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Retinoblastoma (RB) is the most common intraocular malignant tumor in children, primarily attributed to the bi-allelic loss of the RB1 gene in the developing retina. Despite significant progress in understanding the basic pathogenesis of RB, comprehensively unravelling the intricate network of genetics and epigenetics underlying RB tumorigenesis remains a major challenge. Conventional clinical treatment options are limited, and despite the continuous identification of genetic loci associated with cancer pathogenesis, the development of targeted therapies lags behind. This review focuses on the reported genomic and epigenomic alterations in retinoblastoma, summarizing potential therapeutic targets for RB and providing insights for research into targeted therapies.

Biogeochemical redox cycling of iron (Fe) essentially governs various geochemical processes in nature. However, the mechanistic underpinnings of Fe-redox cycling in deep-sea sediments remain poorly understood, due to the limited access to the deep-sea environment. Here, abyssal sediment collected from a depth of 5800 m in the Pacific Ocean was characterized for its elemental, mineralogical, and biological properties. The sedimentary environment was determined to be oligotrophic with limited nutrition, yet contained a considerable amount of trace elements. Fe-redox reactions in sediment progressed through an initial lag phase, followed by a fast Fe(II) reduction and an extended period of Fe(III) oxidation before achieving equilibrium after 58 days. The presence of an external H2 electron donor significantly increased the extent of Fe(III) bio-reduction by 7.73% relative to an amendment-free control under high pressure of 58 MPa. A similar enhancement of 11.20% was observed following lactate amendment under atmospheric pressure. Fe(II) bio-oxidation occurred after 16 days’ anaerobic culturing, coupled with nitrate reduction. During Fe bio-redox reactions, microbial community composition was significantly shaped by the presence/absence of an electron donor, while the hydrostatic pressure levels were the controlling factor. Shewanella spp. emerged as the primary Fe(III)-reducing microorganisms, and were stimulated by supplemented lactate. Marinobacter hydrocarbonoclasticus was the predominant Fe(II)-oxidizing microorganism across all conditions. Our findings illustrate continuous Fe-redox reactions occurring in the deep-sea environment, with coexisting Fe-redox microorganisms determining the oscillation of Fe valence states within the abyssal sediment.

Underwater cracks are difficult to detect and observe, posing a major challenge to crack detection. Currently, deep learning-based underwater crack detection methods rely heavily on a large number of crack images that are difficult to collect due to their complex and hazardous underwater environments. This study proposes a new underwater image-processing method that combines a novel white balance method and bilateral filtering denoising method to transform underwater crack images into high-quality above-water images with original crack features. Crack detection is then performed based on an improved YOLOv9-OREPA model. Through experiments, it is found that the new image-processing method proposed in this study significantly improves the evaluation indicators of new images, compared with other methods. The improved YOLOv9-OREPA also exhibits a significantly improved performance. The experimental results demonstrate that the method proposed in this study is a new approach suitable for detecting underwater cracks in dams and achieves the goal of transforming underwater images into above-water images.

Green process innovation is an important strategy in the high-quality development of enterprises. Digital technology is becoming a key factor in helping businesses address environmental issues and contributes to their green process innovation and sustainable growth. Nevertheless, there is a lack of studies on how particular digital technology categories affect corporate green process innovation. Artificial intelligence (AI) is an important part of digitalization as it can provide new technical means and guidance for enterprise’s innovation of green processes. This study aims to fills this research gap by revealing the logical relationship between digital technology and the green development of enterprises. Using China’s A-share-listed companies as the research object from 2013 to 2022, this study employed a two-way fixed-effects model and investigated the impact of artificial intelligence (AI) on corporate green process innovation and the moderating effect of multidimensional intellectual capital. The results revealed that AI positively impacts corporate green process innovation. Human capital, structural capital, employed capital, and relational capital strengthen this positive effect. Robustness tests validated these conclusions. This study expands the literature on digital technology and corporate green innovation and provides a reference for enterprises to implement green practices using digital technology.

The radial distribution of material feeding onto a screen surface is an important factor affecting vibration screening performance, and it is also the main basis for the optimization of the operating parameters of a vibration screening system. In this paper, based on near-infrared properties, a real-time measurement method for the mass flow rate of grain vibration feeding was proposed. A laser emitter and a silicon photocell were used as the measuring components, and the corresponding signal processing circuit mainly composed of a T-type I/V convertor, a voltage follower, a low-pass filter, and a setting circuit in series was designed. Calibration test results showed that the relationship between grain mass flow rate and output voltage could be described using the Gaussian regression model, and the coefficient of determination was greater than 0.98. According to the working principle of the grain cleaning system of combine harvesters, the dynamic characteristics of grain vibration feeding were analyzed using discrete element method (DEM) simulations, and the monitoring range of the sensor was determined. Finally, grain mass flow rate measurement tests were carried out on a vibration feeding test rig. The results indicated that the grain mass measurement error could be controlled within 5.0% with the average grain mass flow rate in the range of 3.0–5.0 g/mm·s. The proposed measurement method has potential application value in the uniform feeding control systems of vibration feeders.

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is an infectious disease that seriously affects human life and health. Despite centuries of efforts to control it, in recent years, the emergence of multidrug-resistant bacterial pathogens of M. tuberculosis due to various factors has exacerbated the disease, posing a serious threat to global health. Therefore, a new method to control M. tuberculosis is urgently needed. Phages, viruses that specifically infect bacteria, have emerged as potential biocontrol agents for bacterial pathogens due to their host specificity. In this study, a mycobacterium phage, Henu3, was isolated from soil around a hospital. The particle morphology, biological characteristics, genomics and phylogeny of Henu3 were characterized. Additionally, to explore the balance between phage resistance and stress response, phage Henu3-resistant strains 0G10 and 2E1 were screened by sequence passage and bidirectional validation methods, which significantly improved the sensitivity of phage to antibiotics (cefotaxime and kanamycin). By whole-genome re-sequencing of strains 0G10 and 2E1, 12 genes involved in cell-wall synthesis, transporter-encoded genes, two-component regulatory proteins and transcriptional regulatory factor-encoded genes were found to have mutations. These results suggest that phage Henu3 has the potential to control M. tuberculosis pathogens, and phage Henu3 has the potential to be a new potential solution for the treatment of M. tuberculosis infection.

Oil palm is a versatile oil crop with numerous applications. Significant progress has been made in applying histological techniques in oil palm research in recent years. Whole genome sequencing of oil palm has been carried out to explain the function and structure of the order genome, facilitating the development of molecular markers and the construction of genetic maps, which are crucial for studying important traits and genetic resources in oil palm. Transcriptomics provides a powerful tool for studying various aspects of plant biology, including abiotic and biotic stresses, fatty acid composition and accumulation, and sexual reproduction, while proteomics and metabolomics provide opportunities to study lipid synthesis and stress responses, regulate fatty acid composition based on different gene and metabolite levels, elucidate the physiological mechanisms in response to abiotic stresses, and explain intriguing biological processes in oil palm. This paper summarizes the current status of oil palm research from a multi-omics perspective and hopes to provide a reference for further in-depth research on oil palm.

