Search

Abstract Background Sugarcane red rot is a soil-borne disease caused by Colletotrichum falcatum. It can reduce the yield of sugarcane and the purity of sugarcane juice, which seriously restricts the development of sucrose industry. Biocontrol bacteria can control diseases by regulating rhizosphere microecology. In this study, the effects of biocontrol bacteria on sugarcane rhizosphere microecology were studied by metagenomics and metabolomics, and the control effects of biocontrol bacteria and rhizosphere dominant bacteria on sugarcane red rot were further explored by pot experiment. Results The results of metagenomic sequencing showed that inoculation with B. velezensis YC89 and pathogens could significantly change the microbial diversity of the sugarcane rhizosphere. The relative abundance of beneficial strains such as Streptomyces, Burkholderia, Sphingomonas, and Rhizobium increased significantly in the rhizosphere of sugarcane in the YC treatment group. Pseudomonas was significantly enriched in the rhizosphere of sugarcane in the C treatment group. The results of metabolome sequencing showed that the content of amino acids in sugarcane root exudates increased after inoculation with B. velezensis YC89, and the contents of phenolic acids and flavonoids decreased. Spearman correlation analysis showed that there was a significant correlation between differential metabolites and rhizosphere microorganisms. The results of pot experiment showed that YC89 strain and three rhizosphere microorganisms could significantly reduce the disease index of red rot and promote the growth of sugarcane plants. In addition, these strains can also significantly increase the JA and SA content of sugarcane leaves and induce plant system resistance-related enzyme activities. Among them, the synthetic community treatment group had the best biocontrol effect on red rot, and its relative control effect was 67.50%. Conclusions Therefore, we conclude that B. velezensis YC89 could recruit beneficial rhizosphere microorganisms to enrich the rhizosphere and change the content of some phenolic acids and flavonoids in the root exudates. In addition, the isolated rhizosphere dominant bacteria and YC89 strain can resist red rot by inducing plant systemic resistance and promote the growth of sugarcane plants. This study provides a theoretical basis for the use of biocontrol bacteria to regulate rhizosphere bacteria to jointly control plant soil-borne diseases. Graphical Abstract

Low-temperature stress significantly impacts plant growth, development, yield, and geographical distribution. However, during the long-term process of evolution, plants have evolved complicated mechanisms to resist low-temperature stress. The cold tolerance trait is regulated by multiple pathways, such as the Ca2+ signaling cascade, mitogen-activated protein kinase (MAPK) cascade, inducer of CBF expression 1 (ICE1)-C-repeat binding factor (CBF)-cold-reulated gene (COR) transcriptional cascade, reactive oxygen species (ROS) homeostasis regulation, and plant hormone signaling. However, the specific responses of these pathways to cold stress and their interactions are not fully understood. This review summarizes the response mechanisms of plants to cold stress from four aspects, including cold signal perception and transduction, ICE1-CBF-COR transcription cascade regulation, ROS homeostasis regulation and plant hormone signal regulation. It also elucidates the mechanism of cold stress perception and Ca2+ signal transduction in plants, and proposes the important roles of transcription factors (TFs), post-translational modifications (PTMs), light signals, circadian clock factors, and interaction proteins in the ICE1-CBF-COR transcription cascade. Additionally, we analyze the importance of ROS homeostasis and plant hormone signaling pathways in plant cold stress response, and explore the cross interconnections among the ICE1-CBF-COR cascade, ROS homeostasis, and plant hormone signaling. This comprehensive review enhances our understanding of the mechanism of plant cold tolerance and provides a molecular basis for genetic strategies to improve plant cold tolerance.

Abstract MicroRNAs play an important role in the proliferation, invasion, and metastasis of malignancy. In previous studies (detailed in our previous paper), the expression of miR-6839-5p was significantly increased in SW1353 cells after 125I seed 6 Gy irradiation, which indicated miR-6839-5p may play a tumor suppression function in chondrosarcoma cells. This study aimed to identify the effects of miR-6839-5p on the human chondrosarcoma cells, and investigate the potential target genes of miR-6839-5p. Firstly, chondrosarcoma cells (SW1353 and CAL78) were transfected with hsa-miR-6839-5p specific mimic. Secondly, Cell viability assay (MTT assay), Colony formation assay, Wound healing assay, Transwell assay, TUNEL staining and Western blotting experiments were performed, and the results proved miR-6839-5p can inhibit chondrosarcoma cells proliferation, migration and invasion. Meanwhile, miR-6839-5p significantly down-regulated apoptosis facilitator Bcl-2 expression, and promoted apoptosis of chondrosarcoma cells. It is reasonable to speculate miR-6839-5p might downregulate Bcl-2 expression to induce apoptosis in SW1353 human chondrosarcoma cells. Lastly, RNA extraction and bioinformatic analysis was performed on SW1353 cells transfected with hsa-miR-6839-5p specific mimic to investigate the potential target genes of miR-6839-5p. A total of 253 differentially expressed mRNA genes (105 up-regulated genes and 148 down-regulated genes) were found, and 23 differentially expressed downregulated genes were identified. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the results, which demonstrated the expression of BST2, VEGFA, FPR3 and PPARA was significantly downregulated by miR-6839-5p mimic. Furthermore, miR-6839-5p inhibitor can restore or partially restore the expression value of the above four genes. The analysis results of miRNA target gene prediction database indicated VEGFA was the most likely direct target gene of miR-6839-5p.

