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Covalent organic frameworks (COFs) are typical porous organic polymers with crystalline porous architectures, which are provided with the merits of high surface area, low density, and high structural as well as functional adjustability. In comparison to conventional COFs with single-stranded linkages, ladder-type COFs are a very unique class of COFs which are usually connected by rings (conjugated or non-conjugated). Given the structural characteristics of ladder-type COFs, they overcome the shortcomings of conventional COFs and possess the advantages of rigid backbone, extended π-conjugation length, extraordinary chemical/thermal stability, and high conductivity. However, compared to the well-investigated conventional COFs, ladder-type COFs are paid little attention. Gaining ladder-type COFs quickly and efficiently encounters great challenges. Ladder-type COFs, containing a wide array of structures and functionalities, have recently come into focus. Especially for energy conversion and storage, they show great potential with excellent performances. Accordingly, this article systematically summarizes the recent developments in constructing ladder-type COFs. Initially, the topology design is generally introduced. Subsequently, the synthesis of ladder-type COFs is discussed in detail. It shows how to rationally select organic reactions and monomers and how to manipulate experimental conditions to construct ladder-type COFs bearing different functional groups and different conjugation lengths. Ultimately, this paper offers a concise outlook on the prospective advancements in the synthesis of ladder-type COFs.

Nickel/iron-layered double hydroxide (NiFe-LDH) tends to undergo an electrochemically induced surface reconstruction during the water oxidation in alkaline, which will consume excess electric energy to overcome the reconstruction thermodynamic barrier. In the present work, a novel ultrasonic wave-assisted Fenton reaction strategy is employed to synthesize the surface reconstructed NiFe-LDH nanosheets cultivated directly on Ni foam (NiFe-LDH/NF-W). Morphological and structural characterizations reveal that the low-spin states of Ni2+ (t2g6eg2) and Fe2+ (t2g4eg2) on the NiFe-LDH surface partially transform into high-spin states of Ni3+ (t2g6eg1) and Fe3+ (t2g3eg2) and formation of the highly active species of NiFeOOH. A lower surface reconstruction thermodynamic barrier advantages the electrochemical process and enables the NiFe-LDH/NF-W electrode to exhibit superior electrocatalytic water oxidation activity, which delivers 10 mA cm−2 merely needing an overpotential of 235 mV. Besides, surface reconstruction endows NiFe-LDH/NF-W with outstanding electrooxidation activities for organic molecules of methanol, ethanol, glycerol, ethylene glycol, glucose, and urea. Ultrasonic-assisted Fenton reaction inducing surface reconstruction strategy will further advance the utilization of NiFe-LDH catalyst in water and organics electrooxidation.

The development of dimensionally stable anodes (DSAs) has made the chlorine evolution reaction (CER) the most important industrial anode reaction since the 1960s. However, the preparation of DSA depends on the extensive use of precious metals, Ru and Ir, which are expensive and scarce. Herein, a cationic defect adsorption–oxidation anchoring strategy to immobilize oxidized sub‐nano ruthenium clusters on 2D low‐crystallinity titanium oxide (2D TiOx) substrate is reported. Through the metal oxide−support interaction, the 2D TiOx alters the electronic structure of ruthenium oxide (RuOx), improving its activity, selectivity, and stability for CER. Specifically, the mass activity of the RuOx/2D TiOx electrode is 26.5 and 143.5 times higher than that of the state‐of‐the‐art commercial RuO2 and DSA, respectively, at an overpotential of 100 mV. Moreover, the selectivity of the RuOx/2D TiOx electrode to CER is approximately 96.5%, and it exhibits remarkable durability lasting for over 210 h. Therefore, the 2D TiOx substrate holds significant potential for improving the dispersion, active site density, and atomic utilization of oxidized sub‐nano noble metal clusters.

Boron (B) deficiency has been shown to inhibit root cell growth and division. However, the precise mechanism underlying B deficiency-mediated root tip growth inhibition remains unclear. In this study, we investigated the role of BnaA3.NIP5;1, a gene encoding a boric acid channel, in Brassica napus (B. napus). BnaA3.NIP5;1 is expressed in the lateral root cap and contributes to B acquisition in the root tip. Downregulation of BnaA3.NIP5;1 enhances B sensitivity in B. napus, resulting in reduced shoot biomass and impaired root tip development. Transcriptome analysis was conducted on root tips from wild-type B. napus (QY10) and BnaA3.NIP5;1 RNAi lines to assess the significance of B dynamics in meristematic cells during seedling growth. Differentially expressed genes (DEGs) were significantly enriched in plant circadian rhythm and nitrogen (N) metabolism pathways. Notably, the circadian-rhythm-related gene HY5 exhibited a similar B regulation pattern in Arabidopsis to that observed in B. napus. Furthermore, Arabidopsis mutants with disrupted circadian rhythm (hy5/cor27/toc1) displayed heightened sensitivity to low B compared to the wild type (Col-0). Consistent with expectations, B deficiency significantly disrupted N metabolism in B. napus roots, affecting nitrogen concentration, nitrate reductase enzyme activity, and glutamine synthesis. Interestingly, this disruption was exacerbated in BnaA3NIP5;1 RNAi lines. Overall, our findings highlight the critical role of B dynamics in root tip cells, impacting circadian rhythm and N metabolism, ultimately leading to retarded growth. This study provides novel insights into B regulation in root tip development and overall root growth in B. napus.

The vibration signals collected by acceleration sensors are interspersed with noise interference, which increases the difficulty of fault diagnosis for rolling bearings. For this reason, a rolling bearing fault diagnosis method based on complete ensemble empirical model decomposition with adaptive noise (CEEMDAN) and improved convolutional neural network (CNN) is proposed. Firstly, the original vibration signal is decomposed into a series of intrinsic modal function (IMF) components using the CEEMDAN algorithm, the components are filtered according to the correlation coefficients and the signals are reconstructed. Secondly, the reconstructed signals are converted into a two-dimensional grey-scale map and input into a convolutional neural network to extract the features. Lastly, the features are inputted into a support vector machine (SVM) with the optimised parameters of the grey wolf optimiser (GWO) to perform the identification and classification. The experimental results show that the rolling bearing fault diagnosis method based on CEEMDAN and CNN-SVM proposed in this paper can significantly reduce the noise interference, and its average fault diagnosis accuracy is as high as 99.25%. Therefore, it is feasible to apply it in the field of rolling bearing fault diagnosis.