Despite the development of molecular techniques, morphological phylogeny still remains integral in underpinning the relationship between some clades of Calyptratae, especially the ones with fast radiation, such as those in Oestridae (Diptera: Brachycera), yet few synapomorphy has been proposed for adults in this family. Using scanning electron microscopy, we investigated the morphological structure and ultrastructure of the antennae and maxillary palps of adult Oestromyia leporina (Hypodermatinae, Oestridae). One type of trichoid sensillum (Tr), three types of basiconic sensilla (Ba I, Ba II, and Ba III), one type of coeloconic sensillum (Co I), and one type of clavate sensillum (Cl) were found on the antennal postpedicel. Surprisingly, this species has the most complex types of sensilla on the maxillary palps that have been reported in Calyptratae so far, with two types of coeloconic sensilla (Co II and Co III) and two types of mechanoreceptors. We then identified three common characteristics on the arista of Oestridae (Hypodermatinae, Oestrinae, Gasterophilinae and Cuterebrinae) that are potential synapomorphies. These characteristics indicate the value of the morphology of maxillary palps and aristae in taxonomy studies of Calyptratae.

Fermented mare’s milk (koumiss), a traditional Central Asian dairy product derived from fermented mare’s milk, is renowned for its unique sour taste and texture. It has long been consumed by nomadic tribes for its nutritional and medicinal benefits. This study aimed to comprehensively analyze the protective effects of koumiss against alcohol-induced harm across behavioral, hematological, gastrointestinal, hepatic, and reproductive dimensions using a mouse model. Optimal intoxicating doses of alcohol and koumiss doses were determined, and their effects were explored through sleep tests and blood indicator measurements. Pretreatment with koumiss delayed inebriation, accelerated sobering, and reduced mortality in mice, mitigating alcohol’s impact on blood ethanol levels and various physiological parameters. Histopathological and molecular analyses further confirmed koumiss’s protective role against alcohol-induced damage in the liver, stomach, small intestine, and reproductive system. Transcriptomic studies on reproductive damage indicated that koumiss exerts its benefits by influencing mitochondrial and ribosomal functions and also shows promise in mitigating alcohol’s effects on the reproductive system. In summary, koumiss emerges as a potential natural agent for protection against alcohol-induced harm, opening avenues for future research in this field.

In the task of classifying images of cracks in underwater dams, symmetry serves as a crucial geometric feature that aids in distinguishing cracks from other structural elements. Nevertheless, the asymmetry in the distribution of positive and negative samples within the underwater dam crack image dataset results in a long-tail problem. This asymmetry, coupled with the subtle nature of crack features, leads to inadequate feature extraction by existing convolutional neural networks, thereby reducing classification accuracy. To address these issues, this paper improves VanillaNet. First, the Seesaw Loss loss function is introduced to tackle the long-tail problem in classifying underwater dam crack images, enhancing the model’s ability to recognize tail categories. Second, the Adaptive Frequency Filtering Token Mixer (AFF Token Mixer) is implemented to improve the model’s capability to capture crack image features and enhance classification accuracy. Finally, label smoothing is applied to prevent overfitting to the training data and improve the model’s generalization performance. The experimental results demonstrate that the proposed improvements significantly enhance the model’s classification accuracy for underwater dam crack images. The optimized algorithm achieves superior average accuracy in classifying underwater dam crack images, showing improvements of 1.29% and 0.64% over the relatively more accurate models ConvNeXtV2 and RepVGG, respectively. Compared to VanillaNet, the proposed algorithm increases average accuracy by 2.66%. The improved model also achieves higher accuracy compared to the pre-improved model and other mainstream networks.

Oil palm (Elaeis guineensis Jacq.) is a typical tropical oil crop with a temperature of 26–28 °C, providing approximately 35% of the total world’s vegetable oil. Growth and productivity are significantly affected by low-temperature stress, resulting in inhibited growth and substantial yield losses. To comprehend the intricate molecular mechanisms underlying the response and acclimation of oil palm under low-temperature stress, multi-omics approaches, including metabolomics, proteomics, and transcriptomics, have emerged as powerful tools. This comprehensive review aims to provide an in-depth analysis of recent advancements in multi-omics studies on oil palm under low-temperature stress, including the key findings from omics-based research, highlighting changes in metabolite profiles, protein expression, and gene transcription, as well as including the potential of integrating multi-omics data to reveal novel insights into the molecular networks and regulatory pathways involved in the response to low-temperature stress. This review also emphasizes the challenges and prospects of multi-omics approaches in oil palm research, providing a roadmap for future investigations. Overall, a better understanding of the molecular basis of the response of oil palm to low-temperature stress will facilitate the development of effective breeding and biotechnological strategies to improve the crop’s resilience and productivity in changing climate scenarios.

In this study, we investigated the effect of monobutyrin (MB) on the gut microbiota and intestinal health of weaned mice. MB was administered via gavage to 21-day-old weaned mice. Samples of small intestinal and ileal contents were collected on day 1, day 7, and day 21 post-administration. Seven days of MB administration enhanced the mucin layer and morphological structure of the intestine and the integrity of the intestinal brush border. Both MB and sodium butyrate (SB) accelerated tight junction development. Compared to SB, MB modulated intestinal T cells in a distinct manner. MB increased the ratio of Treg cells in the small intestine upon the cessation of weaning. After 21 days of MB administration, enhancement of the villus structure of the ileum was observed. MB increased the proportion of Th17 cells in the ileum. MB facilitated the transition of the small intestinal microbiota toward an adult microbial community structure and enhanced the complexity of the microbial community structure. An increase in Th17 cells enhanced intestinal barrier function. The regulatory effect of MB on Th17 cells may occur through the intestinal microbiota. Therefore, MB can potentially be used to promote intestinal barrier function, especially for weaning animals, with promising application prospects.

As one of the most important food crops in the world, rice yield is directly related to national food security. Lodging is one of the most important factors restricting rice production, and the cultivation of rice varieties with lodging resistance is of great significance in rice breeding. The lodging resistance of rice is directly related to the mechanical strength of the stalks. In this paper, we reviewed the cell wall structure, its components, and its genetic regulatory mechanism, which improved the regulatory network of rice stalk mechanical strength. Meanwhile, we analyzed the new progress in genetic breeding and put forward some scientific problems that need to be solved in this field in order to provide theoretical support for the improvement and application of rice breeding.

