The ubiquitous marine radiocarbon reservoir effect (MRE) constrains the construction of reliable chronologies for marine sediments and the further comparison of paleoclimate records. Different reference values were suggested from various archives. However, it remains unclear how climate and MREs interact. Here we studied two pre-bomb corals from the Hainan Island and Xisha Island in the northern South China Sea (SCS), to examine the relationship between MRE and regional climate change. We find that the MRE from east of Hainan Island is mainly modulated by the Southern Asian Summer Monsoon-induced precipitation (with 11.4% contributed to seawater), rather than wind induced upwelling. In contrast, in the relatively open seawater of Xisha Island, the MRE is dominated by the East Asian Winter Monsoon, with relatively more negative (lower) ΔR values associated with high wind speeds, implying horizontal transport of seawater. The average SCS ΔR value relative to the Marine20 curve is –161±39 14C years. Our finding highlights the essential role of monsoon in regulating the MRE in the northern SCS, in particularly the tight bond between east Asian winter monsoon and regional MRE.

Nonlinear compression experiments based on multiple solid thin plates are conducted in an ultra-high peak power Ti:sapphire laser system. The incident laser pulse, with an energy of 80 mJ and a pulse width of 30.2 fs, is compressed to 10.1 fs by a thin-plate based nonlinear compression. Significant small-scale self-focusing is observed as ring structures appear in the near-field of the output pulse at high energy. Numerical simulations based on the experimental setup provide a good explanation for the observed phenomena, offering quantitative predictions of the spectrum, pulse width, dispersion and near- and far-field distributions of the compressed laser pulse.

MicroRNAs (miRNAs) play important roles in regulating salt tolerance in Dongxiang wild rice (DXWR, Oryza rufipogon Griff.). The development of salt-responsive miRNA-simple sequence repeat (SSR) markers will significantly bolster research on DXWR, providing novel tools for exploring salt-tolerant genetic resources and advancing the development of salt-tolerant rice varieties. In the present study, a total of 137 miRNA-SSR markers were successfully developed, specifically derived from miRNAs responsive to salt stress in DXWR. Subsequently, a subset of 20 markers was randomly selected for validation across three distinct DXWR populations, along with 35 modern rice varieties. Notably, 13 of these markers exhibited remarkable polymorphism. The polymorphic markers collectively amplified 52 SSR loci, averaging four alleles per locus. The polymorphism information content values associated with these loci spanned from 0.23 to 0.70, with a mean value of 0.49. Particularly noteworthy is the miR162a-SSR marker, which demonstrated distinct allelic patterns and holds potential as a diagnostic marker for discriminating the salt-tolerant rice varieties from the non-tolerant varieties. This study provides a valuable tool for genetic analysis and precision breeding, facilitating the identification and utilization of valuable salt-tolerant genetic resources.

Immunity activation and inflammation are the main characteristics of rheumatoid arthritis and clonal hematopoiesis. However, it remains unclear whether rheumatoid arthritis increase the risk of clonal hematopoiesis. Here, a Mendelian randomization (MR) analysis was conduct to explore the causal effects of rheumatoid arthritis on clonal hematopoiesis. Summary statistics data of rheumatoid arthritis (13,838 cases and 33,742 controls) and clonal hematopoiesis (10,203 cases and 173,918 controls) derived from a genomewide association study were selected to analyze. We selected inverse-variance weighted, MR-Egger, weighted median, simple mode, and weighted mode to evaluate the causal effect of rheumatoid arthritis on clonal hematopoiesis. The two-sample MR analysis suggested a strong causal relationship between rheumatoid arthritis and clonal hematopoiesis by inverse-variance weighted (OR = 1.002311673, 95% CI [1.000110757, 1.004517433], p = .039706) and weighted median (OR = 1.002311673, 95% CI [1.000110757, 1.004517433], p = .039518447) methods. No significant pleiotropy or heterogeneity was found in the sensitivity analysis. These results supported a potentially causal relationship between rheumatoid arthritis and clonal hematopoiesis, and the exposure of rheumatoid arthritis increased the risks of clonal hematopoiesis. Our findings highlight the importance of how chronic inflammation and immune activation induced rheumatoid arthritis enhances the risks of clonal hematopoiesis, and that early intervention with rheumatoid arthritis patients might reduce the clonal hematopoiesis risks in rheumatoid arthritis patients. Moreover, our study provides clues for prediction of risk factors and potential mechanisms of clonal hematopoiesis.