PurposeThis study aims to evaluate the diagnostic performance of a machine learning model (ML model) to train junior ophthalmologists in detecting preclinical keratoconus (PKC).MethodsA total of 1,334 corneal topography images (The Pentacam HR system) from 413 keratoconus eyes, 32 PKC eyes and 222 normal eyes were collected. Five junior ophthalmologists were trained and annotated the images with or without the suggestions proposed by the ML model. The diagnostic performance of PKC was evaluated among three groups: junior ophthalmologist group (control group), ML model group and ML model-training junior ophthalmologist group (test group).ResultsThe accuracy of the ML model between the eyes of patients with KC and NEs in all three clinics (99% accuracy, area under the receiver operating characteristic (ROC) curve AUC of 1.00, 99% sensitivity, 99% specificity) was higher than that for Belin-Ambrósio enhanced ectasia display total deviation (BAD-D) (86% accuracy, AUC of 0.97, 97% sensitivity, 69% specificity). The accuracy of the ML model between eyes with PKC and NEs in all three clinics (98% accuracy, AUC of 0.96, 98% sensitivity, 98% specificity) was higher than that of BAD-D (69% accuracy, AUC of 0.73, 67% sensitivity, 69% specificity). The diagnostic accuracy of PKC was 47.5% (95%CI, 0.5–71.6%), 100% (95%CI, 100–100%) and 94.4% (95%CI, 14.7–94.7%) in the control group, ML model group and test group. With the assistance of the proposed ML model, the diagnostic accuracy of junior ophthalmologists improved with statistical significance (p

The photogenerated charge carrier separation and transportation of inside photocathodes can greatly influence the performance of photoelectrochemical (PEC) H2 production devices. Coupling TiO2 with p-type semiconductors to construct heterojunction structures is one of the most widely used strategies to facilitate charge separation and transportation. However, the band position of TiO2 could not perfectly match with all p-type semiconductors. Here, taking antimony selenide (Sb2Se3) as an example, a rational strategy was developed by introducing a viologen electron transfer mediator (ETM) containing polymeric film (poly-1,1′-dially-[4,4′-bipyridine]-1,1′-diium, denoted as PV2+) at the interface between Sb2Se3 and TiO2 to regulate the energy band alignment, which could inhibit the recombination of photogenerated charge carriers of interfaces. With Pt as a catalyst, the constructed Sb2Se3/PV2+/TiO2/Pt photocathode showed a superior PEC hydrogen generation activity with a photocurrent density of −18.6 mA cm−2 vs. a reversible hydrogen electrode (RHE) and a half-cell solar-to-hydrogen efficiency (HC-STH) of 1.54% at 0.17 V vs. RHE, which was much better than that of the related Sb2Se3/TiO2/Pt photocathode without PV2+ (−9.8 mA cm−2, 0.51% at 0.10 V vs. RHE).

In the present study, the adsorption of arsenic(V) and cadmium(II) onto microplastics from poly(butylene succinate-co-butylene adipate) (PBSA) and low-density polyethylene (LDPE) plastic mulch films was investigated through batch experiment. The surface morphology and elemental composition of soil and microplastics were analyzed with scanning electron microscopy equipped with energy-dispersive X-ray spectroscopy (SEM-EDX) and Fourier-transform infrared (FTIR) spectroscopy. The results show that the adsorption of As(V) and Cd(II) on microplastics led to surfaces with coarseness and more cracks, and many small particles. Under the conditions added with 100 pieces of microplastic, PBSA enhanced the adsorption capacity of As(V) (from 0.43 to 0.49 mg/g), and LDPE increased the adsorption of Cd(II) (from 0.174 to 0.176 mg/g) due to the “superimposed effect” caused by hydrogen bonds. Conversely, LDPE reduced the adsorption of As(V) (from 0.44 to 0.40 mg/g) due to a “dilution effect” of PE. Particularly, PBSA exhibited an insignificant effect on the adsorption of Cd(II) in soil during the present study. Overall, our findings provide new insights into the impacts of microplastics on the fate and behavior of heavy metals in the soil system.

With the advancement of Internet of Things (IoT) technology, both the methods of data collection by citizen data collectors and the willingness of citizens to share data are evolving. To analyze the long-term impact of government reward-penalty mechanisms on citizen data collection, this paper constructed three evolutionary game models under scenarios of no reward-penalty, static reward-penalty, and dynamic reward-penalty mechanisms. The focus is on comparing and analyzing evolutionarily stable strategies of a collector and a citizen, followed by computational simulations. Key findings include: 1) Under no reward-penalty and static reward-penalty mechanisms, evolutionarily stable strategies typically result in either consistently active or consistently passive behaviors by both the collector and the citizen. Mixed strategies, which are evolutionarily stable, emerge only under dynamic reward-penalty mechanisms. 2) The balance between the risk associated with data security for the citizen and the benefits they gain from public services significantly influences evolutionary outcomes. 3) Policy directions may be influenced by initial conditions in the pre-collection stage, which can be mitigated by improving the benefit to citizen or reducing the cost during passive data collection. 4) While reward-penalty mechanisms may not directly enhance data collection success rates, they do accelerate the evolutionary process of data collection.

The precise identification of disease traits in the complex sugarcane planting environment not only effectively prevents the spread and outbreak of common diseases but also allows for the real-time monitoring of nutrient deficiency syndrome at the top of sugarcane, facilitating the supplementation of relevant nutrients to ensure sugarcane quality and yield. This paper proposes a human–machine collaborative sugarcane disease detection method in complex environments. Initially, data on five common sugarcane diseases—brown stripe, rust, ring spot, brown spot, and red rot—as well as two nutrient deficiency conditions—sulfur deficiency and phosphorus deficiency—were collected, totaling 11,364 images and 10 high-definition videos captured by a 4K drone. The data sets were augmented threefold using techniques such as flipping and gamma adjustment to construct a disease data set. Building upon the YOLOv8 framework, the EMA attention mechanism and Focal loss function were added to optimize the model, addressing the complex backgrounds and imbalanced positive and negative samples present in the sugarcane data set. Disease detection models EF-yolov8s, EF-yolov8m, EF-yolov8n, EF-yolov7, and EF-yolov5n were constructed and compared. Subsequently, five basic instance segmentation models of YOLOv8 were used for comparative analysis, validated using nutrient deficiency condition videos, and a human–machine integrated detection model for nutrient deficiency symptoms at the top of sugarcane was constructed. The experimental results demonstrate that our improved EF-yolov8s model outperforms other models, achieving mAP_0.5, precision, recall, and F1 scores of 89.70%, 88.70%, 86.00%, and 88.00%, respectively, highlighting the effectiveness of EF-yolov8s for sugarcane disease detection. Additionally, yolov8s-seg achieves an average precision of 80.30% with a smaller number of parameters, outperforming other models by 5.2%, 1.9%, 2.02%, and 0.92% in terms of mAP_0.5, respectively, effectively detecting nutrient deficiency symptoms and addressing the challenges of sugarcane growth monitoring and disease detection in complex environments using computer vision technology.