Testicular development and spermatogenesis are tightly regulated by both coding and non-coding genes, with mRNA and lncRNA playing crucial roles in post-transcriptional gene expression regulation. However, there are significant differences in regulatory mechanisms before and after sexual maturity. Nevertheless, the mRNAs and lncRNAs in the testes of Mongolian horses have not been systematically identified. In this study, we first identified the testicular tissues of sexually immature and sexually mature Mongolian horses at the tissue and protein levels, and comprehensively analyzed the expression profiles of mRNA and lncRNA in the testes of 1-year-old (12 months, n = 3) and 10-year-old (n = 3) Mongolian horses using RNA sequencing technology. Through gene expression analysis, we identified 16,582 mRNAs and 2128 unknown lncRNAs that are commonly expressed in both sexually immature and sexually mature Mongolian horses. Meanwhile, 9217 mRNAs (p < 0.05) and 2191 unknown lncRNAs (p < 0.05) were identified as differentially expressed between the two stages, which were further validated by real-time fluorescent quantitative PCR and analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The analysis results showed that genes in the sexually immature stage were mainly enriched in terms related to cellular infrastructure, while genes in the sexually mature stage were enriched in terms associated with hormones, metabolism, and spermatogenesis. In summary, the findings of this study provide valuable resources for a deeper understanding of the molecular mechanisms underlying testicular development and spermatogenesis in Mongolian horses and offer new perspectives for future related research.

In adverse foggy weather conditions, images captured are adversely affected by natural environmental factors, resulting in reduced image contrast and diminished visibility. Traditional image dehazing methods typically rely on prior knowledge, but their efficacy diminishes in practical, complex environments. Deep learning methods have shown promise in single-image dehazing tasks, but often struggle to fully leverage depth and edge information, leading to blurred edges and incomplete dehazing effects. To address these challenges, this paper proposes a deep-guided bilateral grid feature fusion dehazing network. This network extracts depth information through a dedicated module, derives bilateral grid features via Unet, employs depth information to guide the sampling of bilateral grid features, reconstructs features using a dedicated module, and finally estimates dehazed images through two layers of convolutional layers and residual connections with the original images. The experimental results demonstrate the effectiveness of the proposed method on public datasets, successfully removing fog while preserving image details.

AP2/ERF transcription factor genes play an important role in regulating the responses of plants to various abiotic stresses, such as cold, drought, high salinity, and high temperature. However, less is known about the function of oil palm AP2/ERF genes. We previously obtained 172 AP2/ERF genes of oil palm and found that the expression of EgAP2.25 was significantly up-regulated under salinity, cold, or drought stress conditions. In the present study, the sequence characterization and expression analysis for EgAP2.25 were conducted, showing that it was transiently over-expressed in Nicotiana tabacum L. The results indicated that transgenic tobacco plants over-expressing EgAP2.25 could have a stronger tolerance to salinity stress than wild-type tobacco plants. Compared with wild-type plants, the over-expression lines showed a significantly higher germination rate, better plant growth, and less chlorophyll damage. In addition, the improved salinity tolerance of EgAP2.25 transgenic plants was mainly attributed to higher antioxidant enzyme activities, increased proline and soluble sugar content, reduced H2O2 production, and lower MDA accumulation. Furthermore, several stress-related marker genes, including NtSOD, NtPOD, NtCAT, NtERD10B, NtDREB2B, NtERD10C, and NtP5CS, were significantly up-regulated in EgAP2.25 transgenic tobacco plants subjected to salinity stress. Overall, over-expression of the EgAP2.25 gene significantly enhanced salinity stress tolerance in transgenic tobacco plants. This study lays a foundation for further exploration of the regulatory mechanism of the EgAP2.25 gene in conferring salinity tolerance in oil palm.

A moored spar platform, equipped with various instruments, serves as a crucial tool in hydrological monitoring. However, conducting dynamic analyses of a single spar that endures wind and current requires significant amount of computational time. To address this challenge, this study proposes an efficient surrogate model to represent fluid loads. A database is established to capture the relationship between fluid loads, spar displacements and uniform currents based on a numerical model of the spar. Subsequently, an artificial neural network method is employed to construct the surrogate model. Finally, the surrogate model is integrated with a numerical model of the cable, developed using the lumped mass method, to create a coupled model of the moored spar. The dynamic responses of this coupled model align closely with those obtained from the purely numerical model, demonstrating the efficacy of the surrogate model in capturing fluid loads on the spar. In addition to the surrogate model generation approach, this research provides an efficient method to couple the surrogate model with the numerical model in dynamic analysis of floating systems in uniform currents.

Glycyrrhetinic acid (GA) is a saponin compound, isolated from licorice (Glycyrrhiza glabra), which has been wildly explored for its intriguing pharmacological and medicinal effects. GA is a triterpenoid glycoside displaying an array of pharmacological and biological activities, including anti-inflammatory, anti-bacterial, antiviral and antioxidative properties. In this study, we investigated the underlying mechanisms of GA on acne vulgaris through network pharmacology and proteomics. After the intersection of the 154 drug targets and 581 disease targets, 37 therapeutic targets for GA against acne were obtained. A protein–protein interaction (PPI) network analysis highlighted TNF, IL1B, IL6, ESR1, PPARG, NFKB1, STAT3 and TLR4 as key targets of GA against acne, which is further verified by molecular docking. The experimental results showed that GA inhibited lipid synthesis in vitro and in vivo, improved the histopathological damage of skin, prevented mast cell infiltration and decreased the level of pro-inflammatory cytokines, including TNF-α, IL-1β and IL-6. This study indicates that GA may regulate multiple pathways to improve acne symptoms, and the beneficial effects of GA against acne vulgaris might be through the regulation of sebogenesis and inflammatory responses.

As a strong interference source for the all-time optical imaging surveillance of maritime targets, sea surface glare is difficult to mitigate accurately because of its time-varying characteristics due to lighting conditions and seawater fluctuations. In this paper, we propose an adaptive suppression approach to sea surface glare, which establishes a geographic polarization suppression model based on real-time information regarding geographic positioning and the orientation information of the floating platform, and also combines dynamic polarization control and pixel normalization to achieve adaptive suppression of sea surface glare. Experimental results show that this approach can mitigate the influence of rapidly changing glare effectively, and the SSIM indexes between the images without glare and those with glare suppression of the same scenes exceed 0.8, which is suitable for all-time glare suppression on the sea surface under natural lighting conditions.

This study aimed to investigate differences in testicular tissue morphology, gene expression, and marker genes between sexually immature (1-year-old) and sexually mature (10-year-old) Mongolian horses. The purposes of our research were to provide insights into the reproductive physiology of male Mongolian horses and to identify potential markers for sexual maturity. The methods we applied included the transcriptomic profiling of testicular cells using single-cell sequencing techniques. Our results revealed significant differences in tissue morphology and gene expression patterns between the two age groups. Specifically, 25 cell clusters and 10 cell types were identified, including spermatogonial and somatic cells. Differential gene expression analysis highlighted distinct patterns related to cellular infrastructure in sexually immature horses and spermatogenesis in sexually mature horses. Marker genes specific to each stage were also identified, including APOA1, AMH, TAC3, INHA, SPARC, and SOX9 for the sexually immature stage, and PRM1, PRM2, LOC100051500, PRSS37, HMGB4, and H1-9 for the sexually mature stage. These findings contribute to a deeper understanding of testicular development and spermatogenesis in Mongolian horses and have potential applications in equine reproductive biology and breeding programs. In conclusion, this study provides valuable insights into the molecular mechanisms underlying sexual maturity in Mongolian horses.