Conventional deep learning methods for fault detection often assume that the training and the testing sets share the same fault domain spaces. However, some fault patterns are rare, and many real-world faults have not appeared in the training set. As a result, it is hard for the trained model to achieve desirable performance on the testing set. In this paper, we introduce a novel domain generalization, Load-Domain (LD) domain generalization, which is based on the analysis of the Case Western Reserve University (CWRU) bearing dataset and takes advantage of the physical information of this dataset. For this scenario, we propose a feature shift model called Feature Shift Network (FSN). FSN is trained for feature shift on adjacent source domains and finally shifts target domain features into adjacent source domain feature space to achieve the purpose of domain generalization. Furthermore, through the hybrid classification method, the generalization performance of the model on unseen target domains is effectively improved. The results on the CWRU bearing dataset demonstrate that FSN is better than the existing models in the LD domain generalization. Furthermore, we have another test on the rotated MNIST, which also shows FSN can achieve the best performance.

Polyyne is an sp-hybridized linear carbon chain (LCC) with alternating single and triple carbon–carbon bonds. Polyyne is very reactive; thus, its structure can be easily damaged through a cross-linking reaction between the molecules. The longer the polyyne is, the more unstable it becomes. Therefore, it is difficult to directly synthesize long polyynes in a solvent. The encapsulation of polyynes inside carbon nanotubes not only stabilizes the molecules to avoid cross-linking reactions, but also allows a restriction reaction to occur solely at the ends of the polyynes, resulting in long LCCs. Here, by controlling the diameter of single-walled carbon nanotubes (SWCNTs), polyynes were filled with high yield below room temperature. Subsequent annealing of the filled samples promoted the reaction between the polyynes, leading to the formation of long LCCs. More importantly, single chiral (6,5) SWCNTs with high purity were used for the successful encapsulation of polyynes for the first time, and LCCs were synthesized by coalescing the polyynes in the (6,5) SWCNTs. This method holds promise for further exploration of the synthesis of property-tailored LCCs through encapsulation inside different chiral SWCNTs.

Cryptococcus neoformans (C. neoformans) is a pathogenic fungus that can cause life-threatening meningitis, particularly in individuals with compromised immune systems. The current standard treatment involves the combination of amphotericin B and azole drugs, but this regimen often leads to inevitable toxicity in patients. Therefore, there is an urgent need to develop new antifungal drugs with improved safety profiles. We screened antimicrobial peptides from the hemolymph transcriptome of Blaps rhynchopetera (B. rhynchopetera), a folk Chinese medicine. We found an antimicrobial peptide named blap-6 that exhibited potent activity against bacteria and fungi. Blap-6 is composed of 17 amino acids (KRCRFRIYRWGFPRRRF), and it has excellent antifungal activity against C. neoformans, with a minimum inhibitory concentration (MIC) of 0.81 μM. Blap-6 exhibits strong antifungal kinetic characteristics. Mechanistic studies revealed that blap-6 exerts its antifungal activity by penetrating and disrupting the integrity of the fungal cell membrane. In addition to its direct antifungal effect, blap-6 showed strong biofilm inhibition and scavenging activity. Notably, the peptide exhibited low hemolytic and cytotoxicity to human cells and may be a potential candidate antimicrobial drug for fungal infection caused by C. neoformans.

For high ground-stress soft-rock tunnels surrounding rock with large deformation, rapid deformation rate, a long creep time, and a high likelihood of to causing initial and secondary lining damage, the yielding and relief-pressure support technology of a lining filled with a granular material is proposed. A layer of granular material is placed at the reserved deformation layer of the tunnel to provide the surrounding rock with a certain amount of deformation space. Confined compression tests were undertaken to study the laws of compressive strain, load reduction law, and horizontal force variation of different granular materials under different rock stresses. The research showed that the compressibility and load reduction performance of 8 mm soil was optimal. Its maximum compressive strain reached 47.6%, and the total load reduction rate reached 71%. The yielding- and relief-pressure effects of the granular sand-filled lining support were analyzed from the angles of deflection, pressure, and energy. The results show that the highest reduction rate of deflection was 36.7%, and the greatest load reduction rate of pressure was 78%. The grainy filling material can remove part of the load imposed by the surrounding rock on the support structure of the secondary lining through yielding pressure and relief pressure, which dramatically reduces the damage to the secondary lining from the surrounding rock. The research results have specific reference significance for designing and constructing tunnel support structures.

Malate dehydrogenase (MDH; EC 1.1.1.37) plays a vital role in plant growth and development as well as abiotic stress responses, and it is widely present in plants. However, the MDH family genes have not been explored in sweet potato. In this study, nine, ten, and ten MDH genes in sweet potato (Ipomoea batatas) and its two diploid wild relatives, Ipomoea trifida and Ipomoea triloba, respectively, were identified. These MDH genes were unevenly distributed on seven different chromosomes among the three species. The gene duplications and nucleotide substitution analysis (Ka/Ks) revealed that the MDH genes went through segmental duplications during their evolution under purifying selection. A phylogenetic and conserved structure divided these MDH genes into five subgroups. An expression analysis indicated that the MDH genes were omni-presently expressed in distinct tissues and responded to various abiotic stresses. A transcription factor prediction analysis proved that Dof, MADS-box, and MYB were the main transcription factors of sweet potato MDH genes. These findings provide molecular features of the MDH family in sweet potato and its two diploid wild relatives, which further supports functional characterizations.

Anthocyanin accumulation in plants plays important roles in plant growth and development, as well as the response to environmental stresses. Anthocyanins have antioxidant properties and play an important role in maintaining the reactive oxygen species (ROS) homeostasis in plant cells. Furthermore, anthocyanins also act as a “sunscreen”, reducing the damage caused by ultraviolet radiation under high-light conditions. The biosynthesis of anthocyanin in plants is mainly regulated by an MYB-bHLH-WD40 (MBW) complex. In recent years, many new regulators in different signals involved in anthocyanin biosynthesis were identified. This review focuses on the regulation network mediated by different environmental factors (such as light, salinity, drought, and cold stresses) and phytohormones (such as jasmonate, abscisic acid, salicylic acid, ethylene, brassinosteroid, strigolactone, cytokinin, and auxin). We also discuss the potential application value of anthocyanin in agriculture, horticulture, and the food industry.

