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Abstract Background Chilling stress is a key abiotic stress that severely restricts the growth and quality of melon (Cucumis melo L.). Few studies have investigated the mechanism of response to chilling stress in melon. Results We characterized the physiological, transcriptomic, and metabolomic response of melon to chilling stress using two genotypes with different chilling sensitivity (“162” and “13-5A”). “162” showed higher osmotic regulation ability and antioxidant capacity to withstand chilling stress. Transcriptome analysis identified 4395 and 4957 differentially expressed genes (DEGs) in “162” and “13-5A” under chilling stress, respectively. Metabolome analysis identified 615 and 489 differential enriched metabolites (DEMs) were identified in “162” and “13-5A” under chilling stress condition, respectively. Integrated transcriptomic and metabolomic analysis showed enrichment of glutathione metabolism, and arginine (Arg) and proline (Pro) metabolism, with differential expression patterns in the two genotypes. Under chilling stress, glutathione metabolism-related DEGs, 6-phosphogluconate dehydrogenase (G6PDH), glutathione peroxidase (GPX), and glutathione s-transferase (GST) were upregulated in “162,” and GSH conjugates (L-gamma-glutamyl-L-amino acid and L-glutamate) were accumulated. Additionally, “162” showed upregulation of DEGs encoding ornithine decarboxylase, Pro dehydrogenase, aspartate aminotransferase, pyrroline-5-carboxylate reductase, and spermidine synthase and increased Arg, ornithine, and Pro. Furthermore, the transcription factors (TFs), MYB, ERF, MADS-box, and bZIP were significantly upregulated, suggesting their crucial role in chilling tolerance of melon. Conclusions These findings elucidate the molecular response mechanism to chilling stress in melon and provide insights for breeding chilling-tolerant melon.

The development of virus-resistant melon varieties not only poses challenges in balancing melon quality and resistance but also contributes to sustainable agricultural development. This research focuses on the exploration and application of various breeding techniques to enhance the virus resistance of melon varieties. Molecular markers associated with virus resistance genes have been identified and utilized in marker-assisted selection, enabling more efficient and targeted breeding. Genetic engineering approaches have also shown promise, introducing specific resistance genes into melon genomes. In addition, traditional breeding methods, such as hybridization and selection, continue to play an important role in creating virus-resistant melon lines. The combination of these approaches holds great potential for developing melon varieties with improved virus resistance, thereby increasing yield and quality, and reducing the economic losses caused by viral infections in melon production.

Abstract Skeleton‐based action recognition methods commonly employ graph neural networks to learn different aspects of skeleton topology information However, these methods often struggle to capture contextual information beyond the skeleton topology. To address this issue, a Scene Context‐aware Graph Convolutional Network (SCA‐GCN) that leverages potential contextual information in the scene is proposed. Specifically, SCA‐GCN learns the co‐occurrence probabilities of actions in specific scenarios from a common knowledge base and fuses these probabilities into the original skeleton topology decoder, producing more robust results. To demonstrate the effectiveness of SCA‐GCN, extensive experiments on four widely used datasets, that is, SBU, N‐UCLA, NTU RGB + D, and NTU RGB + D 120 are conducted. The experimental results show that SCA‐GCN surpasses existing methods, and its core idea can be extended to other methods with only some concatenation operations that consume less computational complexity.

Band selection (BS) is an effective dimensionality reduction technique for hyperspectral images. Although many relevant methods have been proposed, they often only focus on the bandwise information and the correlation between the bands, and few of them pay attention to the manifold preservation in low-dimensional space, which may lead to the intrinsic structure of the data being damaged. In this article, we propose a novel method called sparse principal component analysis and adaptive multigraph learning (SPCA-AMGL) to address this issue. First, it applies SPCA to the BS task to learn the projection weight matrix, which utilizes the orthogonal constraint to remove redundant bands and uses the $ {L}_{\text{2,1}}$ norm to impose a sparse regularization on the weight matrix to ensure the selection of effective bands. Then, to select the bands with manifold preserving capability, AMGL is proposed to capture the local neighbor structure of data by combining the benefit of multiple graphs, which can not only adaptively learn the graph structure but also obtain the analytical solution of the multigraph coefficients. Finally, an alternate iterative algorithm is designed to optimize the proposed method. Abundant experiments on three hyperspectral datasets prove the reliability and superiority of the proposed method.

