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Poaching is a global issue that threatens many species. However, little research attention has been paid to key life history traits that might help offset some of the worst genetic and demographic impacts of poaching. We investigate the onset of flowering and fecundity in Aquilaria sinensis, an agarwood-producing tree species that faces a constant threat of poaching throughout its native range in southern China. We hypothesise that certain life history traits in this species could buffer genetic erosion associated with selective poaching of larger individuals. We genotyped 1464 individuals using 15 microsatellite markers and examined the difference in genetic diversity between seedlings and adults, as well as that between individuals either side of the threshold diameter at breast height (DBH) size class targeted by poachers. Our study reveals that flowering commences at a DBH of 2.50 cm and that even trees at a DBH of about 6.9 cm invest heavily in seed-set, but that poachers tend to target individuals with a DBH of 15.25 cm or greater. No significant difference in genetic diversity was detected among individuals belonging to seedling and adult life-history stages, or between targeted and non-targeted size classes. The lack of such difference could be explained by certain life history traits which offset some of the most adverse impacts of poaching in Aquilaria sinensis, with important implications for the management and conservation of other species that are threatened by poaching.

The establishment of the Free Trade (Pilot) Zone (FTZ) is a new attempt by China to embark on modern sustainable urban planning and governmental territorial management at the development stage of a high-quality economy. As urban lands serve as the limited resource foundation for civic production and livelihoods, enhancing land use efficiency becomes a key measure to facilitate metropolitan economies of high quality. Utilizing panel data from prefecture-level cities spanning from 2005 to 2021, this study constructs a multi-period difference-in-differences model to explore the impact of FTZs on urban land use efficiency (ULUE). The results indicate that FTZs can significantly enhance urban land use efficiency, with a more pronounced policy effect observed in central cities, inland cities, and cities with higher urbanization rates. Furthermore, the FTZs also demonstrate spatial spillover effects on urban land use efficiency. This study holds great significance for relevant government departments in formulating policies to optimize land resource allocation, promote FTZ development, and foster high-quality urban planning and territorial management.

In this paper, the solid-state shear milling (S3M) strategy featuring a very strong three-dimensional shear stress field was adopted to prepare the high-performance polyoxymethylene (POM)/molybdenum disulfide (MoS2) functional nanocomposite. The transmission electron microscope and Raman measurement results confirmed that the bulk MoS2 particle was successfully exfoliated into few-layer MoS2 nanoplatelets by the above simple S3M physical method. The polarized optical microscope (PLM) observation indicated the pan-milled nanoscale MoS2 particles presented a better dispersion performance in the POM matrix. The results of the tribological test indicated that the incorporation of MoS2 could substantially improve the wear resistance performance of POM. Moreover, the pan-milled exfoliated MoS2 nanosheets could further substantially decrease the friction coefficient of POM. Scanning electron microscope observations on the worn scar revealed the tribological mechanism of the POM/MoS2 nanocomposite prepared by solid-state shear milling. The tensile test results showed that the pan-milled POM/MoS2 nanocomposite has much higher elongation at break than the conventionally melt-compounded material. The solid-state shear milling strategy shows a promising prospect in the preparation of functional nanocomposite with excellent comprehensive performance at a large scale.

Key points Gut microbial biomarkers across Chinese population can be used as a non-invasive tool for the diagnosis of LC and HCC We constructed two RFmodels based on reproducible genera to distinguish LC or HCC from HC The efficacy of two models was greatly improved when clinical factors were added

Trunk borers are among the most destructive forest pests. The larvae of some species living and feeding in the trunk, relying solely on the tree’s appearance to judge infestation is challenging. Currently, one of the most effective methods to detect the larvae of some trunk-boring beetles is by analyzing the vibration signals generated by the larvae while they feed inside the tree trunk. However, this method faces a problem: the field environment is filled with various noises that get collected alongside the vibration signals, thus affecting the accuracy of pest detection. To address this issue, vibration signal enhancement is necessary. Moreover, deploying sophisticated technology in the wild is restricted due to limited hardware resources. In this study, a lightweight vibration signal enhancement was developed using EAB (Emerald Ash Borer) and SCM (Small Carpenter Moth) as insect example. Our model combines CRN (Convolutional Recurrent Network) and Transformer. We use a multi-head mechanism instead of RNN (Recurrent Neural Network) for intra-block processing and retain inter-block RNN. Furthermore, we utilize a dynamic pruning algorithm based on sparsity to further compress the model. As a result, our model achieves excellent enhancement with just 0.34M parameters. We significantly improve the accuracy rate by utilizing the vibration signals enhanced by our model for pest detection. Our results demonstrate that our method achieves superior enhancement performance using fewer computing and storage resources, facilitating more effective use of vibration signals for pest detection.