The probing depth of the transient electromagnetic method (TEM) refers to the depth range at which the underground conductivity changes can be effectively detected. It typically ranges from tens of meters to several kilometers and is influenced by factors such as instrument parameters and the conductivity of the subsurface structure. Rapid and accurate probing depth is useful for the selection of appropriate inversion parameters and improving survey accuracy. However, mainstream methods suffer from issues such as low computational precision, large uncertainties, or high computational requirements, making them unsuitable for processing massive airborne electromagnetic data. In this study, we propose a prediction model based on deep learning that can directly compute the probing depth from the TEM responses, and its effectiveness and accuracy are validated through synthetic models and field measurements. We compared the performance of classic deep learning models, including CNN, RESNET, and RNN, and found that RNN performed the best overall on both synthetic and field data. Furthermore, we apply this algorithm to deep learning-based ATEM inversion by constraining the one-dimensional resistivity model depths in the training set, to reduce the non-uniqueness of the inversion, accelerate the convergence, and improve its prediction accuracy.

Abstract Despite considerable research efforts on photoelectrochemical water splitting over the past decades, practical application faces challenges by the absence of efficient, stable, and scalable photoelectrodes. Herein, we report a metal-halide perovskite-based photoanode for photoelectrochemical water oxidation. With a planar structure using mesoporous carbon as a hole-conducting layer, the precious metal-free FAPbBr3 photovoltaic device achieves 9.2% solar-to-electrical power conversion efficiency and 1.4 V open-circuit voltage. The photovoltaic architecture successfully applies to build a monolithic photoanode with the FAPbBr3 absorber, carbon/graphite conductive protection layers, and NiFe catalyst layers for water oxidation. The photoanode delivers ultralow onset potential below 0 V versus the reversible hydrogen electrode and high applied bias photon-to-current efficiency of 8.5%. Stable operation exceeding 100 h under solar illumination by applying ultraviolet-filter protection. The photothermal investigation verifies the performance boost in perovskite photoanode by photothermal effect. This study is significant in guiding the development of photovoltaic material-based photoelectrodes for solar fuel applications.

Abstract Electrocatalytic urea synthesis is an emerging alternative technology to the traditional energy-intensive industrial urea synthesis protocol. Novel strategies are urgently needed to promote the electrocatalytic C–N coupling process and inhibit the side reactions. Here, we report a CuWO4 catalyst with native bimetallic sites that achieves a high urea production rate (98.5 ± 3.2 μg h−1 mg−1 cat) for the co-reduction of CO2 and NO3 − with a high Faradaic efficiency (70.1 ± 2.4%) at −0.2 V versus the reversible hydrogen electrode. Mechanistic studies demonstrated that the combination of stable intermediates of *NO2 and *CO increases the probability of C–N coupling and reduces the potential barrier, resulting in high Faradaic efficiency and low overpotential. This study provides a new perspective on achieving efficient urea electrosynthesis by stabilizing the key reaction intermediates, which may guide the design of other electrochemical systems for high-value C–N bond-containing chemicals.

Abstract Present indoor cultivation of saffron (Crocus sativus L.) only depends on artificial planting experience, so that flower number and stigma yield are seriously affected in case of cloudy or rainy days and temperature changes. In this study, a luminaire was used at 10-h photoperiod combined 450 nm blue LEDs with 660 nm broad-band red LEDs, which respectively had full width at half maximum (FWHM) of 15 nm and 85 nm, in a ratio of blue: red: far-red light = 20%: 62%: 18%. The influence of total daily light integral (TDLI) was evaluated on flowering characteristics, stigma quality, as well as leaf morphological characteristics. The results showed that flower number, daily flowering proportion, stigma dry weight and crocetin esters content were significantly correlated with TDLI (P

Autonomous collision avoidance decision making for maritime autonomous surface ships (MASS), as one of the key technologies for MASS autonomous navigation, is a research hotspot focused on by relevant scholars in the field of navigation. In order to guarantee the rationality, efficacy, and credibility of the MASS autonomous collision avoidance scheme, it is essential to design the MASS autonomous collision avoidance algorithm under the stipulations of the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). In order to enhance the autonomous collision avoidance decision-making capability of MASS in accordance with the relevant provisions of COLREGs, an improved NSGA-II autonomous collision avoidance decision-making algorithm based on the good point set method (GPS-NSGA-II) is proposed, which incorporates the collision hazard and the path cost of collision avoidance actions. The experimental results in the four simulation scenarios of head-on situation, overtaking situation, crossing situation, and multi-ship encounter situation demonstrate that the MASS autonomous collision avoidance decision making based on the GPS-NSGA-II algorithm under the constraints of COLREGs is capable of providing an effective collision avoidance scheme that meets the requirements of COLREGs in common encounter situations and multi-ship avoidance scenarios promptly, with a promising future application.

Leaf photosynthesis largely determines the daughter corm yields in vegetative growth for saffron (Crocus sativus L.). Most of the previous researches focus on the spectral response in various species, but research on saffron leaves at different leaf ages is lacking. In this study, the action spectrum based on photosynthetic photon flux density (PPFD) and irradiance were distinguished and interpreted. The optical properties and photosynthetic performances of leaves were, respectively, investigated at two leaf ages, dependent on customized narrow-band LED spotlights from 380 nm to 780 nm with an interval of 20 nm and a band width of 10 nm. The younger leaves were characterized by higher reflectance and transmittance values at 500−600 nm, resulting in lower absorptance compared to the older leaves. The spectral response curves including the action spectrum and quantum yield for younger leaves were higher than the older, but their relative curves displayed coincidence. The spectral response curves exhibited two peaks at 440 and 640 nm, but no obvious troughs between 500 and 600 nm were observed. Nevertheless, the photosynthetic energy efficiencies of spotlights demonstrated very low values in the green/yellow region. Accordingly, more attention should be paid to green and yellow LED lighting during the vegetative stage for saffron, as well as improving their manufacturing technology.