Torque ripple in a brushless DC motor (BLDCM) seriously restricts its application in high-performance fields. This paper proposes a commutation torque ripple suppression strategy based on a Zeta converter. The expected output voltage of a Zeta converter that suppresses the commutation torque ripple is obtained, according to the effect of the duty ratio of the Zeta converter on the turn-off phase freewheeling duration and the turn-on phase rising duration, during commutation. Based on the analysis of the dynamic response of the Zeta converter, the Zeta converter is adjusted to ensure that the Zeta converter reaches stability in sufficient time. During the commutation, the output voltage of the Zeta converter is connected to the main circuit to reduce the torque ripple during commutation, and the expected regulated duty cycle of the Zeta converter during the next commutation is calculated to adjust the output voltage of the Zeta converter. Based on this analysis, the experimental results verify the effectiveness of the proposed method.

Amomum xanthioides, A. villosum and A. longiligulare are three medicinally important herbs that are widely cultivated in southeast Asia. The ripe fruits of all three species are not only used worldwide in treatments for gastrointestinal diseases, but are also popular condiments in cooked food. In this study, we determined and analyzed the complete chloroplast (cp) genome sequences of these three Amomum species. The sizes of the cp genomes of A. xanthioides, A. villosum and A. longiligulare were 161,889 bp, 162,355 bp, and 161,990 bp, respectively. The cp genomes of all three species displayed a typical quadripartite structure. The cp genomes of A. xanthioides, A. villosum, and A. longiligulare encoded a total of 139, 138, and 139 genes, respectively, of which 118, 117, and 118 genes were single-copy genes. These included 92 protein-coding genes, eight rRNAs, as well as 39, 38, and 39 tRNAs, respectively. A comparative analysis revealed that the cp genomes of the three Amomum species had similar characteristics and patterns of organization. However, they also varied in terms of gene content, the expansion of inverted repeats, codon usage, repeat sequences, and simple sequence repeats. A phylogenetic analysis strongly supported a sister relationship between A. xanthioides and A. villosum. Overall, the results advance understanding of the relationships among the three medicinally valuable Amomum species, and provide basic molecular information to aid conservation efforts as well as research in phylogenetics and systematics.

Abstract Animal models and static cultures of intestinal epithelial cells are commonly used platforms for exploring mercury ion (Hg(II)) transport. However, they cannot reliably simulate the human intestinal microenvironment and monitor cellular physiology in situ; thus, the mechanism of Hg(II) transport in the human intestine is still unclear. Here, a gut-on-a-chip integrated with transepithelial electrical resistance (TEER) sensors and electrochemical sensors is proposed for dynamically simulating the formation of the physical intestinal barrier and monitoring the transport and absorption of Hg(II) in situ. The cellular microenvironment was recreated by applying fluid shear stress (0.02 dyne/cm2) and cyclic mechanical strain (1%, 0.15 Hz). Hg(II) absorption and physical damage to cells were simultaneously monitored by electrochemical and TEER sensors when intestinal epithelial cells were exposed to different concentrations of Hg(II) mixed in culture medium. Hg(II) absorption increased by 23.59% when tensile strain increased from 1% to 5%, and the corresponding expression of Piezo1 and DMT1 on the cell surface was upregulated.

Recent years have witnessed tremendous progress in creating and manipulating ground-state ultracold polar molecules. However, the two-body loss regardless of the chemical reactivities is still a hurdle for many future explorations. Here, we investigate the loss suppression of nonreactive bosonic ^{23}Na^{87}Rb molecules with a circularly polarized microwave blue detuned to the rotational transition. We achieve suppression of the loss by 2 orders of magnitude with the lowest two-body loss rate coefficient reduced to 3×10^{-12} cm^{3}/s. Meanwhile, the elastic collision rate coefficient is increased to the 10^{-8} cm^{3}/s level. The large good-to-bad collision ratio has allowed us to carry out evaporative cooling of ^{23}Na^{87}Rb with an efficiency of 1.7(2), increasing the phase-space density by a factor of 10. With further improvements, this technique holds great promises for creating a Bose-Einstein condensate of ultracold polar molecules.

Ferroferric oxide (Fe3O4) is regarded to be a promising high-capacity anode material for LIBs. However, the capacity attenuates fast and the rate performance is poor due to the dramatic pulverization and sluggish charge transfer properties. To solve these problems, a simple in situ encapsulation and composite method was successfully developed to construct carbon nanotube/nanorod/nanosheet-supported Fe3O4 nanoparticles. Owing to the hierarchical architecture design, the novel structure Fe3O4@C nanocomposites effectively enhance the charge transfer, alleviate pulverization, avoid the agglomeration of Fe3O4 nanoparticles, and also provide superior kinetics toward lithium storage, thereby showing significantly improved reversibility and rate performance. The carbon nanotube/nanorod supported core-shell structure Fe3O4@C nanocomposite displays outstanding high rate capability and stable cycling performance (reversible capability of 1006, 552 and 423 mA h g−1 at 0.2, 0.5 and 1 A g−1 after running 100, 300 and 500 cycles, respectively).