The dopamine D1 receptor (D1R) is a promising target for treating various psychiatric disorders. While upregulation of D1R activity has shown potential in alleviating motor and cognitive symptoms, orthosteric agonists have limitations, restricting their clinical applications. However, the discovery of several allosteric compounds specifically targeting the D1R, such as LY3154207, has opened new therapeutic avenues. Based on the cryo-EM structures of the D1R, we conducted molecular dynamics simulations to investigate the binding and allosteric mechanisms of LY3154207. Our simulations revealed that LY3154207 preferred the horizontal orientation above intracellular loop 2 (IL2) and stabilized the helical conformation of IL2. Moreover, LY3154207 binding induced subtle yet significant changes in key structural motifs and their neighboring residues. Notably, a cluster of residues centered around the Na+-binding site became more compact, while interactions involving the PIF motif and its neighboring residues were loosened upon LY3154207 binding, consistent with their role in opening the intracellular crevice for receptor activation. Additionally, we identified an allosteric pathway likely responsible for the positive allosteric effect of LY3154207 in enhancing Gs protein coupling. This mechanistic understanding of LY3154207’s allosteric action at the D1R paves the way for the rational design of more potent and effective allosteric modulators.

In this paper, SEPAM_HRNet, a high-resolution pose-estimation model that incorporates the squeeze-and-excitation and pixel-attention-mask (SEPAM) module is proposed. Feature pyramid extraction, channel attention, and pixel-attention masks are integrated into the SEPAM module, resulting in improved model performance. The construction of the model involves replacing ordinary convolutions with the plug-and-play SEPAM module, which leads to the creation of the SEPAMneck module and SEPAMblock module. To evaluate the model’s performance, the YOGA2022 human yoga poses teaching dataset is presented. This dataset comprises 15,350 images that capture ten basic yoga pose types—Warrior I Pose, Warrior II Pose, Bridge Pose, Downward Dog Pose, Flat Pose, Inclined Plank Pose, Seated Pose, Triangle Pose, Phantom Chair Pose, and Goddess Pose—with a total of five participants. The YOGA2022 dataset serves as a benchmark for evaluating the accuracy of the human pose-estimation model. The experimental results demonstrated that the SEPAM_HRNet model achieved improved accuracy in predicting human keypoints on both the common objects in context (COCO) calibration set and the YOGA2022 calibration set, compared to other state-of-the-art human pose-estimation models with the same image resolution and environment configuration. These findings emphasize the superior performance of the SEPAM_HRNet model.

The current manual reading of substation pointer meters wastes human resources, and existing algorithms have limitations in accuracy and robustness for detecting various pointer meters. This paper proposes a method for recognizing pointer meters based on Yolov7 and Hough transform to improve their automatic readability. The proposed method consists of three main contributions: (1) Using Yolov7 object detection technology, which is the latest Yolo technology, to enhance instrument recognition accuracy. (2) Providing a formula for calculating the angle of a square pointer meter after Hough transformation. (3) Applying OCR recognition to the instrument dial to obtain the model and scale value. This information helps differentiate between meter models and determine the measuring range. Test results demonstrate that the proposed algorithm achieves high accuracy and robustness in detecting different types and ranges of instruments. The map of the Yolov7 model on the instrument dataset is as high as 99.8%. Additionally, the accuracy of pointer readings obtained using this method exceeds 95%, indicating promising applications for a wide range of scenarios.

Al-Li alloys are ideal structural materials for the aerospace industry. However, an increasing number of Al-Li alloys have reached the end of their service life and must be recycled. Unfortunately, when vacuum distillation is used to separate Al-Li alloys, metallic lithium is difficult to condense and collect. Therefore, theoretical and experimental research on lithium condensation conditions under vacuum and vacuum distillation and condensation of Al-Li alloy to prepare metallic lithium were carried out. The results show that the optimal condensation temperature range for lithium is between 523 and 560 K. More than 99.5% metallic lithium and more than 99.97% aluminum were obtained from the Al-7.87%wt Li alloy through vacuum distillation condensation. The direct yield of lithium was above 80%. This paper, therefore, provides a new and improved method for the preparation of metallic lithium.

Bacterial conjugation constitutes a major horizontal gene transfer mechanism for the dissemination of antibiotic-resistant genes (ARGs) among human pathogens. The spread of ARGs can be halted or diminished by interfering with the conjugation process. In this study, we explored the possibility of using an rbsB gene as a single target to inhibit plasmid-mediated horizontal gene transfer in Escherichia coli by CRISPR interference (CRISPRi) system. Three single-guide RNAs (sgRNAs) were designed to target the rbsB gene. The transcriptional levels of the rbsB gene, the conjugation-related genes, and the conjugation efficiency in the CRISPRi strain were tested. We further explored the effect of the repressed expression of the rbsB gene on the quorum sensing (QS) system and biofilm formation. The results showed that the constructed CRISPRi system was effective in repressing the transcriptional level of the rbsB gene at a rate of 66.4%. The repressed expression of the rbsB gene resulted in the reduced conjugation rate of RP4 plasmid by 88.7%, which significantly inhibited the expression of the conjugation-related genes (trbBp, trfAp, traF and traJ) and increased the global regulator genes (korA, korB and trbA). The repressed rbsB gene expression reduced the depletion of autoinducer 2 signals (AI-2) by 12.8% and biofilm formation by a rate of 68.2%. The results of this study indicated the rbsB gene could be used as a universal target for the inhibition of conjugation. The constructed conjugative CRISPRi system has the potential to be used in ARG high-risk areas.