Abstract. Background. The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has greatly threatened public health. Recent studies have revealed that the spike receptor-binding domain (RBD) of SARS-CoV-2 is a potent target for vaccine development. However, adjuvants are usually required to strengthen the immunogenicity of recombinant antigens. Different types of adjuvants can elicit different immune responses. Methods. We developed an RBD recombinant protein vaccine with a polyriboinosinic acid–polyribocytidylic acid [poly(I:C)] adjuvant to evoke a strong immune response. The delivery of poly(I:C) was optimized in two steps. First, poly(I:C) was complexed with a cationic polymer, poly-l-lysine (PLL), to form poly(I:C)–PLL, a polyplex core. Thereafter, it was loaded into five different lipid shells (group II, III-1,2-distearoyl-sn-glycero-3-phosphocholine [DSPC], III-1,2-dioleoyl-sn-glycero-3-phosphoethanolamine [DOPE], IV-DOPE, and IV-DSPC). We performed an enzyme-linked immunosorbent assay and enzyme-linked immunosorbent spot assay to compare the ability of the five lipopolyplex adjuvants to enhance the immunogenicity of the SARS-CoV-2 RBD protein, including humoral and cellular immune responses. Finally, the adjuvant with the highest immunogenicity was selected to verify the protective immunity of the vaccine through animal challenge experiments. Results. Recombinant RBD protein has low immunogenicity. The different adjuvants we developed enhanced the immunogenicity of the RBD protein in different ways. Among the lipopolyplexes, those containing DOPE (III-DOPE and IV-DOPE) elicited RBD-specific immunoglobulin G antibody responses, and adjuvants with four components elicited better RBD-specific immunoglobulin G antibody responses than those containing three components (P < 0.05). The IC50 and IC90 titers indicated that the IV-DOPE lipopolyplex had the greatest neutralization ability, with IC50 titers of 1/117,490. Furthermore, in the challenge study, IV-DOPE lipopolyplex protected mice from SARS-CoV-2 infection. On the fourth day after infection, the average animal body weights were reduced by 18.56% (24.164 ± 0.665 g vs. 19.678 ± 0.455 g) and 0.06% (24.249 ± 0.683 g vs. 24.235 ± 0.681 g) in the MOCK and vaccine groups, respectively. In addition, the relative expression of viral RNA in the vaccinated group was significantly lower than that in the MOCK group (P < 0.05). Interstitial inflammatory cell infiltration was observed in the MOCK group, whereas no obvious damage was observed in the vaccinated group. Conclusions. The IV-DOPE–adjuvanted SARS-CoV-2 recombinant RBD protein vaccine efficiently protected mice from SARS-CoV-2 in the animal challenge study. Therefore, IV-DOPE is considered an exceptional adjuvant for SARS-CoV-2 recombinant RBD protein-based vaccines and has the potential to be further developed into a SARS-CoV-2 recombinant RBD protein-based vaccine.

IntroductionSugarcane is one of the most important sugar crops worldwide, however, sugarcane production is seriously limited by sugarcane red rot, a soil-borne disease caused by Colletotrichum falcatum. Bacillus velezensis YC89 was isolated from sugarcane leaves and can significantly inhibited red rot disease caused by C. falcatum.MethodsIn this study, the genome of YC89 strain was sequenced, its genome structure and function were analyzed using various bioinformatics software, and its genome was compared with those of other homologous strains. In addition, the effectiveness of YC89 against sugarcane red rot and the evaluation of sugarcane plant growth promotion were also investigated by pot experiments.ResultsHere, we present the complete genome sequence of YC89, which consists of a 3.95 Mb circular chromosome with an average GC content of 46.62%. The phylogenetic tree indicated that YC89 is closely related to B. velezensis GS-1. Comparative genome analysis of YC89 with other published strains (B. velezensis FZB42, B. velezensis CC09, B. velezensis SQR9, B. velezensis GS-1, and B. amyloliquefaciens DSM7) revealed that the strains had a part common coding sequences (CDS) in whereas 42 coding were unique of strain YC89. Whole-genome sequencing revealed 547 carbohydrate-active enzymes and identified 12 gene clusters encoding secondary metabolites. Additionally, functional analysis of the genome revealed numerous gene/gene clusters involved in plant growth promotion, antibiotic resistance, and resistance inducer synthesis. In vitro pot tests indicated that YC89 strain controlled sugarcane red rot and promoted the growth of sugarcane plants. Additionally, it increased the activity of enzymes involved in plant defense, such as superoxide dismutase, peroxidase, polyphenol oxidase, chitinase, and β-1,3-glucanase.DiscussionThese findings will be helpful for further studies on the mechanisms of plant growth promotion and biocontrol by B. velezensis and provide an effective strategy for controlling red rot in sugarcane plants.

The NAC (NAM, ATAF1/2, and CUC2) transcription factor family is one of the largest families unique to plants and is involved in plant growth and development, organs, morphogenesis, and stress responses. The NAC family has been identified in many plants. As the main source of resistance genes for sugarcane breeding, the NAC gene family in the wild species Saccharum spontaneum has not been systematically studied. In this study, 115 SsNAC genes were identified in the S. spontaneum genome, and these genes were heterogeneously distributed on 25 chromosomes. Phylogenetic analysis divided the SsNAC family members into 18 subgroups, and the gene structure and conserved motif analysis further supported the phylogenetic classification. Four groups of tandemly duplicated genes and nine pairs of segmentally duplicated genes were detected. The SsNAC gene has different expression patterns at different developmental stages of stems and leaves. Further qRT–PCR analysis showed that drought, low-temperature, salinity, pathogenic fungi, and other stresses as well as abscisic acid (ABA) and methyl jasmonate (MeJA) treatments significantly induced the expression of 12 SsNAC genes, indicating that these genes may play a key role in the resistance of S. spontaneum to biotic and abiotic stresses. In summary, the results from this study provide comprehensive information on the NAC transcription factor family, providing a reference for further functional studies of the SsNAC gene.

The evolution of communication technology has driven the demand for intelligent power grids and data analysis in power systems. However, obtaining and annotating electrical data from intelligent terminals is time-consuming and challenging. We propose Meta In-Context Learning (M-ICL), a new approach that harnesses large language models to classify time series electrical data, which largely alleviates the need for annotated data when adapting to new tasks. The proposed M-ICL consists of two stages: meta-training and meta-testing. In meta-training, the model is trained on various tasks that have an adequate amount of training data. The meta-training stage aims to learn the mapping between electrical data and the embedding space of large language models. In the meta-testing stage, the trained model makes predictions on new tasks. By utilizing the in-context learning ability of large language models, M-ICL adapts models to new tasks effectively with only a few annotated instances (e.g., 1–5 training instances per class). Our contributions lie in the new application of large language models to electrical data classification and the introduction of M-ICL to improve the classification performance with the strong in-context learning ability of large language models. Furthermore, we conduct extensive experiments on 13 real-world datasets, and the experimental results show that the proposed M-ICL improves the average accuracy over all datasets by 19.06%, 12.06%, and 6.63% when only one, two, and five training instances for each class are available, respectively. In summary, M-ICL offers a promising solution to the challenges of electrical data classification.