In preparation for an experiment with a laser-generated intense proton beam at the Laser Fusion Research Center at Mianyang to investigate the 11B(p,α)2α reaction, we performed a measurement at very low proton energy between 140 keV and 172 keV using the high-voltage platform at the Institute of Modern Physics, Lanzhou. The aim of the experiment was to test the ability to use CR-39 track detectors for cross-section measurements and to remeasure the cross-section of this reaction close to the first resonance using the thick target approach. We obtained the cross-section σ = 45.6 ± 12.5 mb near 156 keV. Our result confirms the feasibility of CR-39 type track detector for nuclear reaction measurement also in low-energy regions.

Energy loss of protons with 90 and 100 keV energies penetrating through a hydrogen plasma target has been measured, where the electron density of the plasma is about 1016 cm−3 and the electron temperature is about 1-2 eV. It is found that the energy loss of protons in the plasma is obviously larger than that in cold gas and the experimental results based on the Bethe model calculations can be demonstrated by the variation of effective charge of protons in the hydrogen plasma. The effective charge remains 1 for 100 keV protons, while the value for 90 keV protons decreases to be about 0.92. Moreover, two empirical formulae are employed to extract the effective charge.

Fast neutron absorption spectroscopy is widely used in the study of nuclear structure and element analysis. However, due to the traditional neutron source pulse duration being of the order of nanoseconds, it is difficult to obtain a high-resolution absorption spectrum. Thus, we present a method of ultrahigh energy-resolution absorption spectroscopy via a high repetition rate, picosecond duration pulsed neutron source driven by a terawatt laser. The technology of single neutron count is used, which results in easily distinguishing the width of approximately 20 keV at 2 MeV and an asymmetric shape of the neutron absorption peak. The absorption spectroscopy based on a laser neutron source has one order of magnitude higher energy-resolution power than the state-of-the-art traditional neutron sources, which could be of benefit for precisely measuring nuclear structure data.

Reward processing dysfunctions are considered a candidate mechanism underlying anhedonia and apathy in depression. Neuroimaging studies have documented that neurofunctional alterations in mesocorticolimbic circuits may neurally mediate these dysfunctions. However, common and distinct neurofunctional alterations during motivational and hedonic evaluation of monetary and natural rewards in depression have not been systematically examined. Here, we capitalized on pre-registered neuroimaging meta-analyses to (1) establish general reward-related neural alterations in depression, (2) determine common and distinct alterations during the receipt and anticipation of monetary v. natural rewards, and, (3) characterize the differences on the behavioral, network, and molecular level. The pre-registered meta-analysis (https://osf.io/ay3r9) included 633 depressed patients and 644 healthy controls and revealed generally decreased subgenual anterior cingulate cortex and striatal reactivity toward rewards in depression. Subsequent comparative analyses indicated that monetary rewards led to decreased hedonic reactivity in the right ventral caudate while natural rewards led to decreased reactivity in the bilateral putamen in depressed individuals. These regions exhibited distinguishable profiles on the behavioral, network, and molecular level. Further analyses demonstrated that the right thalamus and left putamen showed decreased activation during the anticipation of monetary reward. The present results indicate that distinguishable neurofunctional alterations may neurally mediate reward-processing alterations in depression, in particular, with respect to monetary and natural rewards. Given that natural rewards prevail in everyday life, our findings suggest that reward-type specific interventions are warranted and challenge the generalizability of experimental tasks employing monetary incentives to capture reward dysregulations in everyday life.

This study investigates the linear instability of a thin-film coating inside a rigid tube. The flow is assumed to be inertialess and driven by an axial body force (e.g. gravity), an interfacial shearing force, or their combinations. The interface and the bulk of the film are laden with soluble surfactant. The properties of the soluble surfactant, i.e. solubility, sorption kinetics and bulk diffusivity, modulate the interfacial dynamics of the film. The influence of these properties on the linear instability of the film is comprehensively investigated via long-wave approximation analysis and numerical calculation. Two modes, namely the interface mode and the surfactant mode, are identified to dominate the instability. For a quiescent film, it is found that solubility, sorption kinetics and bulk diffusivity act to improve the uniformity of the surface surfactant and mitigate the stabilizing effect of the Marangoni force. For the film driven by the axial body/interfacial shearing force, the results reveal that solubility plays contrasting roles in the interface mode and the surfactant mode. A window with intermediate solubility is detected where the film can be linearly stabilized. Moreover, sorption kinetics is found to destabilize the perturbations with long wavelength whereas it stabilizes the perturbations with finite wavelength. The bulk diffusivity of the surfactant has a non-monotonic influence on the flow instability, and the film can be relatively stable at both strong and weak diffusivity.