Root border cells (RBCs) are a group of cells that originated from the root cap meristem, which are developed by genetic regulation and play a variety of biological functions. Being composed of a homologous single cell population with high metabolic activity and intact cell walls, RBCs represent a highly useful tool for studying various aspects of plant mineral absorption and utilization, as well as plant-soil-microbiome interactions in the rhizosphere. Research on RBCs also promise to become a hotspot in the context of understanding root adaptive responses to hostile environments. In order to take advantage of RBCs as an ideal single cell system in plant-environmental interactions, we summarized the production and function of RBCs and built-up the methodology for RBCs culturing, purification, and quantity control for plant research. The latter is done by using a case study of the application of RBCs to study mechanisms of Al toxicity in plants. This work offers plant scientists a new cognition of adopting RBCs as a convenient single cell system for the multidisciplinary research including (but not limited to) plant physiology, development and genetics, nutrition, and stress and adaptation. Root border cells (RBCs) are derived from the root cap and represent a population of living cells with special physiological activity and biological roles that are different from the root cap cells per se. After being separated from the root cap, RBCs become more active in metabolism than the progenitor root cap cells; for example, they incorporate labeled amino acids into protein 2.6-fold more efficiently than the cells of the root cap. In addition, mRNA and protein were differentially expressed between root cap cells and RBCs. Since the production of RBCs is genetically regulated and RBCs played a variety of biological functions in resistance to biotic and abiotic stresses occurred in the rhizosphere, RBCs were suggested as an ideal single cell system for the study the response of plant root cells to nutrient availability, environmental stresses, and in plant-microbial interactions. Some studies revealed that RBCs, which development is regulated by endogenous and exogenous signals, are biologically viable in the majority of higher plant species. This work reviews the research on RBCs in plant environment interaction and describes the case study of RBCs as a convenient single cell system to study plant responses to Al toxicity.

Chicoric acid has been widely used in food, medicine, animal husbandry, and other commercial products because of its significant pharmacological activities. However, the shortage of chicoric acid limits its further development and utilization. Currently, Echinacea purpurea (L.) Moench serves as the primary natural resource of chicoric acid, while other sources of it are poorly known. Extracting chicoric acid from plants is the most common approach. Meanwhile, chicoric acid levels vary in different plants as well as in the same plant from different areas and different medicinal parts, and different extraction methods. We comprehensively reviewed the information regarding the sources of chicoric acid from plant extracts, its chemical synthesis, biosynthesis, and bioactive effects.

Oregano is a medicinal and aromatic plant of value in the pharmaceutical, food, feed additive, and cosmetic industries. Oregano breeding is still in its infancy compared with traditional crops. In this study, we evaluated the phenotypes of 12 oregano genotypes and generated F1 progenies by hybridization. The density of leaf glandular secretory trichomes and the essential oil yield in the 12 oregano genotypes varied from 97–1017 per cm2 and 0.17–1.67%, respectively. These genotypes were divided into four terpene chemotypes: carvacrol-, thymol-, germacrene D/β-caryophyllene-, and linalool/β-ocimene-type. Based on phenotypic data and considering terpene chemotypes as the main breeding goal, six oregano hybrid combinations were performed. Simple sequence repeat (SSR) markers were developed based on unpublished whole-genome sequencing data of Origanum vulgare, and 64 codominant SSR primers were screened on the parents of the six oregano combinations. These codominant primers were used to determine the authenticity of 40 F1 lines, and 37 true hybrids were identified. These 37 F1 lines were divided into six terpene chemotypes: sabinene-, β-ocimene-, γ-terpinene-, thymol-, carvacrol-, and p-cymene-type, four of which (sabinene-, β-ocimene-, γ-terpinene-, and p-cymene-type) were novel (i.e., different from the chemotypes of parents). The terpene contents of 18 of the 37 F1 lines were higher than those of their parents. The above results lay a strong foundation for the creating of new germplasm resources, constructing of genetic linkage map, and mapping quantitative trait loci (QTLs) of key horticultural traits, and provide insights into the mechanism of terpenoid biosynthesis in oregano.

In this paper, the key factors and the mechanism of the extraction of iron and manganese from the sulfuric acid leaching solution of waste ternary lithium-ion batteries were studied by combining P204 and N235 extractors. The experimental results showed that the optimal organic phase composition was 25% P204 + 15% N235 + 60% sulfonated kerosene, and the optimal pH of the pre-extraction solution was in the range of 3.0–3.5. Under the conditions of an extraction temperature of 25–35 °C and an extraction ratio of O/A = 1/1 and after mixing for 5 min, the removal rate of Mn and Fe exceeded 99%. Under the same extraction conditions, the extraction effect of the P204-N235 composite extractant on Mn and Fe was better than that of P204 alone. logD-log[P204] showed that the formulas of the Mn and Fe extracts were MnR2(HR) and FeR2(HR), respectively. The logD-pH diagram showed that only one free H+ was released for each metal ion during extraction, and extraction occurred via a cation exchange reaction.

Cross-modal retrieval aims to elucidate information fusion, imitate human learning, and advance the field. Although previous reviews have primarily focused on binary and real-value coding methods, there is a scarcity of techniques grounded in deep representation learning. In this paper, we concentrated on harmonizing cross-modal representation learning and the full-cycle modeling of high-level semantic associations between vision and language, diverging from traditional statistical methods. We systematically categorized and summarized the challenges and open issues in implementing current technologies and investigated the pipeline of cross-modal retrieval, including pre-processing, feature engineering, pre-training tasks, encoding, cross-modal interaction, decoding, model optimization, and a unified architecture. Furthermore, we propose benchmark datasets and evaluation metrics to assist researchers in keeping pace with cross-modal retrieval advancements. By incorporating recent innovative works, we offer a perspective on potential advancements in cross-modal retrieval.

The COVID-19 pandemic has caused millions of deaths and remains a major public health burden worldwide. Previous studies found that a large number of COVID-19 patients and survivors developed neurological symptoms and might be at high risk of neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). We aimed to explore the shared pathways between COVID-19, AD, and PD by using bioinformatic analysis to reveal potential mechanisms, which may explain the neurological symptoms and degeneration of brain that occur in COVID-19 patients, and to provide early intervention. In this study, gene expression datasets of the frontal cortex were employed to detect common differentially expressed genes (DEGs) of COVID-19, AD, and PD. A total of 52 common DEGs were then examined using functional annotation, protein–protein interaction (PPI) construction, candidate drug identification, and regulatory network analysis. We found that the involvement of the synaptic vesicle cycle and down-regulation of synapses were shared by these three diseases, suggesting that synaptic dysfunction might contribute to the onset and progress of neurodegenerative diseases caused by COVID-19. Five hub genes and one key module were obtained from the PPI network. Moreover, 5 drugs and 42 transcription factors (TFs) were also identified on the datasets. In conclusion, the results of our study provide new insights and directions for follow-up studies of the relationship between COVID-19 and neurodegenerative diseases. The hub genes and potential drugs we identified may provide promising treatment strategies to prevent COVID-19 patients from developing these disorders.