After the outbreak of COVID-19, billions of vaccines with different types have been administrated, including recombinant protein vaccines and mRNA vaccines. Although both types of SARS-CoV-2 vaccine can protect people from viral infection, their differences in humoral and cellular immune responses are still not clearly understood. In this study, we made a head-to-head comparison between an mRNA vaccine candidate and a recombinant protein vaccine we developed previously. Results demonstrated that both vaccine candidates could elicit high specific binding and neutralizing antibody titers in BALB/c mice, but with bias towards different IgG subtypes. Besides, the mRNA vaccine candidate induces higher cellular immune responses than the recombinant protein vaccine. To date, this is the first reported study to directly compare the immune responses of both arms between SARS-CoV-2 mRNA and recombinant vaccines.

Continuous Kr ion irradiation at 400 °C with damage level up to 40 dpa was performed in Zircaloy-4 to investigate the surface damage features of α-Zr matrix. Atomic force microscopy confirms that the irradiation induced surface damage is primarily in the form of damaged pits. The increasing Ra value indicates the gradual surface roughening process with continuous irradiation. The irradiation-induced surface roughening mechanism is suggested as three stages: stage I, the formation and growth along depth direction of damaged pits at low doses; stage II, the extension of damaged region within the surface; stage III, layer by layer removal of surface atoms once the undamaged matrix is depleted.

The effects of electrical pulse width and output irradiance on the inactivation effect of intense pulse light (IPL) are studied in this paper. The measured radiant efficiency of pulsed xenon lamp can be more than 50%, and its irradiance can reach levels 100-times greater than that of a low-pressure mercury lamp. Staphylococcus aureus is used in inactivation experiments. When the irradiance and dose are both constant, there is no significant difference in inactivation efficiency when the pulse width is changed. However, a narrow pulse width corresponding to high irradiance at the same single-pulsed dose displays better inactivation effect. Experimental results are compared between the xenon lamp and low-pressure mercury lamp. The reduction factor (RF) value of the xenon lamp is more than 1.0 higher under the condition of both the same dose and irradiance. In order to achieve the same RF value, the dose of continuous-wave light must be at least three-times greater than that of pulsed light. The spectral action of the pulsed light is also studied. It is confirmed that UVC plays a major role across the whole spectrum. The experimental results show that extreme high-pulsed irradiance presents the main contributing factor behind the excellent bactericidal effect of IPL.

Aiming at the problem of coordinating system economy, security and control performance in secondary frequency regulation of the power grid, a sectional automatic generation control (AGC) dispatch framework is proposed. The dispatch of AGC is classified as three sections with the sectional dispatch method. Besides, a hierarchical multi-agent deep deterministic policy gradient (HMA-DDPG) algorithm is proposed for the framework in this paper. This algorithm, considering economy and security of the system in AGC dispatch, can ensure the control performance of AGC. Furthermore, through simulation, the control effect of the sectional dispatch method and several AGC dispatch methods on the Guangdong province power grid system and the IEEE 39 bus system is compared. The result shows that the best effect can be achieved with the sectional dispatch method.

There is a universal trend toward a data-driven smart grid, which aims to realize two-way communication of energy flow and data flow between various agents across power generation side, transmission&distribution side, electricity retailors and end users. However, the low frequency electrical measurement data accumulated over a long period of time is insignificant for intelligent agents. This paper presents a machine learning method for reconstructing the low frequency electrical measurement data in smart grid. Firstly, the electrical measurement data is converted into electrical images, and then the low frequency electrical measurement data is reconstructed into high frequency electrical measurement data by generative adversarial network to improve the training stability, Wasserstein distance is introduced into the reconstruction mechanism. In addition, by designing the deep residual network based generator, the deep convolutional network based discriminator as well as the perception loss function, the reconstruction accuracy and the high-frequency detail reduction ability are improved. The proposed method is tested on three publicly available datasets and compared with the traditional data reconstruction method, justifying that this method not only can restore high-frequency details with less error, but also can be generalized to different datasets at one location and to datasets at different locations with satisfactory accuracy.

In the current electrical load profile analysis, considering the shortage of traditional methods on the typical load profile extraction of single consumers and the load profile feature extraction, this paper proposes an approach based on time series data mining. Firstly, this method reduces the dimension of the load profile of a single consumer based on the Piecewise Aggregate Approximation(PAA), and re-expresses the load profile of the consumer over a period based on the Symbolic Aggregate approXimation(SAX), representing the consumer's load profile with a symbolic string to extract the typical load profile. Then, combined with the load characteristic indices and time series-based features, the typical load profiles of different consumers are clustered based on the K-means algorithm to analyze the power consumption behaviors. Finally, this paper performs a case analysis with a UCI test data set, and the results show that the proposed approach can excavate typical power consumption behaviors of consumers and improve the electrical load profile analysis efficiency and the clustering quality.

Phenol adsorption by granular activated carbon from coconut shell was studied in batch experiments under various initial phenol concentrations. Adsorption equilibrium was reached within 4 hours. The characteristics of the phenol adsorption process onto granular activated carbon from coconut shell were studied by adsorption isotherm modeling, analysis that uses fluorescence spectroscopy, in addition to measuring nanoparticle size and volume distribution by a Zetasizer Nano. The Langmuir isotherm model best fits the phenol adsorption onto granular activated carbon from coconut shell, and the maximum adsorption capacities for unsterilized and sterilized types were found to be 17.54 mg/g and 13.70 mg/g, respectively. The excitation-emission matrix results showed that the humic-like substance’s peaks almost completely disappear post-adsorption. It was also found that the nanoparticle size distribution shifted from ranges of 0.72–1.74 nm in raw water to 45.66–726.73 nm and 57.08–1068.47 nm post-adsorption in unsterilized and sterilized water samples, respectively, suggesting that phenol adsorption had occurred. This study shows that low-cost coconut shell–based activated carbon demonstrated good removal capability and hence can be used as a new adsorbent material on large scale.