The larvae of certain wood-boring beetles typically inhabit the interior of trees and feed on the wood, leaving almost no external traces during the early stages of infestation. Acoustic techniques are commonly employed to detect the vibrations produced by these larvae while they feed on wood, significantly increasing detection efficiency compared to traditional methods. However, this method’s accuracy is greatly affected by environmental noise interference. To address the impact of environmental noise, this paper introduces a signal separation system based on a multi-channel attention mechanism. The system utilizes multiple sensors to receive wood-boring vibration signals and employs the attention mechanism to adjust the weights of relevant channels. By utilizing beamforming techniques, the system successfully removes noise from the wood-boring vibration signals and separates the clean wood-boring vibration signals from the noisy ones. The data used in this study were collected from both field and laboratory environments, ensuring the authenticity of the dataset. Experimental results demonstrate that this system can efficiently separate the wood-boring vibration signals from the mixed noisy signals.

Recording vibration signals induced by larvae activity in the trunk has proven to be an efficient method for detecting trunk-boring insects. However, the accuracy of the detection is often limited because the signals collected in real-world environments are heavily disrupted by environmental noises. To deal with this problem, we propose a deep-learning-based model that enhances trunk-boring vibration signals, incorporating an attention mechanism to optimize its performance. The training data utilized in this research consist of the boring vibrations of Agrilus planipennis larvae recorded within trunk sections, as well as various environmental noises that are typical of the natural habitats of trees. We mixed them at different signal-to-noise ratios (SNRs) to simulate the realistically collected sounds. The SNR of the enhanced boring vibrations can reach up to 17.84 dB after being enhanced by our model, and this model can restore the details of the vibration signals remarkably. Consequently, our model’s enhancement procedure led to a significant increase in accuracy for VGG16, a commonly used classification model. All results demonstrate the effectiveness of our approach for enhancing the detection of larvae using boring vibration signals.

The gut microbial dysbiosis is a risk of colorectal cancer (CRC) and some bacteria have been reported as potential markers for CRC diagnosis. However, heterogeneity among studies with different populations and technologies lead to inconsistent results. Here, we investigated six metagenomic profiles of stool samples from healthy controls (HC), colorectal adenoma (CA) and CRC, and six and four genera were consistently altered between CRC and HC or CA across populations, respectively. In FengQ cohort, which composed with 61 HC, 47 CA, and 46 CRC samples, a random forest (RF) model composed of the six genera, denoted as signature-HC, distinguished CRC from HC with an area under the curve (AUC) of 0.84. Similarly, another RF model composed of the four universal genera, denoted as signature-CA, discriminated CRC from CA with an AUC of 0.73. These signatures were further validated in five metagenomic sequencing cohorts and six independent 16S rRNA gene sequencing cohorts. Interestingly, three genera overlapped in the two models (Porphyromonas, Parvimonas and Peptostreptococcus) were with very low abundance in HC and CA, but sharply increased in CRC. A concise RF model on the three genera distinguished CRC from HC or CA with AUC of 0.87 and 0.67, respectively. Functional gene family analysis revealed that Kyoto Encyclopedia of Genes and Genomes Orthogroups categories which were significantly correlated with markers in signature-HC and signature-CA were mapped into pathways related to lipopolysaccharide and sulfur metabolism, which might be vital risk factors of CRC development. Conclusively, our study identified universal bacterial markers across populations and technologies as potential aids in non-invasive diagnosis of CRC.

