The papain-like cysteine proteases (PLCPs), the most important group of cysteine proteases, have been reported to participate in the regulation of growth, senescence, and abiotic stresses in plants. ...However, the functions of PLCPs and their roles in stress response in microalgae was rarely reported. The responses to different abiotic stresses in
were often observed, including growth regulation and astaxanthin accumulation. In this study, the cDNA of
containing 1515 bp open reading frame (ORF) was firstly cloned from
by RT-PCR. The analysis of protein domains and molecular evolution showed that
was closely related to
from
. The expression pattern analysis revealed that it significantly responds to NaCl stress in
. Subsequently, transformants expressing
in
were obtained and subjected to transcriptomic analysis. Results showed that
might affect the cell cycle regulation and DNA replication in transgenic
, resulting in abnormal growth of transformants. Moreover, the expression of
might increase the sensitivity to NaCl stress by regulating ubiquitin and the expression of WD40 proteins in microalgae. Furthermore, the expression of
might improve chlorophyll content by up-regulating the expression of NADH-dependent glutamate synthases in
. This study indicated for the first time that
was involved in the regulation of cell growth, salt stress response, and chlorophyll synthesis in microalgae. Results in this study might enrich the understanding of PLCPs in microalgae and provide a novel perspective for studying the mechanism of environmental stress responses in
.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In the field of network security, although there has been related work on software vulnerability detection based on classic machine learning, detection ability is directly proportional to the scale ...of training data. A quantum neural network has been proven to solve the memory bottleneck problem of classical machine learning, so it has far-reaching prospects in the field of vulnerability detection. To fill the gap in this field, we propose a quantum neural network structure named QDENN for software vulnerability detection. This work is the first attempt to implement word embedding of vulnerability codes based on a quantum neural network, which proves the feasibility of a quantum neural network in the field of vulnerability detection. Experiments demonstrate that our proposed QDENN can effectively solve the inconsistent input length problem of quantum neural networks and the problem of batch processing with long sentences. Furthermore, it can give full play to the advantages of quantum computing and realize a vulnerability detection model at the cost of a small amount of measurement. Compared to other quantum neural networks, our proposed QDENN can achieve higher vulnerability detection accuracy. On the sub dataset with a small-scale interval, the model accuracy rate reaches 99%. On each subinterval data, the best average vulnerability detection accuracy of the model reaches 86.3%.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Short text representation is one of the basic and key tasks of NLP. The traditional method is to simply merge the bag-of-words model and the topic model, which may lead to the problem of ambiguity in ...semantic information, and leave topic information sparse. We propose an unsupervised text representation method that involves fusing word embeddings and extended topic information. Following this, two fusion strategies of weighted word embeddings and extended topic information are designed: static linear fusion and dynamic fusion. This method can highlight important semantic information, flexibly fuse topic information, and improve the capabilities of short text representation. We use classification and prediction tasks to verify the effectiveness of the method. The testing results show that the method is valid.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The histone acetyltransferases (HATs), together with histone deacetylases, regulate the gene transcription related to various biological processes, including stress responses in eukaryotes. This ...study found a member of HATs (
) from a transcriptome of the economically important microalgae
. Its expression pattern responding to multiple abiotic stresses and its correlation with transcription factors and genes involved in triacylglycerols and astaxanthin biosynthesis under stress conditions were evaluated, aiming to discover its potential biological function. The isolated
was 1,712 bp in length encoding 415 amino acids. The signature domains of Acetyltransf_1 and BROMO were presented, as the GCN5 gene from
and
, confirming that
belongs to the GCN5 subfamily of the GNAT superfamily. The phylogenetic analysis revealed that
is grouped with GNAT genes from algae and is closer to that from higher plants, compared with yeast, animal, fungus, and bacteria. It was predicted that
is composed of 10 exons and contains multiple stress-related
-elements in the promoter region, revealing its potential role in stress regulation. Real-time quantitative PCR revealed that
responds to high light and high salt stresses in similar behavior, evidenced by their down-regulation exposing to stresses. Differently,
expression was significantly induced by SA and Nitrogen-depletion stresses at the early stage but was dropped back after then. The correlation network analysis suggested that
has a strong correlation with major genes and a transcription factor involved in astaxanthin biosynthesis. Besides, the correlation was only found between
and a few genes involved in triacylglycerols biosynthesis. Therefore, this study proposed that
might play a role in the regulation of astaxanthin biosynthesis. This study firstly examined the role of HATs in stress regulation and results will enrich our understanding of the role of HATs in microalgae.