Proton-coupled electron transfer (PCET) process is very important for water oxidation catalysis. Here, the authors introduced uncoordinated carboxylate in the second-coordination-sphere of Ni-Fe coordination polymer catalyst as an internal base to promote the water oxidation kinetics by such PCET process.

Abstract Background The modification effect of leaching fraction (LF) on the physiological responses of plants to irrigation water salinity (ECiw) remains unknown. Here, leaf gas exchange, photosynthetic light–response and CO2–response curves, and total carbon (C) and nitrogen (N) accumulation in hot pepper leaves were investigated under three ECiw levels (0.9, 4.7 and 7.0 dS m− 1) and two LFs treatments (0.17 and 0.29). Results Leaf stomatal conductance was more sensitive to ECiw than the net photosynthesis rate, leading to higher intrinsic water use efficiency (WUE) in higher ECiw, whereas the LF did not affect the intrinsic WUE. Carbon isotope discrimination was inhibited by ECiw, but was not affected by LF. ECiw reduced the carboxylation efficiency, photosynthetic capacity, photorespiration rate, apparent quantum yield of CO2 and irradiance–saturated rate of gross photosynthesis; however, LF did not influence any of these responses. Total C and N accumulation in plants leaves was markedly increased with either decreasing ECiw or increasing LF. Conclusions The present study shows that higher ECiw depressed leaf gas exchange, photosynthesis capacity and total C and N accumulation in leaves, but enhanced intrinsic WUE. Somewhat surprisingly, higher LF did not affect the intrinsic WUE but enhanced the total C and N accumulation in leaves.

The impact of natural organic matter (NOM) and pathogenic bacteria in water are of great concern in water treatment due to their effect on human health. In this study, the ability to combine filtration with an inductively coupled plasma system (ICPS) to remove natural organic matter and pathogenic bacteria from water was investigated. UV260 adsorption, dissolved organic carbon (DOC) and excitation-emission matrices (EEMs) were used to evaluate the removal of NOM by the filtration-ICPS combination. The system was operated at two different flow rates, 100 and 150 ml/minute. Decreasing trend revealed for UV260 and DOC with the higher flow rate. Tryptophan-like substances generally found in water were taken as a measure of microbial activity. This preliminary research shows that the average removal efficiencies for fecal coliforms, total coliforms and salmonella were highest at a flow rate of 100 ml/minute. It can be concluded that the combined filtration-ICPS method is capable of removing NOM and pathogenic bacteria from water.

Siamese network trackers based on pre-trained depth features have achieved good performance in recent years. However, the pre-trained depth features are trained in advance on large-scale datasets, which contain feature information of a large number of objects. There may be a pair of interference and redundant information for a single tracking target. To learn a more accurate target feature information, this paper proposes a lightweight target-aware attention learning network to learn the most effective channel features of the target online. The lightweight network uses a designed attention learning loss function to learn a series of channel features with weights online with no complex parameters. Compared with the pre-trained features, the channel features with weights can represent the target more accurately. Finally, the lightweight target-aware attention learning network is unified into a Siamese tracking network framework to implement target tracking effectively. Experiments on several datasets demonstrate that the tracker proposed in this paper has good performance.

Water oxidation is a vital anodic reaction for renewable fuel generation via electrochemical- and photoelectrochemical-driven water splitting or CO2 reduction. Ruthenium complexes, such as Ru-bda family, have been shown as highly efficient water-oxidation catalysts (WOCs), particularly when they undergo a bimolecular O-O bond formation pathway. In this study, a novel Ru(pda)-type (pda2– =1,10-phenanthroline-2,9-dicarboxylate) molecular WOC with 4-vinylpyridine axial ligands was immobilized on the glassy carbon electrode surface by electrochemical polymerization. Electrochemical kinetic studies revealed that this homocoupling polymer catalyzes water oxidation through a bimolecular radical coupling pathway, where interaction between two Ru(pda)–oxyl moieties (I2M) forms the O-O bond. The calculated barrier of the I2M pathway by density-functional theory (DFT) is significantly lower than the barrier of a water nucleophilic attack (WNA) pathway. By using this polymerization strategy, the Ru centers are brought closer in the distance, and the O-O bond formation pathway by the Ru (pda) catalyst is switched from WNA in a homogeneous molecular catalytic system to I2M in the polymerized film, providing some deep insights into the importance of third coordination sphere engineering of the water oxidation catalyst.

Chondrosarcoma is the second most common bone malignancy in adults, and it is often resistant to traditional chemotherapy and radiation therapy. Permanent implantation of iodine-125 ( 125 I) seeds has been explored for the treatment of many types of cancer. In this study, the aim was to investigate the proliferative and microRNA (miRNA) effects of 125 I seeds irradiation on human chondrosarcoma SW1353 cells. First, a new in vitro 125 I seed irradiation model was established, and cell viability and miRNA microarray assays were performed before and after exposure to the 125 I seeds. Cell proliferation was inhibited, and miRNA expression was substantially altered by irradiation exposure. The inhibition of cell proliferation was positively correlated with increased radiation doses, with cells showing the highest total radiation dose 7 days after irradiation. A total of 2549 miRNAs were detected in the SW1353 cells after exposure to 6 Gy of radiation, which included 189 differentially expressed miRNAs (98 upregulated and 91 downregulated). Four miRNAs were found to play important roles in the inhibition of cell proliferation after irradiation exposure, including miR-1224-5p, miR-492, miR-135b-5p, and miR-6839-5p. The target genes of the associated miRNAs mentioned were vascular endothelial growth factor A ( VEGFA ), C-X-C motif chemokine 12 ( CXCL12 ), mitogen-activated protein kinase kinase kinase kinase 3 ( MAP4K3 ), and apoptosis facilitator Bcl-2-like protein 14 ( BCL2L14 ). Hence, the mitogen-activated protein kinase signaling pathway may be involved in how chondrosarcoma cells respond to 125 I seed irradiation.

Atomic probe tomography (APT) samples with Al/Ni multilayer structure were successfully prepared by using a focused ion beam (FIB), combining with a field emission scanning electron microscope, with a new single-wedge lift-out method and a reduced amorphous damage layer of Ga ions implantation. The optimum vertex angle and preparation parameters of APT sample were discussed. The double interdiffusion relationship of the multilayer films was successfully observed by the local electrode APT, which laid a foundation for further study of the interface composition and crystal structure of the two-phase composites.

