedly supply power to the lamp without a decline of electrochemical performance. Considering the facile fabrication technology with an outstanding performance, this work has paved the way for the integration of sustainable energy harvesting and wearable energy storage units.

Deep learning methods have been applied to randomly generate images, such as in fashion, furniture design. To date, consideration of human aspects which play a vital role in a design process has not been given significant attention in deep learning approaches. In this paper, results are reported from a human- in-the-loop design method where brain EEG signals are used to capture preferable design features. In the framework developed, an encoder extracting EEG features from raw signals recorded from subjects when viewing images from ImageNet are learned. Secondly, a GAN model is trained conditioned on the encoded EEG features to generate design images. Thirdly, the trained model is used to generate design images from a person's EEG measured brain activity in the cognitive process of thinking about a design. To verify the proposed method, a case study is presented following the proposed approach. The results indicate that the method can generate preferred designs styles guided by the preference related brain signals. In addition, this method could also help improve communication between designers and clients where clients might not be able to express design requests clearly.