To develop a machine learning model and nomogram to predict the probability of persistent virus shedding (PVS) in hospitalized patients with coronavirus disease 2019 (COVID-19), the clinical symptoms and signs, laboratory parameters, cytokines, and immune cell data of 429 patients with nonsevere COVID-19 were retrospectively reviewed. Two models were developed using the Akaike information criterion (AIC). The performance of these two models was analyzed and compared by the receiver operating characteristic (ROC) curve, calibration curve, net reclassification index (NRI), and integrated discrimination improvement (IDI). The final model included the following independent predictors of PVS: sex, C-reactive protein (CRP) level, interleukin-6 (IL-6) level, the neutrophil-lymphocyte ratio (NLR), monocyte count (MC), albumin (ALB) level, and serum potassium level. The model performed well in both the internal validation (corrected C-statistic = 0.748, corrected Brier score = 0.201) and external validation datasets (corrected C-statistic = 0.793, corrected Brier score = 0.190). The internal calibration was very good (corrected slope = 0.910). The model developed in this study showed high discriminant performance in predicting PVS in nonsevere COVID-19 patients. Because of the availability and accessibility of the model, the nomogram designed in this study could provide a useful prognostic tool for clinicians and medical decision-makers.

In this study, the length scaling for the boundary layer separation induced by two incident shock waves is experimentally and analytically investigated. The experiments are performed in a Mach 2.73 flow. A double-wedge shock generator with two deflection angles ($\alpha _1$ and $\alpha _2$) is employed to generate two incident shock waves. Two deflection angle combinations with an identical total deflection angle are adopted: ($\alpha _1 = 7^\circ$, $\alpha _2 = 5^\circ$) and ($\alpha _1 = 5^\circ$, $\alpha _2 = 7^\circ$). For each deflection angle combination, the flow features of the dual-incident shock wave–turbulent boundary layer interactions (dual-ISWTBLIs) under five shock wave distance conditions are examined via schlieren photography, wall-pressure measurements and surface oil-flow visualisation. The experimental results show that the separation point moves downstream with increasing shock wave distance ($d$). For the dual-ISWTBLIs exhibiting a coupling separation state, the upstream interaction length ($L_{int}$) of the separation region approximately linearly decreases with increasing $d$, and the decrease rate of $L_{int}$ with $d$ increases with the second deflection angle under the condition of an identical total deflection angle. Based on control volume analysis of mass and momentum conservations, the relation between $L_{int}$ and $d$ is analytically determined to be approximately linear for the dual-ISWTBLIs with a coupling separation region, and the slope of the linear relation obtained analytically agrees well with that obtained experimentally. Furthermore, a prediction method for $L_{int}$ of the dual-ISWTBLIs with a coupling separation region is proposed, and the relative error of the predicted $L_{int}$ in comparison with the experimental result is $\sim$10 %.

The associations of red/processed meat consumption and cancer-related health outcomes have been well discussed. The umbrella review aimed to summarise the associations of red/processed meat consumption and various non-cancer-related outcomes in humans. We systematically searched the systematic reviews and meta-analyses of associations between red/processed meat intake and health outcomes from PubMed, Embase, Web of Science and the Cochrane Library databases. The umbrella review has been registered in PROSPERO (CRD 42021218568). A total of 40 meta-analyses were included. High consumption of red meat, particularly processed meat, was associated with a higher risk of all-cause mortality, CVD and metabolic outcomes. Dose–response analysis revealed that an additional 100 g/d red meat intake was positively associated with a 17 % increased risk of type 2 diabetes mellitus (T2DM), 15 % increased risk of CHD, 14 % of hypertension and 12 % of stroke. The highest dose–response/50 g increase in processed meat consumption at 95 % confident levels was 1·37, 95 % CI (1·22, 1·55) for T2DM, 1·27, 95 % CI (1·09, 1·49) for CHD, 1·17, 95 % CI (1·02, 1·34) for stroke, 1·15, 95 % CI (1·11, 1·19) for all-cause mortality and 1·08, 95 % CI (1·02, 1·14) for heart failure. In addition, red/processed meat intake was associated with several other health-related outcomes. Red and processed meat consumption seems to be more harmful than beneficial to human health in this umbrella review. It is necessary to take the impacts of red/processed meat consumption on non-cancer-related outcomes into consideration when developing new dietary guidelines, which will be of great public health importance. However, more additional randomised controlled trials are warranted to clarify the causality.