Metal ions play a crucial role in many biochemical processes, and when in a state of scarcity or surplus, they can lead to various diseases. Therefore, the development of a selective, sensitive, cost-effective, and fast-responding sensor to detect metal ions is critical for in vitro medical diagnostics. In recent years, fluorescent sensors have been extensively investigated as potent kits for the effective assessment of metal ions in living systems due to their high sensitivity, selectivity, ability to perform real-time, non-invasive monitoring, and versatility. This review is an overview of recent advances in fluorescent sensors for the detection and imaging of metal ions in biosystems from 2018 to date. Specifically, we discuss their application in detecting essential metal ions and non-essential metal ions for in vitro diagnostics, living cell imaging, and in vivo imaging. Finally, we summarize remaining challenges and offer a future outlook on the above topics.

Device to device (D2D) communication has recently been established in the literature as an effective means to increase the frequency spectrum and enhance the efficiency of energy consumption in future cellular systems. However, certain issues, resulting from reusing resources in the same cell, have caused serious perturbations. We study issues pertaining to D2D communication, such as dual mode selection, channel allocation and power control, aiming at the maximization of the overall throughput of the system, while at the same time ensuring that the generated interference is kept minimized. This is an NP-Hard problem that decomposes the optimization problem into two layers: the inner layer, where the DQN algorithm is used as an indicator of the optimal transmission power that should be allocated to the D2D pairs in accordance with their mode of operation, and the outer layer, where strategic decisions, such as which communication mode to use and how to allocate the channels, are made. We have proved the superiority of the proposed scheme, in terms of both system throughput and performance, through simulating experiments involving different scenarios.

When it comes to selecting an optimal defense strategy for an intrusion detection system of a wireless sensor network, such challenges as those brought about by the diversification of the attack methods and the expanded database of the attack patterns have to be dealt with. To overcome those challenges, this paper combines realistic bounded rationality with the incomplete information of the attack-defense players by employing evolutionary game theory as a tool. Firstly, an attack-defense evolutionary game model considering three types of population, in which attackers are subdivided by the source of the threat into external attackers and selfish nodes, is proposed. The sets of player types and the game strategies in our model can be extended from $2\times2$ to $\text{n}\times $ m $\times $ l. The sensitivity of the evolutionary population to similar strategies, which reflects the efficiency change in the multi-agent learning process, is depicted by a replicator dynamic equation especially optimized for this purpose by the introduction of an enhanced cooperation mechanism. In essence, an optimal defense strategy selection algorithm is provided by calculating the evolutionary stable equilibrium and a description of the evolutionary trajectory of the players over time is obtained. Moderate security and proactive defense in the form of support decisions have been provided by our method for wireless sensor networks. Experimental results have verified the validity of our method. Moreover, the optimized algorithm has solved the problem that an excessively large database of attack patterns affects the speed of switching to the optimal defense decision strategy and the learning efficiency of the evolutionary game replicator dynamic mechanism is not fast enough.

Advanced carbon materials have played an important function in the field of energy conversion and storage. The green and low-carbon synthesis of elemental carbon with controllable morphology and microstructure is the main problem for carbon materials. Herein, we develop a green and low-carbon method to synthesize porous carbon by reacting CO2 with LiAlH4 at low temperatures. The starting reaction temperatures are as low as 142, 121, and 104 °C for LiAlH4 reacting with 1, 30, and 60 bar CO2, respectively. For the elemental carbon, the porosity of elemental carbon gradually decreased, whereas its graphitization degree increased as the CO2 pressure increased from 1 bar to 60 bar. CO2 serves as one of the two reactants and the CO2 pressure can adjust the thermodynamic and kinetic properties of the formation reaction for synthesizing elemental carbon. The mechanism for CO2 pressure-dependent microstructure and morphology of carbon is discussed on the basis of the formation reaction of elemental carbon and gas blowing effect of H2 and CO2. The elemental carbon with different morphology and microstructure exhibits distinct electrochemical lithium storage performance including reversible capacity, rate capability, cycling stability, and Coulombic efficiency, owing to their different lithium storage mechanism. The elemental carbon synthesized at 30 bar CO2 delivers the highest reversible capacity of 506 mAh g−1 after 1000 cycles even at 1.0 A g−1. Advanced energy storage technology based on the green and low-carbon synthesis of carbon materials is a requisite for providing a stable and sustainable energy supply to meet the ever-growing demand for energy.