Aiming at the nonlinear radiometric differences between multi-source sensor images and coherent spot noise and other factors that lead to alignment difficulties, the registration method of gradient weakly sensitive multi-source sensor images is proposed, which does not need to extract the image gradient in the whole process and has rotational invariance. In the feature point detection stage, the maximum moment map is obtained by using the phase consistency transform to replace the gradient edge map for chunked Harris feature point detection, thus increasing the number of repeated feature points in the heterogeneous image. To have rotational invariance of the subsequent descriptors, a method to determine the main phase angle is proposed. The phase angle of the region near the feature point is counted, and the parabolic interpolation method is used to estimate the more accurate main phase angle under the determined interval. In the feature description stage, the Log-Gabor convolution sequence is used to construct the index map with the maximum phase amplitude, the heterogeneous image is converted to an isomorphic image, and the isomorphic image of the region around the feature point is rotated by using the main phase angle, which is in turn used to construct the feature vector with the feature point as the center by the quadratic interpolation method. In the feature matching stage, feature matching is performed by using the sum of squares of Euclidean distances as a similarity metric. Finally, after qualitative and quantitative experiments of six groups of five pairs of different multi-source sensor image alignment correct matching rates, root mean square errors, and the number of correctly matched points statistics, this algorithm is verified to have the advantage of robust accuracy compared with the current algorithms.

Enzyme-assisted ultrasonic extraction (EAUE) was utilized and optimized for extracting polysaccharides from Schizochytrium limacinum meal (SLMPs) via the response surface methodology. The optimal EAUE conditions were determined as follows: enzyme concentration at 5.18%, ultrasonic temperature at 53 °C, ultrasonic duration of 40 min, ultrasonic power at 60 W, and a liquid-to-material ratio of 34 mL/g, achieving a polysaccharide extraction yield of 11.86 ± 0.61%. The purified polysaccharide component, SLMP1-1, isolated using DEAE Sepharose Fast Flow and Sephadex G-100 columns, exhibited potent antioxidant activity. SLMP1-1, with a molecular weight of 25.5 kDa, comprises glucose, mannose, arabinose, and galactose in a molar ratio of 16.39:14.75:1:693.03. 1H NMR analysis revealed the α configuration of SLMP1-1. Antioxidant assessments, including DPPH, ABTS, and ferric ion reduction assays, were detected with inhibitory values at 21.82–82.98%, 38.21–98.46%, and 3.30–20.30% at 0.2–1.0 mg/mL. This confirmed the effective antioxidant capacity of SLMP1-1, which is notably enhanced post oral and gastric digestion. The findings suggest that polysaccharides extracted from Schizochytrium limacinum meal hold significant promise as natural antioxidants.

Flexible electronics is a cutting-edge field that has paved the way for artificial tactile systems that mimic biological functions of sensing mechanical stimuli. These systems have an immense potential to enhance human–machine interactions (HMIs). However, tactile sensing still faces formidable challenges in delivering precise and nuanced feedback, such as achieving a high sensitivity to emulate human touch, coping with environmental variability, and devising algorithms that can effectively interpret tactile data for meaningful interactions in diverse contexts. In this review, we summarize the recent advances of tactile sensory systems, such as piezoresistive, capacitive, piezoelectric, and triboelectric tactile sensors. We also review the state-of-the-art fabrication techniques for artificial tactile sensors. Next, we focus on the potential applications of HMIs, such as intelligent robotics, wearable devices, prosthetics, and medical healthcare. Finally, we conclude with the challenges and future development trends of tactile sensors.

Light detection and ranging (LiDAR) is widely used in scenarios such as autonomous driving, imaging, remote sensing surveying, and space communication due to its advantages of high ranging accuracy and large scanning angle. Optical phased array (OPA) has been studied as an important solution for achieving all-solid-state scanning. In this work, the recent research progress in improving the beam steering performance of the OPA based on silicon photonic integrated chips was reviewed. An optimization scheme for aperiodic OPA is proposed.

The aim of this study was to verify whether small molecules can improve the efficiency of precision gene editing using clustered regularly interspaced short palindromic repeats (CRISPR) ribonucleoprotein (RNP) in porcine cells. CRISPR associated 9 (Cas9) protein, small guide RNA (sgRNA), phosphorothioate-modified single-stranded oligonucleotides (ssODN), and different small molecules were used to generate precise nucleotide substitutions at the insulin (INS) gene by homology-directed repair (HDR) in porcine fetal fibroblasts (PFFs). These components were introduced into PFFs via electroporation, followed by polymerase chain reaction (PCR) for the target site. All samples were sequenced and analyzed, and the efficiencies of different small molecules at the target site were compared. The results showed that the optimal concentrations of the small molecules, including L-189, NU7441, SCR7, L755507, RS-1, and Brefeldin A, for in vitro-cultured PFFs’ viability were determined. Compared with the control group, the single small molecules including L-189, NU7441, SCR7, L755507, RS-1, and Brefeldin A increased the efficiency of HDR-mediated precise gene editing from 1.71-fold to 2.28-fold, respectively. There are no benefits in using the combination of two small molecules, since none of the combinations improved the precise gene editing efficiency compared to single small molecules. In conclusion, these results suggested that a single small molecule can increase the efficiency of CRISPR RNP-mediated precise gene editing in porcine cells.

Obesity and its complications constitute a main threat to global human health. The purpose of this investigation was to explore the influences of Clostridium tyrobutyricum (Ct) on lipid metabolism, intestinal barrier function, and intestinal microbiome in obese mice induced by a high-fat diet (HFD). After establishing the obesity model, 107 CFU/mL and 108 CFU/mL C. tyrobutyricum were used to intervene in HFD-fed mice by gavage for six weeks, and indexes related to obesity were measured. In the liver of HFD-fed mice, the results revealed that C. tyrobutyricum reduced liver weight and the levels of triglyceride (TG), total cholesterol (TC), and nonesterified fatty acid (NEFA), along with decreasing red lipid droplets and fat vacuoles. After C. tyrobutyricum intervention, the mRNA expression of peroxisome proliferator-activated receptor-γ (PPARγ) was downregulated, and AMP-activated protein kinase (AMPK), peroxisome proliferator-activated receptor-α (PPARα), adipose triglyceride lipase (ATGL), and hormone-sensitive lipase (HSL) were upregulated in the liver. Additionally, C. tyrobutyricum alleviated intestinal morphology injury caused by HFD, decreased the expression of tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), and IL-1β in the colon, and upregulated tight junction protein expression. In addition, 16S rRNA sequencing revealed that C. tyrobutyricum increases the diversity of intestinal microbiota. Overall, C. tyrobutyricum improved HFD-induced lipid metabolism disorders, preserved the intestinal barrier’s integrity, and modulated the structure of the intestinal microbiome. These findings provide a novel insight into the role of C. tyrobutyricum as a probiotic in regulating lipid metabolism.