AimsTo investigate cardiac pathology in critically ill patients with coronavirus disease 2019 (COVID-19) and identify associations between pathological changes and clinical characteristics.MethodsThe present autopsy cohort study included hearts from 26 deceased patients hospitalized in intensive care units due to COVID-19, and was conducted at four sites in Wuhan, China. Cases were divided into a neutrophil infiltration group and a no-neutrophil group based on the presence or absence of histopathologically identified neutrophilic infiltrates.ResultsAmong the 26 patients, histopathological examination identified active myocarditis in four patients. All patients with myocarditis exhibited extensive accompanying neutrophil infiltration, and all patients without myocarditis did not. The neutrophil infiltration group exhibited significantly higher rates of detection of interleukin-6 (100 vs. 4.6%) and tumor necrosis factor-alpha (100 vs. 31.8%) than the no-neutrophil group (both p < 0.05). On admission, four patients with neutrophil infiltration in myocardium had significantly higher baseline levels of aspartate aminotransferase, D dimer, and high-sensitivity C reactive protein than the other 22 patients (all p < 0.05). During hospitalization, patients with neutrophil infiltration had significantly higher maximum creatine kinase-MB (median 280.0 IU/L vs. 38.7 IU/L, p = 0.04) and higher troponin I (median 1.112 ng/ml vs. 0.220 ng/ml, p = 0.56) than patients without neutrophil infiltration.ConclusionActive myocarditis was frequently associated with neutrophil infiltration in the hearts of deceased patients with severe COVID-19. Patients with neutrophil-infiltrated myocarditis had a series of severely abnormal laboratory test results on admission, and high maximum creatine kinase-MB during hospitalization. The role of neutrophils in severe heart injury and systemic conditions in patients with COVID-19 should be emphasized.

Abstract One third of chondrichthyan species (sharks, rays, and chimeras) are threatened with extinction, mainly due to unsustainable fishing. Large accessible international markets for meat and luxury products like dried fins can help drive overfishing by encouraging targeted capture or retention of high‐value export species. If this is common, then species in international trade could have heightened extinction risk. Here, we examined the species composition of the Hong Kong shark fin market from 2014 to 2018, finding that traded species disproportionately occur in threatened categories (70.9%) and all premium value species are threatened. A small number of cosmopolitan species dominate the trade, but noncosmopolitan coastal species are still traded at concerning levels given their limited distribution. These coastal species are not generally subject to retention prohibitions, fisheries management, or international trade regulations and without management many could become extinct. The conservation potential of international trade regulations alone for coastal chondrichthyans depends on the extent to which overfishing is driven by export markets; socioeconomic studies of coastal fishing communities are needed to make this determination. Nonetheless, adding international trade regulations for more coastal shark species that are in the fin trade could prompt broad engagement with overfishing in nations lacking effective management.

Using data from 30 provincial-level in China during 2005–2019, this paper investigates the impact of foreign direct investment (FDI) quality characteristics on carbon emission intensity. Based on the Copeland-Taylor model, the mechanism of the impact of FDI quality characteristics on carbon emission intensity is also investigated. The key findings demonstrate that FDI quality traits considerably lower regional carbon intensity, and the result is still robust after considering the spatial correlation and using IV-2sls in consideration of endogeneity. The FDI quality characteristics mainly reduce carbon emission intensity through green technology improvement, industrial structure, and factor endowment structure optimization. Moreover, further evidence shows that there are heterogeneous effects with regard to regional and FDI quality characteristics. From the standpoint of FDI quality characteristics, this study adds to the literature on FDI and environmental pollution. Policy recommendations for China are also discussed in this paper, which can serve as a guide for other emerging nations.

Under the influence of the dual policies of sustainable economic development and the national dual-carbon target, the establishment of an environmental protection department for the treatment of heavily polluting industries is imminent, and the country has launched pollution control policies and regulations to restrict the emission rights of heavily polluting industries. Therefore, this paper focuses on whether the restriction of emission rights in key industries has reduced carbon emissions. To achieve this, this paper uses panel data of prefecture-level cities in China from 2006 to 2019 and adopts a two-way fixed-effects DID model to systematically analyze the impact of the key pollution industry governance policies launched by the Ministry of Environmental Protection on CO2 emissions in 2017. And further analyze the role of variables such as green technology innovation patents and energy efficiency using this model, while parallel trend tests and placebo tests, and related policies are used to ensure the robustness of the regression results. This paper reveals that: (1) The heavy pollution industry governance policy implemented in 2017 can effectively reduce CO2 emissions in the cities of the treated group, and the effect is more significant in the year of policy implementation; (2) Green utility patents and energy-use efficiency are the effective mediating mechanisms to reduce CO2 emissions; (3) Over time, the effect of heavy pollution industry governance policy on CO2 emissions gradually decreases; (4) The reliability of the baseline regression results of this paper is proved by the use of parallel trend tests, placebo tests, and tests excluding the influence factors such as relevant policies in the same period. Therefore, the key polluting industries treatment policy launched by China’s Ministry of Environmental Protection in 2017 under the recent dual-carbon policy development goals formulated by China, can effectively reduce carbon emissions; however, in the future economic development process, the government should give more consideration to the continuity of the policy impact and its coherence on economic development when implementing the policy.