The resistance and capacitance parameters of a resistance–capacitance divider may change due to factors such as long-term operation, internal insulation flashover, and dielectric breakdown, which will affect the measurement characteristics of the resistance–capacitance divider. Since it is difficult to separate the voltage divider, and because improper disassembly will damage the insulation of the equipment, measuring the resistance and capacitance parameters of a voltage divider non-destructively has always been a problem. In this paper, an indirect method for evaluating the resistance and capacitance parameters is proposed, and the uncertainty of measurement of this method is determined. Simulation and actual test results show that this method can be used to estimate the resistance–capacitance parameters and has a good level of measurement accuracy. Besides, through the uncertainty analysis, it is concluded that the proposed method can overcome measurement errors within a certain range and has high practicability. Finally, a very practical application scenario of the proposed method is given, showing that the proposed method has good economic significance.

Abstract Alternate partial root–zone drip irrigation (ADI) or fertigation has favorable effect on crop water- and nitrogen- use efficiencies (WUE and NUE). However, the advantage of combined application of ADI and nitrogen fertigation on crop WUE and NUE remains unclear. A pot experiment was conducted to investigate the impact of three irrigation methods (CDI conventional drip irrigation (both halves of pot irrigated), ADI (both halves of pot alternatively irrigated) and FDI fixed partial root–zone drip irrigation (fixed half of pot irrigated)) and five nitrogen treatments (F0 no N supplied, F1-F4 0.2, 0.18, 0.16 and 0.14 g N per kg soil via fertigation) on sweet-waxy maize. Compared with CDI, ADI reduced water consumption by 19.9%, but increased water use efficiency based on dry seed yield (WUEs) by 32.3%, and also enhanced nitrogen apparent recovery fraction (Nrf) and nitrogen agronomic efficiency (NAE). F1-F4 augmented dry mass accumulation, dry seed yield and total nitrogen uptake if compared to F0. Moreover, F2-ADI had higher shoot and total dry masses, WUEs, total nitrogen uptake, Nrf and NAE. Thus ADI increased nitrogen uptake, WUE and NUE of sweet-waxy maize with nitrogen fertigation of 0.18 g N per kg soil in this study.

Onsite wastewater treatment system named Johkasou has been widely applied in the Japanese rural areas, which the effluent is mainly discharged into stream channels. However, Johkasou effluent would potentially be a source of contamination that can deteriorate water and sediment quality of the receiving downstream network. In order to identify the effect of Johkasou effluent particularly in sediment, a study on the distribution of fecal indicators (F-RNA bacteriophages, total coliform (TC), and Escherichia coli [E. coli]) in several sediment spots of local open channels receiving Johkasou effluent was conducted. The results showed that the contents of F-RNA bacteriophages, TC and E. coli in the sediment of open channels were detected in high levels while those contents in the sediment of Johkasou drainage channel were up to two orders magnitude higher than in the open channel. A high number of fecal bacteria in the receiving open channels was majorly influenced by the number of domestic households. Moderate correlations of fecal bacteria indicator with solid sediment and volatile sediment indicate that the sediment particles can be carriers of microbes to the downstream water networks. Therefore, water flushing and hydraulic events are suggested to reduce sediment depth that contained fecal bacteria indicator in the open channel.

Water oxidation is a key component of water splitting, but more effective catalysts for the process are still required. Here the authors synthesize a monolayer nickel-vanadium layered double hydroxide material showing high activity for water oxidation owing to enhanced conductivity and abundant active sites.

Transformerless grid-connected inverters are of great industrial value in photovoltaic power generation. However, the direct current (DC) induced into the inverter’s output degrades the power quality of the grid. Recently, a back-propagation neural work proportional−integral−derivative (BP-PID) scheme has proven helpful in solving this problem. However, this scheme can be improved by reducing the suppressing time and overshoot. A genetic algorithm (GA)-based DC current minimization scheme, namely the genetic-algorithm-based BP-PID (GA-BP-PID) scheme, was established in this study. In this scheme, GA was used off-line to optimize the initial weights within the BP neural network. Subsequently, the optimal weight was applied to the online DC current suppression process. Compared with the BP-PID scheme, the proposed scheme can reduce the suppressing time by 59% and restrain the overshoot. A prototype of the proposed scheme was implemented and tested on experimental hardware as a proof of concept. The results of the scheme were verified using a three-phase inverter experiment. The novel GA-PB-PID scheme proposed in this study was proven efficient in reducing the suppressing time and overshoot.

In order to solve the placement problem of three kinds of feeder terminal units (FTU) in the distribution network, this paper proposes a novel mathematical model. The model considers economic cost and electricity supply reliability from the perspective of life cycle cost. The reliability algorithm in this model is established for the distribution network configured with centralized feeder automation. Different evaluation indices of reliability and the importance of several kinds of customers are also considered in this model. Aiming at the reliability evaluation in this model, this paper puts forward the reliability analysis method for the distribution network with three kinds of FTUs. In view of the difficulty to express the reliability of distribution network in a formula with decision variables, and the non-deterministic polynomial hard (NP-hard) nature of this model, a variety of intelligent algorithms are applied to solve the model. The feasibility and effectiveness of the model and methods for FTUs placement optimization problem are verified by a case study of the Roy Billinton test system (RBTS) Bus 5 system.

It is well known that path planning has always been an important study area for intelligent ships, especially for unmanned surface vehicles (USVs). Therefore, it is necessary to study the path-planning algorithm for USVs. As one of the basic algorithms for USV path planning, the rapidly-exploring random tree (RRT) is popular due to its simple structure, high speed and ease of modification. However, it also has some obvious drawbacks and problems. Designed to perfect defects of the basic RRT and improve the performance of USVs, an enhanced algorithm of path planning is proposed in this study, called the adaptive hybrid dynamic stepsize and target attractive force-RRT(AHDSTAF-RRT). The ability to pass through a narrow area and the forward speed in open areas of USVs are improved by adopting the AHDSTAF-RRT in comparison to the basic RRT algorithm. The improved algorithm is also applied to an actual gulf map for simulation experiments, and the experimental data is collected and organized. Simulation experiments show that the proposed AHDSTAF-RRT in this paper outperforms several existing RRT algorithms, both in terms of path length and calculating speed.