Hyperspectral image (HSI) classification plays a key role in the field of earth observation missions. Recently, transformer-based approaches have been widely used for HSI classification due to their ability to model long-range sequences. However, these methods face two main challenges. First, they treat HSI as linear vectors, disregarding their 3D attributes and spatial structure. Second, the repeated concatenation of encoders leads to information loss and gradient vanishing. To overcome these challenges, we propose a new solution called the multi-level feature extraction network (MLFEN). MLFEN consists of two sub-networks: the hybrid convolutional attention module (HCAM) and the enhanced dense vision transformer (EDVT). HCAM incorporates a band shift strategy to eliminate the edge effect of convolution and utilizes hybrid convolutional blocks to capture the 3D properties and spatial structure of HSI. Additionally, an attention module is introduced to identify strongly discriminative features. EDVT reconfigures the organization of original encoders by incorporating dense connections and adaptive feature fusion components, enabling faster propagation of information and mitigating the problem of gradient vanishing. Furthermore, we propose a novel sparse loss function to better fit the data distribution. Extensive experiments conducted on three public datasets demonstrate the significant advancements achieved by MLFEN.

Catalases (CATs) play crucial roles in scavenging H2O2 from reactive oxygen species, controlling the growth and development of plants. So far, genome-wide identification and characterization of CAT genes in oil palm have not been reported. In the present study, five EgCAT genes were obtained through a genome-wide identification approach. Phylogenetic analysis divided them into two subfamilies, with closer genes sharing similar structures. Gene structure and conserved motif analysis demonstrated the conserved nature of intron/exon organization and motifs among the EgCAT genes. Several cis-acting elements related to hormone, stress, and defense responses were identified in the promoter regions of EgCATs. Tissue-specific expression of EgCAT genes in five different tissues of oil palm was also revealed by heatmap analysis using the available transcriptome data. Stress-responsive expression analysis showed that five EgCAT genes were significantly expressed under cold, drought, and salinity stress conditions. Collectively, this study provided valuable information on the oil palm CAT gene family and the validated EgCAT genes can be used as potential candidates for improving abiotic stress tolerance in oil palm and other related crops.

Accurate identification and understanding of various metallic minerals are crucial for deciphering geological formations, structures, and ages. Giving their pivotal role as essential natural resources, a microscopic exploration of metallic minerals becomes imperative. Traditional analytical methods, while helpful, exhibit certain limitations. However, terahertz time-domain spectroscopy, distinguished by its high signal-to-noise ratio, expansive frequency band, and low incident wave energy, is a promising complement to conventional techniques in characterizing metallic minerals. This study employs terahertz time-domain spectroscopy to examine samples of Stibnite, Sphalerite, Galena, and Pyrite originating from diverse geological conditions. The vibrations of molecules within these metallic minerals induce discernible changes in the terahertz spectra. Our findings untiate the extensive potential of terahertz time-domain spectroscopy in the characterization of metallic minerals, affirming its considerable practical value in mineral resource exploration.

As major carbon (C) pools in cities, urban green spaces play a crucial role in reducing atmospheric carbon. To determine the importance of litterfall C storage in urban green spaces, we selected the leaf area index (LAI) as a proxy indicator for litterfall C density (LCD), and established a log-linear regression model between LCD and LAI to predict the annual litterfall C pool in large-scale urban green spaces using Sentinel-2 satellite remote sensing data. Forty-five sample units were randomly selected in typical urban green spaces in Beijing, China. A high-temperature combustion method was used to measure the LCD of the sampling units, and stepwise linear regression was used to filter the proxy indicator for LCD. The annual litterfall C pool in regions within the Fifth Ring Road was also estimated with inversion using remote sensing data. From 2015 to 2021, the estimated annual litterfall C pool was in the range of 4.5–5.8 × 1010 g, i.e., approximately 18.9% of the total C storage recorded for the urban green space, which was far greater than that observed in forest ecosystems. We concluded that the litterfall C pool in urban green spaces is seriously underestimated, and that urban tree litterfall has the potential to reduce greenhouse gas emissions if used as a carbon-neutral resource.

This study aims to enhance the productivity of high-voltage transmission line insulators and their operational safety by investigating their failure mechanisms under ultimate load conditions. Destructive tests were conducted on a specific type of insulator under ultimate load conditions. A high-speed camera was used to document the insulator’s failure process and collect strain data from designated points. A simulation model of the insulator was established to predict the effects of ultimate loads. The simulation results identified a maximum first principal stress of 94.549 MPa in the porcelain shell, with stress distribution characteristics resembling a cantilever beam subjected to bending. This implied that the insulator failure occurred when the stress reached the bending strength of the porcelain shell. To validate the simulation’s accuracy, bending and tensile strength tests were conducted on the ceramic materials constituting the insulator. The bending strength of the porcelain shell was 100.52 MPa, showing a 5.6% variation from the simulation results, which indicated the reliability of the simulation model. Finally, optimization designs on the design parameters P1 and P2 of the insulator were conducted. The results indicated that setting P1 to 8° and P2 to 90.062 mm decreased the first principal stress of the porcelain shell by 47.6% and Von Mises stress by 31.6% under ultimate load conditions, significantly enhancing the load-bearing capacity. This research contributed to improving the production yield and safety performance of insulators.

A new type of prefabricated foundation for onshore wind power was proposed in this paper. The stress and bearing mechanism of the new foundation was explored through theoretical calculation and finite element analysis. The results show that compared with the extended foundation in the same position, the amount of concrete in the new foundation is reduced by 30.00%, and the amount of rebars are reduced by 34.69%. The new prefabricated foundation has been inspected and calculated according to the specification. The calculation results indicate that the stress and initial reinforcement of the foundation meet the specification requirements. The bearing capacity, inclination rate, deformation, and stability of the foundation meet the requirements. Through finite element analysis, it is further confirmed that the structure meets the requirements of wind turbine operation, and the overall force meets the requirements of various indicators. The stress distribution of the foundation concrete and rebars is reasonable and uniform, and the load transfer is great. Also, the maximum stress of rebars and concrete does not exceed the specification limit, and the concrete remains intact without cracking or damage. The new foundation structural design and theoretical analysis were reasonable and accurate, and can be put into application in the future.

The newly released ‘Snow White’ (SW), a white-fleshed loquat (Eriobotrya japonica Lindl.) cultivar, holds promise for commercial production. However, the specifics of the phenolic composition in white-fleshed loquats, along with the antioxidant substances and their regulatory mechanisms, are not yet fully understood. In this study, we examined the dynamic changes in the phenolic compounds, enzyme activities, antioxidant capacity, and gene expression patterns of SW during the key stages of fruit development and ripening. A total of 18 phenolic compounds were identified in SW, with chlorogenic acid, neochlorogenic acid, and coniferyl alcohol being the most predominant. SW demonstrated a stronger antioxidant capacity in the early stages of development, largely due to total phenolics and flavonoids. Neochlorogenic acid may be the most significant antioxidant contributor in loquat. A decline in enzyme activities corresponded with fruit softening. Different genes within a multigene family played distinct roles in the synthesis of phenolics. C4H1, 4CL2, 4CL9, HCT, CCoAOMT5, F5H, COMT1, CAD6, and POD42 were implicated in the regulation of neochlorogenic acid synthesis and accumulation. Consequently, these findings enhance our understanding of phenolic metabolism and offer fresh perspectives on the development of germplasm resources for white-fleshed loquats.