Transistors made up of carbon nanotube CNT have demonstrated excellent current–voltage characteristics which outperform some high-grade silicon-based transistors. A continuously tunable energy barrier across semiconductor interfaces is desired to make the CNT-based transistors more robust. Despite that the direct band gap of the carbyne inside a CNT can be widely tuned by strain, the size of the carbyne cannot be controlled easily. The production of a monoatomic chain with more than 6000 carbon atoms is an enormous technological challenge. To predict the optimal chain length of a carbyne in different molecular environments, we have developed a Monte Carlo model in which a finite-length carbyne with a size of 4000–15,000 atoms is encapsulated by a CNT at finite temperatures. Our simulation shows that the stability of the carbyne@nanotube is strongly influenced by the nature and porosity of the CNT, the external pressure, the temperature, and the chain length. We have observed an initiation of the chain-breaking process in a compressed carbyne@nanotube. Our work provides much-needed input for optimizing the carbyne length to produce carbon chains much longer than 6000 atoms at ~300 K. Design rules are proposed for synthesizing ~1% strained carbyne@(6,5)CNT as a component in CNT-based transistors to tune the energy barriers continuously.

Our study aimed to identify a design which would reduce cutting resistance during the harvesting of castor. This paper presents a theoretical study of the wave-type disc cutter, which plays an important role in castor harvesting. Based on the SPH–FEM coupling algorithm, a combined orthogonal rotation experiment was performed to study the effects of disc cutter thickness, edge angle, disc cutter rotation speed, and feeding speed on the maximum cutting force. The response surface method was used to achieve an optimal combination of all the test factors. Mathematical modeling of the maximum cutting force and influencing factors was utilized to obtain the optimal parameters for a cutting system consisting of wave-type disc cutters. The optimal results were obtained with a computer-simulated disc cutter rotation speed of 844.2–942.1 r/min, a feeding speed of 0.89–1.01 m/s, a disc cutter thickness of 2.71–3.15 mm, and an edge angle of 29.2–33.9°. Under these conditions, the maximum cutting force was less than 50 N. Finally, the experimental data and numerical computer simulation results were compared using cutting performance test verification. The analysis found that the test results and simulation results were largely consistent. Therefore, the simulation model was judged to be effective and reasonable.

Resveratrol is an antitoxin secreted by plants such as Polygonum cuspidatum Sieb. et Zucc and Vitis vinifera L. when they are attacked by pathogens. In the present study, three methods were used to prepare biological samples, and then an efficient strategy based on ultra-high-performance liquid chromatography-linear ion trap-Orbitrap mass spectrometry (UHPLC-LTQ-Orbitrap MS) was developed to screen and identify resveratrol metabolites in rat urine, plasma and faeces. As a result, a total of 56 resveratrol metabolites were screened and characterized. Among them, 39 metabolites were found in rat urine, while 6 and 16 metabolites were characterized from rat plasma and faeces, respectively. In addition, 56, 12 and 15 metabolic products were screened by solid phase extraction (method I), methanol precipitation (method II) and acetonitrile precipitation (method III), respectively, indicating that method I could be adopted as the most acceptable method. The results also demonstrated that resveratrol mainly underwent glucuronidation, glucosylation, sulfation, hydroxylation, dehydrogenation, hydrogenation, methylation and their composite reactions. Moreover, these metabolic reactions occurred to form a possible metabolic network that is similar to a triangular pyramid model. In summary, this research provides an idea for the further study of drug metabolism.

In the process of the comprehensive recovery and utilization of discarded lithium-ion batteries via acid leaching, a large number of NiS and CoS mixed materials are produced. To improve the metal recovery rate, the kinetics and rate-determining step of the oxygen-rich pressurized acid leaching of Ni and Co were investigated. The results showed that the leaching rates of Ni and Co were greater than 99% under the following conditions: sulfuric acid (leaching agent) concentration of 95 g/L, liquid-to-solid ratio of 6:1, leaching time of 120 min, temperature of 110 °C, stirring speed of 400 r/min, 90% oxygen-rich atmosphere, and pressure of 1.2 MPa. The leaching of Ni and Co was described by the shrinking unreacted core model, and the leaching rates of Ni and Co conformed to the kinetic equation 1 − (1 − x)1/3 = k·t. The apparent activation energies of the Ni and Co leaching reactions were 50.87 and 45.6 kJ/mol, respectively, and the leaching process was found to be controlled by the chemical reaction at the interface.

Air and water pollution poses a serious threat to public health and the ecological environment worldwide. Particulate matter (PM) is the major air pollutant, and its primary sources are processes that require high temperatures, such as fossil fuel combustion and vehicle exhaust. PM0.3 can penetrate and seriously harm the bronchi of the lungs, but it is difficult to remove PM0.3 due to its small size. Therefore, PM0.3 air filters that are highly efficient and resistant to high temperatures must be developed. Polyimide (PI) is an excellent polymer with a high temperature resistance and a good mechanical property. Air filters made from PI nanofibers have a high PM removal efficiency and a low air flow resistance. Herein, zeolitic imidazolate framework-8 (ZIF-8) was used to modify PI nanofibers to fabricate air filters with a high specific surface area and filtration efficiency. Compared with traditional PI membranes, the ZIF-8/PI multifunction nanofiber membranes achieved super-high filtration efficiency for ultrafine particles (PM0.3, 100%), and the pressure drop was only 63 Pa. The filtration mechanism of performance improvement caused by the introduction of ZIF-8/PI nanofiber membrane is explored. Moreover, the ZIF-8/PI nanofiber membranes exhibited excellent thermal stability (300 C) and efficient water–oil separation ability (99.85%).

Multifunctional terahertz beam manipulations have attracted much attention because of the potential for wide-scale applications in terahertz imaging, communications, etc. In this work, a grating-like terahertz reflective-type metasurface is designed for terahertz beam manipulations on the basis of a frequency-scanning mechanism. The theoretical calculation based on the grating principle has predicted that the metasurface grating can steer the deflected beam from 59.5° to 47.3° as the frequency of the perpendicularly incident terahertz wave changes between 0.87 and 1.02 THz. The large-deflection-angle frequency-scanning performance is validated by both numerical simulations and experimental tests. The metasurface grating developed in this work possesses the potential for applications in terahertz beam steering and beam-splitting devices.