We investigate the low-energy scattering properties of two identical particles interacting via the polarized quadrupolar interaction. It is shown that a series of s - and p -wave resonances appear for identical bosons and fermions, respectively, as the strength of the quadrupolar interaction increases. Interestingly, scattering resonances also appear on the generalized scattering length corresponding to the coupling between the s and d waves. This observation inspires us to propose a new pseudopotential for the quadrupolar interaction. We also explore the bound-state properties of two particles in both free space and harmonic traps.

This study focuses on an investigation of the operating performance and pollutant emission characteristics of a micro gas turbine combined cycle using biomass gas, replacing natural gas. The models of both recuperative cycle micro gas turbines with a waste heat utilization system and a micro gas-steam turbine combined cycle system are established. When the gas turbine works at 100 kW and the same types of fuel are burnt, the recuperative cycle system consumes less fuel than the gas-steam combined cycle system. The electric efficiency of the recuperative cycle system can reach more than 29%, which is higher than 24% of the gas-steam combined system. The combined cycle thermal efficiency of the recuperative system is as high as 66%, with 36% waste heat utilization efficiency. The electrical efficiency of the recuperative cycle system in the biomass gas case decreases, while that of the gas-steam combined cycle system undergoes little change. When the gas turbine power output increases from 50 kW to 100 kW, the electrical efficiency and combined cycle thermal efficiency increases, but the thermal efficiency of waste heat utilization of recuperative cycle decreases, the NOX and SO2 emissions gradually rise. Under the same working conditions, the NOX emissions of the recuperative cycle system are greater than that of the steam-gas combined cycle system.

DNA methylation regulates key biological processes in plants. In this study, kenaf seedlings were pretreated with the DNA methylation inhibitor 5-azacytidine (5-azaC) (at concentrations of 0, 100, 200, 400, and 600 μM), and the results showed that pretreatment with 200 μM 5-azaC promoted flowering most effectively. To elucidate the underlying mechanism, phytohormone, adenosine triphosphate (ATP), and starch contents were determined, and genome-wide DNA methylation and transcriptome analyses were performed on anthers pretreated with 200 μM 5-azaC (5-azaC200) or with no 5-azaC (control conditions; 5-azaC0). Biochemical analysis revealed that 5-azaC pretreatment significantly reduced indoleacetic acid (IAA) and gibberellic acid (GA) contents and significantly increased abscisic acid (ABA) and ATP contents. The starch contents significantly increased in response to 200 and 600 μM 5-azaC. Further genome-wide DNA methylation analysis revealed 451 differentially methylated genes (DMGs) with 209 up- and 242 downregulated genes. Transcriptome analysis showed 3,986 differentially expressed genes (DEGs), with 2,171 up- and 1,815 downregulated genes. Integrated genome-wide DNA methylation and transcriptome analyses revealed 72 genes that were both differentially methylated and differentially expressed. These genes, which included ARFs, PP2C, starch synthase, FLC, PIF1, AGL80, and WRKY32, are involved mainly in plant hormone signal transduction, starch and sucrose metabolism, and flowering regulation and may be involved in early flowering. This study serves as a reference and theoretical basis for kenaf production and provides insights into the effects of DNA methylation on plant growth and development.

Over the past decades, RNA viruses have been threatened people’s health and led to global health emergencies. Significant progress has been made in diagnostic methods and antiviral therapeutics for combating RNA viruses. ELISA and RT-qPCR are reliable methods to detect RNA viruses, but they suffer from time-consuming procedures and limited sensitivities. Vaccines are effective to prevent virus infection and drugs are useful for antiviral treatment, while both need a relatively long research and development cycle. In recent years, CRISPR-based gene editing and modifying tools have been expanded rapidly. In particular, the CRISPR-Cas13 system stands out from the CRISPR-Cas family due to its accurate RNA-targeting ability, which makes it a promising tool for RNA virus diagnosis and therapy. Here, we review the current applications of the CRISPR-Cas13 system against RNA viruses, from diagnostics to therapeutics, and use some medically important RNA viruses such as SARS-CoV-2, dengue virus, and HIV-1 as examples to demonstrate the great potential of the CRISPR-Cas13 system.