Liriomyza trifolii is a significant pest of vegetable and ornamental crops across the globe. Microwave radiation has been used for controlling pests in stored products; however, there are few reports on the use of microwaves for eradicating agricultural pests such as L. trifolii, and its effects on pests at the molecular level is unclear. In this study, we show that microwave radiation inhibited the emergence of L. trifolii pupae. Transcriptomic studies of L. trifolii indicated significant enrichment of differentially expressed genes (DEGs) in ‘post-translational modification, protein turnover, chaperones’, ‘sensory perception of pain/transcription repressor complex/zinc ion binding’ and ‘insulin signaling pathway’ when analyzed with the Clusters of Orthologous Groups, Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes databases, respectively. The top DEGs were related to reproduction, immunity and development and were significantly expressed after microwave radiation. Interestingly, there was no significant difference in the expression of genes encoding heat shock proteins or antioxidant enzymes in L. trifolii treated with microwave radiation as compared to the untreated control. The expression of DEGs encoding cuticular protein and protein takeout were silenced by RNA interference, and the results showed that knockdown of these two DEGs reduced the survival of L. trifolii exposed to microwave radiation. The results of this study help elucidate the molecular response of L. trifolii exposed to microwave radiation and provide novel ideas for control.

The study investigated the strategies used by Chinese students in inferring meanings of unfamiliar words and the influential factors of successful use of different lexical inferencing strategies. A total of 104 fourth graders inferred 36 unfamiliar semitransparent compound words in three conditions: word in isolation, contextual information only, and both word and context. Results revealed that students were more likely to obtain the correct meaning of words when both morphological information and contextual information were available. The likelihood of using a morpheme-based or context-based lexical inferencing strategy was strongly influenced by the presentation condition of target words and precursors. Students with higher vocabulary knowledge and reading comprehension ability were more sensitive to morphological and contextual information and were able to synthesize multiple sources of information, whereas children with lower vocabulary knowledge and reading comprehension ability showed difficulties in integration and tended to overly rely on morphological information. The findings reveal the interactions between available source information and individual differences in vocabulary knowledge and reading comprehension in predicting lexical inferencing and have implications for vocabulary and reading instruction.

Let $\mathbb {N}$ be the set of all nonnegative integers. For $S\subseteq \mathbb {N}$ and $n\in \mathbb {N}$ , let $R_S(n)$ denote the number of solutions of the equation $n=s_1+s_2$ , $s_1,s_2\in S$ and $s_1<s_2$ . Let A be the set of all nonnegative integers which contain an even number of digits $1$ in their binary representations and $B=\mathbb {N}\setminus A$ . Put $A_l=A\cap [0,2^l-1]$ and $B_l=B\cap [0,2^l-1]$ . We prove that if $C \cup D=[0, m]\setminus \{r\}$ with $0<r<m$ , $C \cap D=\emptyset $ and $0 \in C$ , then $R_{C}(n)=R_{D}(n)$ for any nonnegative integer n if and only if there exists an integer $l \geq 1$ such that $m=2^{l}$ , $r=2^{l-1}$ , $C=A_{l-1} \cup (2^{l-1}+1+B_{l-1})$ and $D=B_{l-1} \cup (2^{l-1}+1+A_{l-1})$ . Kiss and Sándor [‘Partitions of the set of nonnegative integers with the same representation functions’, Discrete Math. 340 (2017), 1154–1161] proved an analogous result when $C\cup D=[0,m]$ , $0\in C$ and $C\cap D=\{r\}$ .

Magnesium ions (Mg2+) are vital for RNA structure and cellular functions. Present efforts in RNA structure determination and understanding of RNA functions are hampered by the inability to accurately locate Mg2+ ions in an RNA. Here we present a machine-learning method, originally developed for computer visual recognition, to predict Mg2+ binding sites in RNA molecules. By incorporating geometrical and electrostatic features of RNA, we capture the key ingredients of Mg2+-RNA interactions, and from deep learning, predict the Mg2+ density distribution. Five-fold cross-validation on a dataset of 177 selected Mg2+-containing structures and comparisons with different methods validate the approach. This new approach predicts Mg2+ binding sites with notably higher accuracy and efficiency. More importantly, saliency analysis for eight different Mg2+ binding motifs indicates that the model can reveal critical coordinating atoms for Mg2+ ions and ion-RNA inner/outer-sphere coordination. Furthermore, implementation of the model uncovers new Mg2+ binding motifs. This new approach may be combined with X-ray crystallography structure determination to pinpoint the metal ion binding sites.