Moth-flame optimization is a typical meta-heuristic algorithm, but it has the shortcomings of low-optimization accuracy and a high risk of falling into local optima. Therefore, this paper proposes an enhanced moth-flame optimization algorithm named HMCMMFO, which combines the mechanisms of hybrid mutation and chemotaxis motion, where the hybrid-mutation mechanism can enhance population diversity and reduce the risk of stagnation. In contrast, chemotaxis-motion strategy can better utilize the local-search space to explore more potential solutions further; thus, it improves the optimization accuracy of the algorithm. In this paper, the effectiveness of the above strategies is verified from various perspectives based on IEEE CEC2017 functions, such as analyzing the balance and diversity of the improved algorithm, and testing the optimization differences between advanced algorithms. The experimental results show that the improved moth-flame optimization algorithm can jump out of the local-optimal space and improve optimization accuracy. Moreover, the algorithm achieves good results in solving five engineering-design problems and proves its ability to deal with constrained problems effectively.

Thermal management is a critical task for highly integrated or high-power semiconductor devices. Low dimensional materials including graphene and single-layer hexagonal boron nitride (BN) are attractive candidates for this task because of their high thermal conductivity, semi-conductivity and other excellent physical properties. The similarities in crystal structure and chemistry between graphene and boron nitride provide the possibility of constructing graphene/BN heterostructures bearing unique functions. In this paper, we investigated the interfacial thermal transport properties of graphene/BN nanosheets via non-equilibrium molecular dynamics (NEMD) simulations. We observed a significant thermal rectification behavior of these graphene/BN nanosheets, and the rectification ratio increased with the system length increases up to 117%. This phenomenon is attributed to the mismatch of out-of-plane phonon vibration modes in two directions at the interface. In addition, we explored the underlying mechanism of the length dependence of the thermal transport properties. The results show promise for the thermal management of this two-dimensional heterostructure in an actively tunable manner.

Origanum vulgare, belonging to the Lamiaceae family, is a principal culinary herb used worldwide which possesses great antioxidant and antibacterial properties corresponding to various volatile organic components (VOCs). However, the metabolite profiles and underlying biosynthesis mechanisms of elaborate tissues (stems, leaves, bracts, sepals, petals) of Origanum vulgare have seldom been reported. Here, solid-phase microextraction–gas chromatography/mass spectrometry results showed that Origanum vulgare ‘Hot and Spicy’ (O. vulgare ‘HS’) was extremely rich in carvacrol and had the tissue dependence characteristic. Moreover, a full-length transcriptome analysis revealed carvacrol biosynthesis and its tissue-specific expression patterns of ‘upstream’ MVA/MEP pathway genes and ‘downstream’ modifier genes of TPSs, CYPs, and SDRs. Furthermore, the systems biology method of modular organization analysis was applied to cluster 16,341 differently expressed genes into nine modules and to identify significant carvacrol- and peltate glandular trichome-correlated modules. In terms of these positive and negative modules, weighted gene co-expression network analysis results showed that carvacrol biosynthetic pathway genes are highly co-expressed with TF genes, such as ZIPs and bHLHs, indicating their involvement in regulating the biosynthesis of carvacrol. Our findings shed light on the tissue specificity of VOC accumulation in O. vulgare ‘HS’ and identified key candidate genes for carvacrol biosynthesis, which would allow metabolic engineering and breeding of Origanum cultivars.

As the complexity and cost of industrial systems continue to increase, so does the need for the safety and reliability of industrial systems. In recent years, in the field of mechanical fault diagnosis, methods based on deep learning are gradually gaining popularity. The traditional deep learning method assumes that the training set and the test set belong to the same working condition, which is contrary to the actual industrial process. In order to improve the general ability of the fault diagnosis model, researchers start to study the domain adaptation method. However, most domain adaptation methods do not impose constraints on the test set, which leads to the occurrence of the domain mismatch problem. This paper proposes a multi-source consistency domain adaptation neural network MCDANN, which uses sub-domain division alignment and multi-source prediction consistency to achieve fine-grained domain matching and improve the transfer accuracy of the model. This paper conducts domain adaptation experiments on the open-source bearing fault dataset CWRU and DIRG bearing dataset and compares them with other classical methods. Experiments show that in the case of a signal-to-noise ratio of −4, the MCDANN model achieves an average diagnostic accuracy of more than 96% on the CWRU dataset and the DIRG dataset on noisy fault signals from the target domain, and is superior in almost all fields than other adaptive models.

The lumen of the endoplasmic reticulum (ER) has resident proteins that are critical to perform the various tasks of the ER such as protein maturation and lipid metabolism. These ER resident proteins typically have a carboxy-terminal ER retention/retrieval sequence (ERS). The canonical ERS that promotes ER retrieval is Lys-Asp-Glu-Leu (KDEL) and when an ER resident protein moves from the ER to the Golgi, KDEL receptors (KDELRs) in the Golgi recognize the ERS and return the protein to the ER lumen. Depletion of ER calcium leads to the mass departure of ER resident proteins in a process termed exodosis, which is regulated by KDELRs. Here, by combining computational prediction with machine learning-based models and experimental validation, we identify carboxy tail sequences of ER resident proteins divergent from the canonical “KDEL” ERS. Using molecular modeling and simulations, we demonstrated that two representative non-canonical ERS can stably bind to the KDELR. Collectively, we developed a method to predict whether a carboxy-terminal sequence acts as a putative ERS that would undergo secretion in response to ER calcium depletion and interacts with the KDELRs. The interaction between the ERS and the KDELR extends beyond the final four carboxy terminal residues of the ERS. Identification of proteins that undergo exodosis will further our understanding of changes in ER proteostasis under physiological and pathological conditions where ER calcium is depleted.

The AP2/ERF transcription factors are widely involved in the regulation of plant growth, development and stress responses. Arabidopsis ERF012 is differentially responsive to various stresses; however, its potential regulatory role remains elusive. Here, we show that ERF012 is predominantly expressed in the vascular bundles, lateral root primordium and vein branch points. ERF012 overexpression inhibits root growth, whereas it promotes root hair development and leaf senescence. In particular, ERF012 may downregulate its target genes AtC4H and At4CL1, key players in phenylpropanoid metabolism and cell wall formation, to hinder auxin accumulation and thereby impacting root growth and leaf senescence. Consistent with this, exogenous IAA application effectively relieves the effect of ERF012 overexpression on root growth and leaf senescence. Meanwhile, ERF012 presumably activates ethylene biosynthesis to promote root hair development, considering that the ERF012-mediated root hair development can be suppressed by the ethylene biosynthetic inhibitor. In addition, ERF012 overexpression displays positive and negative effects on low- and high-temperature responses, respectively, while conferring plant resistance to drought, salinity and heavy metal stresses. Taken together, this study provides a comprehensive evaluation of the functional versatility of ERF012 in plant growth, development and abiotic stress responses.