ObjectivesThis study aimed to determine the HBV infection status of 135 patients with DLBCL (diffuse large B cell lymphoma), to analyze the overall survival (OS) and progression-free survival (PFS) of the different HBV infection status groups, and to discuss the relationship between HBV serological test results and the prognosis of DLBCL patients.MethodsA retrospective analysis was performed of the clinical data, HBV serological test results, and PFS/OS of 135 DLBCL patients who were initially diagnosed and treated with more than 3 cycles of an R-CHOP/CHOP/CHOP-like regimen at our center from January 1, 2008 to December 31, 2012.ResultsThe patients in the HBV infection group were older at disease onset (≥60 years old) and were more likely to present with stage 3-4 disease compared with the HBV-free group (P = 0.030 and P = 0.025, respectively). Approximately 50% of the patients with an active HBV infection required a reduction in the chemotherapy dose, and 66.7% of the patients in this group received more than 1 line of therapy; these rates were significantly higher than those in the no infection group (P = 0.003 and P = 0.011, respectively). Although HBV infection had no obvious influence on the outcome of first-line therapy, patients with an inactive infection had a higher relapse/progression rate within 3 months after a CR/PR than patients with an active infection (14/20 vs. 1/12, P = 0.001). The PFS at 1 year, 3 years and OS rates at 1 year, 3 years were significantly lower in the active HBV infection group than in the HBV-free group (P = 0.008, P = 0.002, P = 0.004, and P = 0.002, respectively). The PFS rates at 1 year and 3 year in HBV-free group were higher than those in the HBV infection group (80.5% and 52.9% P = 0.001, 78.1% and 44.4% P = 0.002). The lymphoma-related mortality rates were 2.7% in the no infection group, 19.2% in the HBV infection group (P = 0.004), and 28.6% in the active HBV infection group (P = 0.001). Among the patients treated with MabThera, the PFS in the HBV infection group was 11 months in the HBV infection group and 67 months in the infection-free group (P = 0.000). A Cox regression model of PFS revealed that age ≥60 years and HBV infection were independent prognostic factors (age: P = 0.019, HR = 2.002, 95% CI 1.123-3.567; HBV infection: P = 0.026, HR = 0.494, 95% CI 0.265-0.919).ConclusionCompared with the patients in HBV-free group, those in the HBV infection group were older at disease onset, and the active infection patients presented with more advanced disease and had a lower PFS at 1, 3 years as well as a lower OS at 3 years. The patients in the inactive infection group had a higher progression/relapse rate within 3 months after a CR/PR than those in the active infection group. HBV infection was an unfavorable factor for PFS in the MabThera group. An age ≥60 years and HBV infection were independent unfavorable prognostic factors for PFS.

China has a long history in library classifications, although modern classifications did not emerge until one hundred years ago when the Western classifications were introduced into the country. The Classification for Chinese Libraries (CCL) was developed after years of collective work. The purposes of this article are to review the ancient history and modern efforts in developing Chinese library classifications, examine the organizations, accomplishments and problems of the CCL especially in the areas of philosophy and social sciences, and compare the CCL with the Library of Congress Classification (LCC) in terms of their structures.

Owing to the global spread of the coronavirus disease 2019 (COVID-19), education has shifted to distance online learning, whereas some face-to-face courses have been resumed with the improvement of the outbreak prevention and management situation, including a laboratory course for senior undergraduate students in chemical biology. Here, we present an innovative chemical biology experiment covering COVID-19 topics, which was created for third-year undergraduates. The basic principles of two nucleic-acid- and antigen-based diagnostic techniques for SARS-CoV-2 are demonstrated in detail. These experiments are designed to provide students with comprehensive knowledge of COVID-19 and related diagnoses in daily life. Crucially, the biosafety of this experimental manipulation was ensured by using artificial nucleic acids and recombinant protein. Furthermore, an interactive hybrid online-facing teaching model was designed to cover the key mechanism regarding PCR and serological tests of COVID-19. Finally, a satisfactory evaluation was obtained through a questionnaire, and simultaneously, reasonable improvements to the course design were suggested. The proposed curriculum provides all the necessary information for other instructors to create new courses supported by research.

無Selecting automated library systems is a complex and often difficult process that most library administrators will have to go through, and different libraries usually took different approaches. This study is to identify the factors that influence library administrators' decision-making process regarding library automation. The most significant attitude changes between librarians with automated systems already in their libraries and those without automation occurred in the areas of system cost and vendor selection. Administrators from libraries without automation considered the system cost to be the dominant factor, while librarians with automated systems operating in their libraries had learned from their experience and put much more emphasis on performance, and were more willing to search for the computer system that would best meet their needs.

無Effective electronic resource sharing is critical to library information services of the 1990s. Explosion of data and increased cost of information force libraries to work together, and technological advancements present the library service profession a platform for resource sharing. The Palladian Alliance Project of the Associated Colleges of the South is designed to provides ACS member institutions an effective means to enhance information access for their faculty and students, and achieve significant cost containment in the years to come.