Recurrence is the main factor affecting the prognosis of early hepatocellular carcinoma (HCC), which is not accurately evaluated by clinical indicators. The metabolic heterogeneity of HCC hints at the possibility of constructing a stratification model to predict the clinical outcome. On the basis of the relative expression orderings of 2939 metabolism-related genes, an individualized signature with 10 metabolism-related gene pairs (10-GPS) was developed from 250 early HCC samples in the discovery datasets, which stratified HCC patients into the high- and low-risk subgroups with significantly different survival rates. The 10-GPS was validated in 311 public transcriptomic samples from two independent validation datasets. A nomogram that included the 10-GPS, age, gender, and stage was constructed for eventual clinical evaluation. The low-risk group was characterized by lower proliferation, higher metabolism, increased activated immune microenvironment, and lower TIDE scores, suggesting a better response to immunotherapy. The high-risk group displayed hypomethylation, higher copy number alterations, mutations, and more overexpression of immune-checkpoint genes, which might jointly lead to poor outcomes. The prognostic accuracy of the 10-GPS was further validated in 47 institutional transcriptomic samples and 101 public proteomic samples. In conclusion, the 10-GPS is a robust predictor of the clinical outcome for early HCC patients and could help evaluate prognosis and characterize molecular heterogeneity.

The use of a free-trade zone (FTZ) has emerged as a smart land tool in increasing trading, attracting foreign investment, attempting financial openness and conducting other pilot economic reforms, which adds higher requirements for smart spatial planning, smart industry planning and smart management planning. However, no systematic analysis has been performed, making it difficult to provide deeper insights into FTZs. Thus, this study conducted bibliometric and visual analysis to identify the research status, new theories or practices, and potential future directions of FTZs based on 953 publications from the Web of Science Core Collection. The results show that there is a marked rise in the number of FTZ studies since 2013, which is the same year China authorized the first FTZ in Shanghai. China and the United States of America have played a leading role in FTZ research. Finally, the increasing trend in FTZ utilization will remain sizeable during its deepening development. The findings may contribute to a better understanding of FTZs and make some references to smart land-use planning experience and practices around the globe.

Industrial agglomeration is a major source of regional economic development and the main pattern enterprises employ after having developed to a certain stage. Industrial agglomeration also affects the emissions of air pollutants in production. Based on provincial panel data for China from 2006 to 2019, this paper introduces the full generalized least squares (FGLS) panel econometrics model. By considering spatial correlation, the potential endogenous problem has been controlled using the instrumental variable and the effects of the co-agglomeration of manufacturing and producer services on three major air pollutants, i.e., SO2, PM2.5, and NOx, have been empirically estimated. The empirical results show that: (1) The agglomeration of manufacturing increases the emission of PM2.5 in the air, while the agglomeration of producer services and the co-agglomeration of manufacturing and producer services reduce it. Moran correlation index test showed that SO2 and NOx had no significant spatial correlation. (2) The agglomeration of manufacturing, the agglomeration of producer services, and co-agglomeration exert the most significant effects on PM2.5 in the air in central and western China. This is probably because of the availability of basic natural resources in these areas. (3) The energy consumption structure mediates the effect of the agglomeration of manufacturing on PM2.5, and human capital mediates the effect of the agglomeration of producer services on PM2.5 emissions. Based on the results, policy suggestions to improve the atmospheric environment during the process of industrial agglomeration are proposed.

Background: Previously reported transcriptional signatures for predicting the prognosis of stage I-III bladder cancer (BLCA) patients after surgical resection are commonly based on risk scores summarized from quantitative measurements of gene expression levels, which are highly sensitive to the measurement variation and sample quality and thus hardly applicable under clinical settings. It is necessary to develop a signature which can robustly predict recurrence risk of BLCA patients after surgical resection.Methods: The signature is developed based on the within-sample relative expression orderings (REOs) of genes, which are qualitative transcriptional characteristics of the samples.Results: A signature consisting of 12 gene pairs (12-GPS) was identified in training data with 158 samples. In the first validation dataset with 114 samples, the low-risk group of 54 patients had a significantly better overall survival than the high-risk group of 60 patients (HR = 3.59, 95% CI: 1.34~9.62, p = 6.61 × 10−03). The signature was also validated in the second validation dataset with 57 samples (HR = 2.75 × 1008, 95% CI: 0~Inf, p = 0.05). Comparison analysis showed that the transcriptional differences between the low- and high-risk groups were highly reproducible and significantly concordant with DNA methylation differences between the two groups.Conclusions: The 12-GPS signature can robustly predict the recurrence risk of stage I-III BLCA patients after surgical resection. It can also aid the identification of reproducible transcriptional and epigenomic features characterizing BLCA metastasis.