Supported single atom or nanocluster catalysts have been widely studied due to their excellent catalytic properties. Many methods to prepare such catalysts start with constructing defects on supports, and the main focus is to improve dispersion and stability of the active sites. This paper for the first time reports a radical-assisted method to prepare single atom or nanocluster Pd on a biochar. The char was prepared by pyrolyzing walnut shell at 600°C under N2, and Pd was loaded on the char by impregnating with palladium acetate in toluene under an oxygen-free atmosphere. It is found that there are three types of radicals in the fresh char (F-Char-600), two of them may adsorb/bond with O2 or Pd2+ resulting in decreases in the char's radical concentration. The Pd on F-Char-600 for 24 h impregnation are single atoms (0.1–0.3 nm, 2%) and nanoclusters (0.3–1.2 nm, 98%), which grow larger (0.3–4 nm, 100%) for 84 h impregnation. The Pd on N2 purged O2-adsorbed-char (N-O-Char-600) is much larger in size. The bond between Pd and char is probably C–Pd in F-Char-600 or C–O–Pd in N-O-Char-600.

Summary: We demonstrate the nearly quantitative conversion of methanol to methyl formate (MF) with a reliable durability on the reduced-graphene-oxide-confined VTiOx nanoparticles (rGO@VTiO). The rGO@VTiO exhibits superior low-temperature reactivity than the rGO-free VTiO, and the MF yield of 98.8% is even comparable with the noble metal catalysts. Both experiments and simulations demonstrate that the ultrathin rGO shell significantly impacts the shell/core interfacial electronic structure and the surface chemistry of the resultant catalysts, leading to remarkable reactivity in methanol to MF. rGO enhances the dispersion and loading rates of active monomeric/oligomeric VOx. In particular, the electron migration between the rGO shell and oxides core reinforces the acidity of rGO@VTiO in the absence of sulfate acidic sites. Moreover, both in situ NAP-XPS and DRIFTS investigations suggest that the lattice oxygen was involved in the oxidation of methanol and the MF was formed via the hemiacetal mechanism.

Multidrug resistance is a serious problem and a common cause of cancer treatment failure, leading to patient death. Although numerous reversal resistance inhibitors have been evaluated in preclinical or clinical trials, efficient and low-toxicity reversal agents have not been identified. In this study, a series of novel quinoline compound derivatives from NSC23925 were designed to inhibit P-glycoprotein (P-gp). Among them, YS-7a showed a stronger inhibitory effect against P-gp than verapamil, as a positive control, when co-incubated with chemotherapy drugs at minimally cytotoxic concentrations. YS-7a suppressed the P-gp transport function without affecting the expression of P-gp but stimulated the ATPase activity of P-gp in a dose-dependent manner. Next, molecular docking was used to predict the six most probable binding sites, namely, SER270, VAL273, VAL274, ILE354, VAL357, and PHE390. Moreover, YS-7a had no effect on cytochrome P450 3A4 activity and showed little toxicity to normal cells. In addition, combined treatment of YS-7a with vincristine showed a better inhibitory effect than the positive control verapamil in vivo without a negative effect on mouse weight. Overall, our results showed that YS-7a could reverse cancer multidrug resistance through the inhibition of P-gp transport function in vitro and in vivo, suggesting that YS-7a may be a novel therapeutic agent.

Hybrid organic–inorganic MCM-41 (Mobil Composition of Matter No. 41) silicas functionalized with Nafion (perfluoroalkylsulfonic acid analogous) were prepared and characterized by Fourier Transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and N2 adsorption analysis. The Brønsted acidity was determined by UV spectrophotometer. The prepared catalyst (SA/MCM-41) exhibited high catalytic activity in the nitration of TAIW (tetraacetylhexaazaisowurtzitan) aiming at synthesizing CL-20 (hexanitrohexaazaisowurtzitane), with the yield up to 93%. The leaching problem was not observed after several runs, demonstrating that the catalyst could be recycled and reused without losing activity. Keywords: Perfluorosulfonic acid, Nafion, MCM-41, Nitration, CL-20

In this paper, we report the synthesis, characterization, and electrochemical evaluation of a mesoporous PtSnO2/C catalyst, called PtSnO2(M)/C, with a nominal Pt : Sn ratio of 3 : 1. Brunauer–Emmett–Teller and transmission electron microscopy characterizations showed the obvious mesoporous structure of SnO2 in PtSnO2(M)/C catalyst. X-ray photoelectron spectroscopy analysis exhibited the interaction between Pt and mesoporous SnO2. Compared with Pt/C and commercial PtSnO2/C catalysts, PtSnO2(M)/C catalyst has a lower active site, but higher catalytic activity for ethanol electro-oxidation reaction (EOR). The enhanced activity could be attributed to Pt nanoparticles deposited on mesoporous SnO2 that could decrease the amount of poisonous intermediates produced during EOR by the interaction between Pt and mesoporous SnO2.

In this paper, we propose a new method for detecting abnormal human behavior based on skeleton features using self-attention augment graph convolution. The skeleton data have been proved to be robust to the complex background, illumination changes, and dynamic camera scenes and are naturally constructed as a graph in non-Euclidean space. Particularly, the establishment of spatial temporal graph convolutional networks (ST-GCN) can effectively learn the spatio-temporal relationships of Non-Euclidean Structure Data. However, it only operates on local neighborhood nodes and thereby lacks global information. We propose a novel spatial temporal self-attention augmented graph convolutional networks (SAA-Graph) by combining improved spatial graph convolution operator with a modified transformer self-attention operator to capture both local and global information of the joints. The spatial self-attention augmented module is used to understand the intra-frame relationships between human body parts. As far as we know, we are the first group to utilize self-attention for video anomaly detection tasks by enhancing spatial temporal graph convolution. Moreover, to validate the proposed model, we performed extensive experiments on two large-scale publicly standard datasets (i.e., ShanghaiTech Campus and CUHK Avenue datasets) which reveal the state-of-art performance for our proposed approach when compared to existing skeleton-based methods and graph convolution methods.