Dependency parsing aims to analyze the syntactic structure of sentences from the perspective of linguistics.Existing studies suggest that combining such graph-like data with graph convolutional ...network（GCN） can help model better understand the text semantics.However, when dealing with dependency syntactic information as adjacency matrix, these methods ignore the types of syntactic dependency tags and the word semantics related to the tags, which makes the model unable to capture the deep emotional features.To solve the preceding problem, this paper proposes a Chinese short text sentiment analysis model CDSI（context and dependency syntactic information）.This model can use BiLSTM（bidirectional long short-term memory） network to extract the context semantics of the text.Moreover, a dependency-aware embedding representation method is introduced to mine the contribution weights of different dependent paths to the sentiment classification task based on the syntactic structure.Then the GCN is used to model the conte
The integration of distributed generation resources, including electric vehicles (EVs), has become increasingly important in supplying grid loads. EVs have the potential to act as a distributed ...generation source and help reduce the electrical company's expenses. However, their extensive use in distribution networks may cause some difficulties for the electricity grids, such as economic and scientific functioning problems and the potential for other applications. In this study, we propose a model to control coordinated and uncoordinated charging systems of grid-connected electric cars using two wind turbines and one solar power plant as distributed generation sources. The model divides EVs into four classes based on their grid shares and the number of accidental vehicles per class, utilizing the normal distribution function. The suggested model is solved using a hybrid firefly and cuckoo method. The goal function of the model is a combination of yearly energy loss cost and the operational cost of distributed generating units. The simulation, conducted on a 33-bus IEEE grid, demonstrates that the proposed model is highly effective and efficient. The results indicate that random EV charging leads to significantly higher expenses compared to the coordinated charging approach. Additionally, the peak demand reduces when EV charging is coordinated.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Antibacterial hydrogel wound dressings hold great potential in eliminating bacteria and accelerating the healing process. However, it remains a challenge to fabricate hydrogel wound dressings that ...simultaneously exhibit excellent mechanical and photothermal antibacterial properties. Here we report the development of polydopamine-functionalized graphene oxide (rGO@PDA)/calcium alginate (CA)/Polypyrrole (PPy) cotton fabric-reinforced hydrogels (abbreviated as rGO@PDA/CA/PPy FHs) for tackling bacterial infections. The mechanical properties of hydrogels were greatly enhanced by cotton fabric reinforcement and an interpenetrating structure, while excellent broad-spectrum photothermal antibacterial properties based on the photothermal effect were obtained by incorporating PPy and rGO@PDA. Results indicated that rGO@PDA/CA/PPy FHs exhibited superior tensile strength in both the warp (289 ± 62.1 N) and weft directions (142 ± 23.0 N), similarly to cotton fabric. By incorporating PPy and rGO@PDA, the swelling ratio was significantly decreased from 673.5% to 236.6%, while photothermal conversion performance was significantly enhanced with a temperature elevated to 45.0 °C. Due to the synergistic photothermal properties of rGO@PDA and PPy, rGO@PDA/CA/PPy FHs exhibited excellent bacteria-eliminating efficiency for
(0.57%) and
(3.58%) after exposure to NIR for 20 min. We believe that the design of fabric-reinforced hydrogels could serve as a guideline for developing hydrogel wound dressings with improved mechanical properties and broad-spectrum photothermal antibacterial properties for infected-wound treatment.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Metallic nanocrystals exhibit superior properties to their bulk counterparts because of the reduced sizes, diverse morphologies, and controllable exposed crystal facets. Therefore, the fabrication of ...metal nanocrystals and the adjustment of their properties for different applications have attracted wide attention. One of the typical examples is the fabrication of nanocrystals encased with high-index facets, and research on their magnified catalytic activities and selections. Great accomplishment has been achieved within the field of noble metals such as Pd, Pt, Ag, and Au. However, it remains challenging in the fabrication of base metal nanocrystals such as Ni, Cu, and Co with various structures, shapes, and sizes. In this paper, the synthesis of metal nanocrystals is reviewed. An introduction is briefly given to the metal nanocrystals and the importance of synthesis, and then commonly used synthesis methods for metallic nanocrystals are summarized, followed by specific examples of metal nanocrystals including noble metals, alloys, and base metals. The synthesis of base metal nanocrystals is far from satisfactory compared to the tremendous success achieved in noble metals. Afterwards, we present a discussion on specific synthesis methods suitable for base metals, including seed-mediated growth, ligand control, oriented attachment, chemical etching, and Oswald ripening, based on the comprehensive consideration of thermodynamics, kinetics, and physical restrictions. At the end, conclusions are drawn through the prospect of the future development direction.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Nowadays, the time lag between vulnerability discovery and the timely remediation of the vulnerability is extremely important to the current state of cybersecurity. Unfortunately, the silent security ...patch presents a significant challenge. Despite related work having been conducted in this area, the patch identification lacks interpretability. To solve this problem, this paper first proposes a trusted multi-view security patch identification system called TMVDPatch. The system obtains evidence from message commit and code diff views respectively, and models the uncertainty of each view based on the D-S evidence theory, thereby providing credible and interpretable security patch identification results. On this basis, this paper performs weighted training on the original evidence based on the grey relational analysis method to improve the ability to make credible decisions based on multi-views. Experimental results show that the multi-view learning method exhibits excellent capabilities in terms of the complementary information provided by control dependency and data dependency, and the model shows strong robustness across different hyperparameter settings. TMVDPatch outperforms other models in all evaluation metrics, achieving an accuracy of 85.29% and a F1 score of 0.9001, clearly verifying the superiority of TMVDPatch in terms of accuracy, scientificity, and reliability.
Fouling is a great problem that significantly affects the continuous operation for large-scale radio-frequency (RF) thermal plasma synthesizing nanopowders. In order to eliminate or weaken the ...phenomenon, numerical simulations based on FLUENT software were founded to investigate the effect of operation parameters, including feeding style of central gas and sheath gas, on plasma torches. It is shown that the tangential feeding style of central gas brings serious negative axial velocity regions, which always forces the synthesized nanopowders to "back-mix", and further leads to the fouling of the quartz tube. Moreover, it is shown that sheath gas should be tangentially fed into the plasma reactor to further eliminate the gas stream's back-mixing. However, when this feeding style is applied, although the negative axial velocity region is decreased, the plasma gas and kinetic energy of the vapor phase near the wall of the plasma reactor are less and lower, respectively; as a result, that plasma flame is more difficult to be arced. A new plasma arcing method by way of feeding gun instead of torch wall was proposed and put in use. The fouling problem has been well solved and plasma arcing is well ensured, and as a result, the experiment on large-scale production of nanopowders can be carried out for 8 h without any interruption, and synthesized Si and Al
O
nanopowders exhibit good dispersion and sphericity.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
PDF