Despite being protected by both international and national regulations, pangolins are threatened by illegal trade. Here we report mitochondrial DNA identification and haplotype richness estimation, using 239 pangolin scale samples from two confiscations in Hong Kong. We found a total of 13 genetically distinct cytochrome c oxidase I (COI) haplotypes in two confiscations (13 and ten haplotypes respectively, with ten shared haplotypes between confiscations). These haplotypes clustered in two distinct clades with one clade representing the Sunda pangolin (Manisjavanica). The other clade did not match with any known Asian pangolin sequences, and likely represented a cryptic pangolin lineage in Asia. By fitting sample coverage and rarefaction/regression models to our sample data, we predicted that the total number of COI haplotypes in two confiscations were 14.86 and 11.06 respectively, suggesting that our sampling caught the majority of haplotypes and that we had adequately characterized each confiscation. We detected substantial sequence divergence among the seized scales, likely evidencing that the Sunda pangolins were harvested over wide geographical areas across Southeast Asia. Our study illustrates the value of applying DNA forensics for illegal wildlife trade monitoring.

In this paper, we give the “generator” of int-soft filters and propose the notion of t-int-soft filters on residuated lattices. We study the properties of t-int-soft filters and obtain some commonalities (e.g., the extension property, quotient characteristics, and a triple of equivalent characteristics). We also use involution-int-soft filters as an example and show some basic properties of involution-int-soft filters. Finally, we investigate the relations among t-int-soft filters and give a simple method for judging their relations.

Summary Studies on the role of the E-box binding transcription factor Snail2 (Slug) in the induction of neural crest by mesoderm (Shi et al., 2011) revealed an unexpected increase in the level of sizzled RNA in the dorsolateral mesodermal zone (DMLZ) of morphant Xenopus embryos. sizzled encodes a secreted protein with both Wnt and BMP inhibitor activities. Morpholino-mediated down-regulation of sizzled expression in one cell of two cell embryos or the C2/C3 blastomeres of 32-cell embryos, which give rise to the DLMZ, revealed decreased expression of the mesodermal marker brachyury and subsequent defects in neural crest induction, pronephros formation, and muscle patterning. Loss of sizzled expression led to decreases in RNAs encoding the secreted Wnt inhibitor SFRP2 and the secreted BMP inhibitor Noggin; the sizzled morphant phenotype could be rescued by co-injection of RNAs encoding Noggin and either SFRP2 or Dickkopf (a mechanistically distinct Wnt inhibitor). Together, these observations reveal that sizzled, in addition to its established role in dorsal-ventral patterning, is also part of a dynamic BMP and Wnt signaling network involved in both mesodermal patterning and neural crest induction.

We give the simple general principle of studying the relations among fuzzy t-filters on residuated lattices. Using the general principle, we can easily determine the relations among fuzzy t-filters on different logical algebras.

One-dimensional SrTiO3/TiO2−xNx nanostructures were prepared by the hydrothermal method and investigated by X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and ultraviolet-visible diffuse reflectance spectroscopy (UV-vis DRS) measurements. The photocatalytic activities of the prepared samples were evaluated by photodegrading the methylene blue (MB) solution. According to the characterizations, the intermediate product of SrTiO3/titanate nanotubes was presented after hydrothermal processing of the TiO2−xNx nanoparticles with the mixed solution of NaOH and Sr(NO3)2. The final product of SrTiO3/TiO2−xNx nanorods was obtained after calcining the intermediate. As compared to the TiO2−xNx nanoparticles, the absorption performance of SrTiO3/titanate nanotubes or SrTiO3/TiO2−xNx nanorods was depressed, instead of improving it. The mechanisms of the absorption property changes were discussed. The SrTiO3/TiO2−xNx nanorods presented better photocatalytic activity than the TiO2−xNx nanoparticles or nanorods. However, due to overmuch adsorption, the SrTiO3/titanate nanotubes gave ordinary photocatalytic performances.