Nuclear Factor-Y (NF-Y) transcription factors play vital roles in plant abiotic stress response. Here, the NF-Y family in Brassica napus, which is hyper-sensitive to nitrogen (N) deprivation, was comprehensively identified and systematically characterized. A total of 108 NF-Y family members were identified in B. napus and categorized into three subfamilies (38 NF-YA, 46 NF-YB and 24 NF-YC; part of the Arabidopsis NF-YC homologous genes had been lost during B. napus evolution). In addition, the expansion of the NF-Y family in B. napus was driven by whole-genome duplication and segmental duplication. Differed expression patterns of BnaNF-Ys were observed in response to multiple nutrient starvations. Thirty-four genes were regulated only in one nutrient deficient condition. Moreover, more BnaNF-YA genes were differentially expressed under nutrient limited environments compared to the BnaNF-YB and BnaNF-YC subfamilies. Sixteen hub genes responded diversely to N deprivation in five rapeseed tissues. In summary, our results laid a theoretical foundation for the follow-up functional study of the key NF-Y genes in B. napus in regulating nutrient homeostasis, especially N.

The WOX family is a group of plant-specific transcription factors which regulate plant growth and development, cell division and differentiation. From the available genome sequence databases of nine Triticeae species, 199 putative WOX genes were identified. Most of the identified WOX genes were distributed on the chromosomes of homeologous groups 1 to 5 and originated via the orthologous evolution approach. Parts of WOX genes in Triticum aestivum were confirmed by the specific PCR markers using a set of Triticum. durum-T. aestivum genome D substitution lines. All of these identified WOX proteins could be grouped into three clades, similar to those in rice and Arabidopsis. WOX family members were conserved among these Triticeae plants; all of them contained the HOX DNA-binding homeodomain, and WUS clade members contained the characteristic WUS-box motif, while only WUS and WOX9 contained the EAR motif. The RNA-seq and qPCR analysis revealed that the TaWOX genes had tissue-specific expression feature. From the expression patterns of TaWOX genes during immature embryo callus production, TaWOX9 is likely closely related with the regulation of regeneration process in T. aestivum. The findings in this study could provide a basis for evolution and functional investigation and practical application of the WOX family genes in Triticeae species.

During the recent pandemic of COVID-19, an increasing amount of information has been propagated on social media. This situational information is valuable for public authorities. Therefore, this study characterized the propagation scale of situational information types by harnessing the power of natural language processing techniques and machine learning algorithms. We observed that the length of the post has a positive correlation with type 1 information (announcements), and negative words were mostly used in type 5 information (criticizing the government), whereas anxiety-related words have a negative effect on the amount of retweeted type 0 (precautions) and type 2 (donations) information. This type of research study not only contributes to the situational information literature by comprehensively defining categories but also provides data-oriented practical insights into information so that management authorities can formulate response strategies after the pandemic. Our approach is one of its kind and combines Twitter content features, user features and LIWC linguistic features with machine learning algorithms to analyze the propagation scale of situational information, and it achieved 77% accuracy with SVM while classifying the information categories.

Na and cyano-group co-modified g-C3N4 was easily synthesized and its physicochemical property was completely analyzed. The results manifested that Na and cyano-group modification could heighten visible light absorbed ability and accelerate photoinduced charge separation. When resultant Na and cyano-group co-modified g-C3N4 was splitting water H2 evolution, its H2 evolution rate was obviously improved. Furthermore, it also kept excellent stable capacity of H2 evolution and stability of chemical structure. Hence, this present study does not only develop an efficient strategy to boost photocatalytic property of g-C3N4 based catalysts, but also provides useful guidance for designing more effective photocatalysts.

Low phosphorus (P) availability is one of the major constraints to plant growth, particularly in acidic soils. A possible mechanism for enhancing the use of sparsely soluble P forms is the secretion of malate in plants by the aluminum-activated malate transporter (ALMT) gene family. Despite its significance in plant biology, the identification of the ALMT gene family in oilseed rape (Brassica napus; B. napus), an allotetraploid crop, is unveiled. Herein, we performed genome-wide identification and characterization of ALMTs in B. napus, determined their gene expression in different tissues and monitored transcriptional regulation of BnaALMTs in the roots and leaves at both a sufficient and a deficient P supply. Thirty-nine BnaALMT genes were identified and were clustered into five branches in the phylogenetic tree based on protein sequences. Collinearity analysis revealed that most of the BnaALMT genes shared syntenic relationships among BnaALMT members in B. napus, which suggested that whole-genome duplication (polyploidy) played a major driving force for BnaALMTs evolution in addition to segmental duplication. RNA-seq analyses showed that most BnaALMT genes were preferentially expressed in root and leaf tissues. Among them, the expression of BnaC08g13520D, BnaC08g15170D, BnaC08g15180D, BnaC08g13490D, BnaC08g13500D, BnaA08g26960D, BnaC05g14120D, BnaA06g12560D, BnaC05g20630D, BnaA07g02630D, BnaA04g15700D were significantly up-regulated in B. napus roots and leaf at a P deficient supply. The current study analyzes the evolution and the expression of the ALMT family in B. napus, which will help in further research on their role in the enhancement of soil P availability by secretion of organic acids.

The dynamics model used for inertially or strapdown inertially stabilized platforms is based on the rotor and motor load, and it either does not consider the stator or it implicitly assumes a fixed stator. It has been determined that vibrations occur in the system when a controller is used in strapdown inertially stabilized platforms with a light base support. As the system is also affected by multi-source disturbances, which are the main factors that affect the control accuracy. For the above two problems, this paper originally establishes a multi-body dynamics model including the controller. The composite controller not only suppresses the vibration successfully, but also greatly improves the disturbance compensation and tracking performance of the strapdown inertially stabilized platforms. Specifically, a modified feedback controller is used to suppress the vibrations analyzed according to the dynamics model. The friction feedforward and residual disturbance observer facilitates the design of compound disturbance compensation on the basis of composite hierarchical anti-disturbance control. To emphasize the advantages of strapdown inertially stabilized platforms, the feedforward controller employs feedforward angular velocity and acceleration. The results of the numerical analysis and experiments indicate that vibrations are successfully suppressed and tracking accuracy and disturbance isolation ability are improved.