Nuclear logging is one of most important logging services provided by many oil service companies. The main parameters of interest are formation porosity, bulk density, and natural radiation. Other services are also provided from using complex nuclear logging tools, such as formation lithology/mineralogy, etc. Some parameters can be measured by using neutron logging tools and some can only be measured by using a gamma ray tool. To understand the response of nuclear logging tools, the neutron transport/diffusion theory and photon diffusion theory are needed. Unfortunately, for most cases there are no analytical answers if complex tool geometry is involved. For many years, Monte Carlo numerical models have been used by nuclear scientists in the well logging industry to address these challenges. The models have been widely employed in the optimization of nuclear logging tool design, and the development of interpretation methods for nuclear logs. They have also been used to predict the response of nuclear logging systems for forward simulation problems. In this case, the system parameters including geometry, materials and nuclear sources, etc., are pre-defined and the transportation and interactions of nuclear particles (such as neutrons, photons and/or electrons) in the regions of interest are simulated according to detailed nuclear physics theory and their nuclear cross-section data (probability of interacting). Then the deposited energies of particles entering the detectors are recorded and tallied and the tool responses to such a scenario are generated. A general-purpose code named Monte Carlo N– Particle (MCNP) has been the industry-standard for some time. In this paper, we briefly introduce the fundamental principles of Monte Carlo numerical modeling and review the physics of MCNP. Some of the latest developments of Monte Carlo Models are also reviewed. A variety of examples are presented to illustrate the uses of Monte Carlo numerical models for the development of major nuclear logging tools, including compensated neutron porosity, compensated density, natural gamma ray and a nuclear geo-mechanical tool.

Panax notoginseng, a traditional Chinese medicinal plant, has been cultivated and domesticated for approximately 400 years, mainly in Yunnan and Guangxi, two provinces in southwest China. This species was named according to cultivated rather than wild individuals, and no wild populations had been found until now. The genetic resources available on farms are important for both breeding practices and resource conservation. In the present study, the recently developed technology RADseq, which is based on next-generation sequencing, was used to analyze the genetic variation and differentiation of P. notoginseng. The nucleotide diversity and heterozygosity results indicated that P. notoginseng had low genetic diversity at both the species and population levels. Almost no genetic differentiation has been detected, and all populations were genetically similar due to strong gene flow and insufficient splitting time. Although the genetic diversity of P. notoginseng was low at both species and population levels, several traditional plantations had relatively high genetic diversity, as revealed by the He and π values and by the private allele numbers. These valuable genetic resources should be protected as soon as possible to facilitate future breeding projects. The possible geographical origin of Sanqi domestication was discussed based on the results of the genetic diversity analysis.

BACKGROUND:Since Spartina alterniflora (simplified as Spartina) has strong ecological competitiveness and rapid growth, it has been introduced and living in the coastal wetland regions of China for more than 30 years. Taking coastal wetland in the Beibu Gulf of south China as an example, the effects of Spartina invasion on soil quality were investigated to provide scientific basis for soil management. METHODOLOGY:The soil quality of six different coastal wetlands, i.e. mangrove (vegetation coverage is above 95%), mangrove- Spartina ecotones (vegetation coverage is above 95%), sparse mangrove (vegetation coverage is 10%-20%), sparse mangrove- Spartina ecotones (vegetation coverage is about 80%), Spartina (vegetation coverage is about 80%) and bare beach (no plants), were analyzed using the following indicators: pH, cation exchange capacity, contents of total nitrogen, total phosphorus and organic carbon, microbial biomass carbon, microbial biomass nitrogen, microbial carbon / organic carbon, and activities of urease, acid phosphatase, invertase, polyphenol oxidase and catalase. PRINCIPAL FINDINGS:The results showed that compared to mangrove wetland, most indicators in the mangrove-Spartina wetland showed a decline tendency except pH value, and the contents of total phosphorus and organic carbon, microbial biomass carbon and soil microbial biomass nitrogen, and the activities of acid phosphatase and invertase were significantly reduced (P

DpnI can cleave fully methylated parental DNA while leaving hemi-methylated DNA intact. Based on this observation, we developed a rapid site-directed mutagenesis method using uracil-containing, double-stranded (ds)DNA templates and DpnI digestion. A 38% mutation efficiency was achieved by DpnI treatment of the mutagenic strand-extension reaction, and it increased to 70%–91% when uracilcontaining dsDNA templates were used. This method compares favorably to the most efficient current methods, but is simpler and does not require the use of single-stranded templates or phage vectors.

T cell directed HIV vaccines are based upon the induction of CD8+ T cell memory responses that would be effective in inhibiting infection and subsequent replication of an infecting HIV-1 strain, a process that requires a match or near-match between the epitope induced by vaccination and the infecting viral strain. We compared the frequency and specificity of the CTL epitope responses elicited by the replication-defective Ad5 gag/pol/nef vaccine used in the Step trial with the likelihood of encountering those epitopes among recently sequenced Clade B isolates of HIV-1. Among vaccinees with detectable 15-mer peptide pool ELISpot responses, there was a median of four (one Gag, one Nef and two Pol) CD8 epitopes per vaccinee detected by 9-mer peptide ELISpot assay. Importantly, frequency analysis of the mapped epitopes indicated that there was a significant skewing of the T cell response; variable epitopes were detected more frequently than would be expected from an unbiased sampling of the vaccine sequences. Correspondingly, the most highly conserved epitopes in Gag, Pol, and Nef (defined by presence in >80% of sequences currently in the Los Alamos database www.hiv.lanl.gov) were detected at a lower frequency than unbiased sampling, similar to the frequency reported for responses to natural infection, suggesting potential epitope masking of these responses. This may be a generic mechanism used by the virus in both contexts to escape effective T cell immune surveillance. The disappointing results of the Step trial raise the bar for future HIV vaccine candidates. This report highlights the bias towards less-conserved epitopes present in the same vaccine used in the Step trial. Development of vaccine strategies that can elicit a greater breadth of responses, and towards conserved regions of the genome in particular, are critical requirements for effective T-cell based vaccines against HIV-1.ClinicalTrials.gov NCT00849680, A Study of Safety, Tolerability, and Immunogenicity of the MRKAd5 Gag/Pol/Nef Vaccine in Healthy Adults.