Urban green spaces (UGSs) satisfy citizens’ physical and psychological demands and are considered an integral part of sustainable urban development. However, the distribution of UGS is often uneven, especially in historic urban areas with high building density and limited facilities, thus leading to issues of green inequity. This study examines two dimensions of green equity in Qingdao’s historic urban area, distributional equity and perceived equity, based on a fine-grained division of units and districts. Distributional equity is analyzed using the Gaussian two-step floating catchment area (G2SFCA) method and Gini coefficient to accurately calculate the equity in distribution and accessibility of UGSs. The perceived equity is assessed through the green view index (GVI) and location quotient of the streets, which represents citizens’ visual perception of green quality. Based on these analyses, a dual-perspective evaluation model of green equity is conducted, and the results show a significant imbalance of greenery supply and population demand in the historical urban area of Qingdao. This disequilibrium in green spaces leads to 62.20% of people living with low green equity, while only 8.12% experience high green equity. To maximize social justice, priority should be given to improving the 15 districts with low green equity; doing so could effectively reduce green inequity within historic urban areas where facilities and resources are relatively scarce, thereby improving the efficiency of urban renewal efforts.

A terahertz (THz) metamaterial design mechanism based on a stacked chip is proposed. Unlike the traditional sandwich-type metamaterial design mechanism based on the “resonant layer–dielectric layer–ground layer” structure, it adopts a stacked design of upper and lower metamaterial chips to achieve a new structure based on the “dielectric layer–resonant layer–air layer–ground layer” structure. This could break through the thickness limitations and construct an ultra-thin metamaterial upper chip. To verify the effectiveness of this method, we applied it to the field of THz perfect absorbers. We designed, simulated, and prepared a terahertz stacked chip-based perfect absorber with an upper-chip thickness less than 1/800 of the wavelength. Then, a reflective spectroscopy system based on a vector network analyzer is built to test the absorption performance. The measured results show that it has an absorptivity of 98.4% at 0.222 THz, which is in good agreement with simulations.

Species in Ectrichodiinae are known for their prey specialization on millipedes. However, knowledge of the morphological adaptations to this unique feeding habit was limited. In the current study, we examined the microstructures of the antennae, mouthparts, and legs of four millipede feeding ectrichodiines, Ectrychotes andreae (Thunberg, 1888), Haematoloecha limbata Miller, 1953, Labidocoris pectoralis (Stål, 1863), and Neozirta eidmanni (Taueber, 1930), and compared them with those of three species of tribelocephalines, a group closely related to Ectrichodiinae. On the antennae, we found four types of antennal sensilla. On the mouthparts, we recognized four types of labial sensilla. Sampled ectrichodiines have distinctly more and denser slightly transverse ridges on the external side of mandibles than tribelocephalines. E. andreae and H. limbata possess numerous small papillae fringed with densely arranged finger-print-like grains on the trochanter and femur; these probably facilitate the immobilization of prey. Overall, our study illustrates, at a microstructural level, the remarkable morphological adaption of prey manipulation in ectrichodiine, and has enhanced our understanding about stenophagy in the family Reduviidae.

There are various forms of assembly data sources for wind turbines, which contributes to the lack of a unified and standardized expression. Moreover, the reusability of historical assembly data is low, which leads to the poor reasoning ability of a new product assembly sequence. In this paper, we propose a knowledge graph-based approach for assembly sequence recommendations for wind turbines. First, for the multimodal data (text in process manual, image of tooling, and three-dimensional (3D) model) of assembly, a multi-process assembly information representation model is established to express assembly elements in a unified way. In addition, knowledge extraction methods for different modal data are designed to construct a multimodal knowledge graph for wind turbine assembly. Further, the retrieval of similar assembly process items based on the bidirectional encoder representation from transformers joint graph-matching network (BERT-GMN) is proposed to predict the assembly sequence subgraphs. Also, a Semantic Web Rule Language (SWRL)-based assembly process items inference method is proposed to automatically generate subassembly sequences by combining component assembly relationships. Then, a multi-objective sequence optimization algorithm for the final assembly is designed to output the optimal assembly sequences. Finally, taking the VEU-15 wind turbine as the object, the effectiveness of the assembly process information modeling and part multi-source information representation is verified. Sequence recommendation results are better quality compared to traditional assembly sequence planning algorithms. It provides a feasible solution for wind turbine assembly to be optimized from multiple objectives simultaneously.

The adaptive capacity of tree species is crucial for their survival under environmental change. Liushan (Cryptomeria japonica var. sinensis), an allogamous conifer species, is widely distributed across southern China. However, despite its broad distribution, there have been few investigations on the geographical variation and environmental adaptability of this species. Here, we combined the phenotypic (eight needle traits) and genetic data (14 nSSR loci) to fill this gap by assessing the genetic variation of geographical populations and exploring environmental adaptations of this species. Both phenotypic and molecular genetic analyses indicated a strong genetic differentiation among geographic populations. All populations could be clustered into three groups that were consistent with their geography. Most of the needle traits showed significantly correlated with geography and environmental factors. Geographical isolation and environmental differences are the main factors that have shaped current morphological traits and patterns of genetic variation. We suggest conservation measures to be implemented on a population level with existing populations, especially those with rare phenotypes as the main goal. Our findings shed light on the geographic variation in Liushan and expanded the knowledge of its putative adaptive mechanisms, ultimately benefiting the conservation of this species.

Scale properties and energy dissipation in the turbulent energy transfer process play an important role in deeply understanding the features of ocean turbulence. In this paper, a universal multifractal cascade model is applied to investigate scale and intermittency properties of a turbulent flow, and two sets of measured turbulence datasets in horizontal and vertical directions are performed for comprehensive experimental verification. First, an empirical mode decomposition method is utilized to adaptively decompose microstructure shear time series into several intrinsic mode functions. Then, the multifractal spectrum is calculated to extract multifractal features for different time scales. The ocean microstructure field shows an asymmetric structure with a left truncation and a long right tail in different directions. This proves that most energy transfer processes occur on small scales. Finally, the calculated multifractal indexes of all intrinsic mode functions for two datasets show that the intermittency of turbulence decreases with the increase in time scales, which reflects the multifractal intensity and the level of intermittency of turbulence. The multifractal cascade model can successfully build a bridge between intermittency and dissipation in the multiscale energy cascade process.

Polyamines (PAs) are ubiquitous low-molecular-weight aliphatic polycations in all living organisms, which are crucial for plant response to abiotic and biotic stresses. The role of PAs in plant disease resistance has been well documented. However, their involvement in plant–pest interactions remains unclear. Here, the role of PAs in rice against striped stem borer (SSB, Chilo suppressalis Walker), a destructive pest in rice production worldwide, was investigated. SSB larval infestation led to a substantial accumulation of free putrescine (Put) in rice seedlings, which was in parallel with an elevated expression of host PA biosynthesis genes Arginine Decarboxylase1 (ADC1) and ADC2. Moreover, SSB larval oral secretion application with wounding further raised the transcripts of ADC1 and ADC2 in rice compared with wounding treatment alone. The larval growth on both rice plants and artificial diet was promoted by the exogenous application of PA and inhibited by a PA biosynthesis inhibitor. On the other hand, the rice defense responses, including polyphenol oxidase (PPO) and peroxidase (POD) activities, as well as protease inhibitor level, were enhanced by a Put supplement and reduced by an ADC inhibitor. Our results indicate that SSB herbivory triggers polyamine accumulation in host rice plants, which is beneficial to SSB in rice–SSB interaction.

The exploration of low-cost, high-performance adsorbents is a popular research issue. In this work, a straightforward method that combined hydrothermal with tube firing was used to produce Osmanthus fragrans biomass charcoal (OBC) from low-cost osmanthus for dye adsorption in water. The study examined the parameters of starting concentration, pH, and duration, which impacted the process of adsorption of different dyes by OBC. The analysis showed that the adsorption capacities of OBC for six dyes: malachite green (MG, C0 = 800 mg/L, pH = 7), Congo red (CR, C0 = 1000 mg/L, pH = 8), rhodamine B (RhB, C0 = 500 mg/L, pH = 6), methyl orange (MO, C0 = 1000 mg/L, pH = 7), methylene blue (MB, C0 = 700 mg/L, pH = 8), and crystalline violet (CV, C0 = 500 mg/L, pH = 7) were 6501.09, 2870.30, 554.93, 6277.72, 626.50, and 3539.34 mg/g, respectively. The pseudo-second-order model and the Langmuir isotherm model were compatible with the experimental findings, which suggested the dominance of ion exchange and chemisorption. The materials were characterized by using XRD, SEM, FTIR, BET, and XPS, and the results showed that OBC had an outstanding specific surface area (2063 m2·g–1), with potential adsorption mechanisms that included electrostatic mechanisms, hydrogen bonding, and π-π adsorption. The fact that the adsorption capacity did not drastically decrease after five cycles of adsorption and desorption suggests that OBC has the potential to be a dye adsorbent.

The litchi downy blight disease of litchi caused by Peronophythora litchii accounts for severe losses in the field and during storage. While ample quantitative studies have shown that 6-pentyl-2H-pyran-2-one (6PP) possesses antifungal activities against multiple plant pathogenic fungi, the regulatory mechanisms of 6PP-mediated inhibition of fungal pathogenesis and growth are still unknown. Here, we investigated the potential molecular targets of 6PP in the phytopathogenic oomycetes P. litchii through integrated deployment of RNA-sequencing, functional genetics, and biochemical techniques to investigate the regulatory effects of 6PP against P. litchii. Previously we demonstrated that 6PP exerted significant oomyticidal activities. Also, comparative transcriptomic evaluation of P. litchii strains treated with 6PP Revealed significant up-regulations in the expression profile of TOR pathway-related genes, including PlCytochrome C and the transcription factors PlYY1. We also noticed that 6PP treatment down-regulated putative negative regulatory genes of the TOR pathway, including PlSpm1 and PlrhoH12 in P. litchii. Protein-ligand binding analyses revealed stable affinities between PlYY1, PlCytochrome C, PlSpm1, PlrhoH12 proteins, and the 6PP ligand. Phenotypic characterization of PlYY1 targeted gene deletion strains generated in this study using CRISPR/Cas9 and homologous recombination strategies significantly reduced the vegetative growth, sporangium, encystment, zoospore release, and pathogenicity of P. litchii. These findings suggest that 6PP-mediated activation of PlYY1 expression positively regulates TOR-related responses and significantly influences vegetative growth and the virulence of P. litchii. The current investigations revealed novel targets for 6PP and underscored the potential of deploying 6PP in developing management strategies for controlling the litchi downy blight pathogen.

As a biological characteristic, gait uses the posture characteristics of human walking for identification, which has the advantages of a long recognition distance and no requirement for the cooperation of subjects. This paper proposes a research method for recognising gait images at the frame level, even in cases of discontinuity, based on human keypoint extraction. In order to reduce the dependence of the network on the temporal characteristics of the image sequence during the training process, a discontinuous frame screening module is added to the front end of the gait feature extraction network, to restrict the image information input to the network. Gait feature extraction adds a cross-stage partial connection (CSP) structure to the spatial–temporal graph convolutional networks’ bottleneck structure in the ResGCN network, to effectively filter interference information. It also inserts XBNBlock, on the basis of the CSP structure, to reduce estimation caused by network layer deepening and small-batch-size training. The experimental results of our model on the gait dataset CASIA-B achieve an average recognition accuracy of 79.5%. The proposed method can also achieve 78.1% accuracy on the CASIA-B sample, after training with a limited number of image frames, which means that the model is more robust.

Although the spectrum sensing algorithms based on deep learning have achieved remarkable detection performance, the sensing performance is easily affected by adversarial attacks due to the fragility of neural networks. Even slight adversarial perturbations lead to a sharp deterioration of the model detection performance. To enhance the defense capability of the spectrum sensing model against such attacks, an unsupervised learning-based spectrum sensing algorithm with defending adversarial attacks (USDAA) is proposed, which is divided into two stages: adversarial pre-training and fine-tuning. In the adversarial pre-training stage, encoders are used to extract the features of adversarial samples and clean samples, respectively, and then decoders are used to reconstruct the samples, and comparison loss and reconstruction loss are designed to optimize the network parameters. It can reduce the dependence of model training on labeled samples and improve the robustness of the model to attack perturbations. In the fine-tuning stage, a small number of adversarial samples are used to fine-tune the pre-trained encoder and classification layer to obtain the spectrum sensing defense model. The experimental results show that the USDAA algorithm is better than the denoising autoencoder and distillation defense algorithm (DAED) against FGSM and PGD adversarial attacks. The number of labeled samples used in USDAA is only 11% of the DAED. When the false alarm probability is 0.1 and the SNR is −10 dB, the detection probability of the USDAA algorithm for the fast gradient sign method (FGSM) and the projected gradient descent (PGD) attack samples with random perturbations is above 88%, while the detection probability of the DAED algorithm for both attack samples is lower than 69%. Additionally, the USDAA algorithm has better robustness to attack with unknown perturbations.

Kiwifruit (Actinidia spp.) is susceptible to waterlogging stress. Although abundant wild germplasm resources exist among Actinidia plants for improving the waterlogging tolerance of kiwifruit cultivars, the underlying mechanisms remain largely unknown. Here, a comparative study was undertaken using one wild germplasm, Maorenshen (A. valvata Dunn, MRS), and one cultivar, Miliang-1 (A. chinensis var. deliciosa (A.Chev.) A.Chev. cv. Miliang-1, ML). Under stress, the ML plantlets were seriously damaged with wilted chlorotic leaves and blackened rotten roots, whereas the symptoms of injury in the MRS plantlets were much fewer, along with higher photosynthetic rates, chlorophyll fluorescence characteristics and root activity under stress conditions. However, neither aerenchyma in the root nor adventitious roots appeared in both germplasms upon stress exposure. The activities of pyruvate decarboxylase (PDC) and alcohol dehydrogenase (ADH), as well as their transcript levels, were constitutively higher in MRS than those in ML under both normal and stress conditions. Waterlogging stress significantly enhanced the PDC and ADH enzyme activities in both germplasms, which were 60.8% and 22.4% higher in the MRS roots than those in the ML roots under waterlogging stress, respectively. Moreover, MRS displayed higher activities of antioxidant enzymes, including SOD, CAT, and APX, as well as DPPH-radical scavenging ability, and decreased H2O2 and MDA accumulation under both normal and stress conditions. Our findings suggest that the waterlogging tolerance of the wild A. valvata germplasm was associated with high PDC and ADH, as well as antioxidant ability.

This study examines the impact of surface defects on the electro-explosive properties of metal explosive foil transducers. Specifically, it focuses on the effects of defects in the bridge foil and their influence on the electrical explosion time and transduction efficiency. To analyze these effects, a current-voltage simulation model is developed to simulate the behavior of a defective bridge foil. The simulation results are validated through experimental current-voltage measurements at both ends of the bridge area. The findings reveal that the presence of through-hole defects on the surface of the bridge foil leads to an advancement in the electrical explosion time and a reduction in the transduction efficiency of the bridge foil. A performance comparison is made between the defective bridge foil and a defect-free copper foil. As observed, a through-hole defect with a radius of 20 μm results in a 1 ns advance in the blast time and a 1.52% decrease in energy conversion efficiency. Similarly, a through-hole defect with a radius of 50 μm causes a 51 ns advancement in the blast time and a 13.96% reduction in the energy conversion efficiency. These findings underscore the detrimental effects of surface defects on the electro-explosive properties, emphasizing the importance of minimizing defects to enhance their performance.

Fermented shrimp paste is a popular food in Asian countries. However, biogenic amines (BAs) are a typically associated hazard commonly found during the fermentation of shrimp paste and pose a food-safety danger. In this work, an autochthonic salt-tolerant Tetragenococcus muriaticus TS (T. muriaticus TS) strain was used as a starter culture for grasshopper sub shrimp paste fermentation. It was found that with the starter culture, putrescine, cadaverine, and histamine concentrations were significantly lower (p < 0.05) with a maximal reduction of 19.20%, 14.01%, and 28.62%, respectively. According to high-throughput sequencing data, T. muriaticus TS could change the interactions between species and reduce the abundance of bacterial genera positively associated with BAs, therefore inhibiting the BA accumulation during shrimp paste fermentation. Moreover, the volatile compounds during the fermentation process were also assessed by HS-SPME-GC-MS. With the starter added, the content of pyrazines increased, while the off-odor amines decreased. The odor of the shrimp paste was successfully improved. These results indicate that T. muriaticus TS can be used as an appropriate starter culture for improving the safety and quality of grasshopper sub shrimp paste.

The long–term stability of proton conductors is one of the most important factors in evaluating materials. Guest molecules can act as “bridges” for proton conduction channels and reside in the channels of covalent organic frameworks, but they are prone to leakage. Therefore, it is important to develop proton conductors with intrinsic proton conductivity. In this paper, we synthesized an intrinsically sulfonated covalent organic framework, TpPa–SO3H, which has a more stable proton conducting performance than that of TpPa@H2SO4 by loading guest molecules. Meanwhile, the proton conductivity of TpPa–SO3H was further improved by coating a superabsorbent polymer through an in situ reaction to obtain PANa@TpPa–SO3H (PANa: sodium polyacrylate). As a result, the modified composite exhibits an ultrahigh proton conductivity of 2.33 × 10−1 S cm−1 at 80 °C under 95% relative humidity (RH). The stability of PANa@TpPa–SO3H makes it an efficient proton transport platform with excellent proton conductivity and long–term durability.

This study focuses on the development of more cropping systems in response to global warming and food security concerns. A two-year field experiment (2017–2018) was conducted to investigate the effects of greenhouse gases (GHGs), soil environmental factors and yield on traditional double-cropping rice (DR), maize rice (MR) and ratooning rice (Rr). The results showed a significant annual effect of temperature and rainfall on GHG emissions under different cropping systems. Annual CH4 emissions under MR and Rr were significantly lower than under DR. Compared to DR, the highest cumulative N2O emissions were observed in MR (14.9 kg·ha−1) with a reduction of 23.7% in Rr. In addition, the upland crops significantly reduced CH4 emissions for late rice, while N2O emissions increased by 20.6%. Compared with DR and Rr, global warming potential (GWP) and greenhouse gas intensity (GHGI) were significantly lower for MR (p < 0.05). Meanwhile, the annual yield of MR (16.40 t·ha−1) was 8.1% and 2.4% higher than that of DR and Rr, respectively. This study further found that soil temperature and NH4+-N content were positively correlated with CH4 and N2O emissions, and soil moisture was positively correlated with N2O emission. Thus, we concluded that MR has the greatest potential to improve crop yield and mitigate GHG emissions in central China.

As global inflation escalates and geopolitical conflicts exacerbate, the world’s economy confronts an intensified degree of instability. In this volatile environment, blockchain currencies emerge as a potential bulwark, offering both value preservation and liquidity benefits. However, the conventional “mining” process introduces significant challenges, such as high energy consumption, data security risks, and detachment from the real economy, which potentially facilitate financial capital manipulation. This research endeavors to mitigate these issues, constructing an innovative blockchain cryptocurrency framework that integrates mining and distribution with intelligent big data. It also incorporates social contributions from individuals in domains such as health, knowledge, and ecological conservation. Consequently, the efficiency of cryptocurrency production and distribution correlates with the individual’s societal contribution. The more substantial the contribution, the higher the intrinsic value of the individual and the more efficient the access. Utilizing a comprehensive framework of mathematical modeling, computer numerical simulation, and fuzzy integrated evaluation, we propose a novel endogenous-value blockchain cryptocurrency system. We quantify and optimize variables such as individual intrinsic value, community efficiency, redistribution weights, and total monetary potential. We introduce an innovative method for accumulating time-decaying values such as knowledge contribution and establish an anti-cheating framework. Our results indicate that this pioneering approach can significantly enhance mining efficiency and optimize cryptocurrency distribution. This counters traditional criticisms of blockchain currencies and paves the way for a more sustainable, fair, and efficient model for future blockchain currency systems.