Search

We research the mutual correlation and chaotic behavior in phantom Anti-de Sitter (AdS) black holes based mainly on shock wave geometry. In the static background of the phantom spacetime, by analyzing mutual correlation, we find out that the greater the phantom dark energy parameter is, the smaller the mutual correlation becomes, which implies phantom dark energy can destroy bilateral correlation of the two sub-regions from the AdS boundary. In the dynamic background, the results show that, the greater the applied energy perturbation is, the smaller the mutual correlation becomes. Especially, the bigger the phantom dark energy is exerted, the faster the mutual correlation destroys. This is similar to the butterfly effect of chaos theory.

Lyophyllum consists of rare edible and medicinal mushrooms. Considering this group’s economic and ecological significance, understanding its biodiversity could be strategically important. Our analysis involved an extensive examination of publicly available ITS sequences from NCBI-GenBank and fungal amplicon sequencing data obtained from NCBI-SRA. At a 98% sequence similarity level, we deliminated 88 Lyophyllum OTUs, 49 of which were not categorized as ‘known species’. The diversity of Lyophyllum is predominantly concentrated in the Northern Hemisphere and tends to display endemic distribution, and Europe is particularly notable for its high diversity of Lyophyllum. Given the escalating volume of data produced by amplicon sequencing, employing the amplicon dataset can facilitate an accurate survey of species diversity in Lyophyllum taxonomy. By using data from amplicon datasets, the fieldwork time and research funding for taxonomists can be saved, thereby significantly advancing the progress of the entire field of biodiversity research.

A new myxomycete species, Didymium arenosum, was described based on morphological evidence and phylogenetic analyses. The species was discovered in the arid region at the confluence of the Badain Jaran desert and Tengger desert on the leaves of Betula platyphylla and was cultivated in a moist chamber culture. Morphologically, the species is distinguished by the greenish-yellow calcium carbonate crystals on the surface and the spores covered with small warts, some of which are connected into a short line. A phylogenetic analysis of D. arenosum strongly supports its classification as a separate clade. The spore to spore agar culture of D. arenosum requires 23 days, and this study provides a detailed description of its life cycle.

Background: Histone deacetylase 3 (HDAC3) restores chromatin nucleosomes to a transcriptional repression state, thereby inhibiting gene expression. Studies have found that HDAC3 expression is upregulated in a variety of pathological states of the central nervous system and related to its neurotoxicity. However, the role of HDAC3 in surgical brain injury (SBI) has not been thoroughly explored. Objective: To observe the role of HDAC3 in SBI and the outcome of SBI after its suppression. Methods: Rat SBI model was used, and intraperitoneal injection of RGFP966 (HDAC3 specific inhibitor) was used to detect the changes of HDAC3 expression and neuronal apoptosis indexes in the surrounding cortex of SBI rats, and the cerebral edema and neurological outcome of rats were observed. Results: The expression of HDAC3 in the peripheral cortex of SBI rats was increased, and RGFP966 inhibited the upregulation of HDAC3 and saved the nerve cells around the damaged area. In addition, RGFP966 increased the expression of anti-oxidative stress proteins such as heme oxygenase-1 (HO-1) and superoxide dismutase 2 (SOD2). At the same time, the expression of apoptotic marker protein cleaved-caspase-3 (cle-caspase-3) was decreased, while the expression level of apoptotic protective marker protein B-cell lymphoma 2 (Bcl-2) was increased. In addition, this research demonstrated that in the RGFP966 rat SBI model, the expression level of antioxidant modifier nuclear factor-erythroid 2-related factor 2 (Nrf2) was increased. Conclusion: RGFP966 might activate HDAC3/Nrf2 signaling pathway by inhibiting HDAC3, regulated oxidative stress and nerve cell apoptosis induced by SBI in rat SBI model, reduced brain edema, and had a protective effect on nerve injury. It might be a potential target of SBI pathology.

Abstract Background Myxomycetes are a group of eukaryotes belonging to Amoebozoa, which are characterized by a distinctive life cycle, including the plasmodium stage and fruit body stage. Plasmodia are all found to be associated with bacteria. However, the information about bacteria diversity and composition in different plasmodia was limited. Therefore, this study aimed to investigate the bacterial diversity of plasmodia from different myxomycetes species and reveal the potential function of plasmodia-associated bacterial communities. Results The bacterial communities associated with the plasmodia of six myxomycetes (Didymium iridis, Didymium squamulosum, Diderma hemisphaericum, Lepidoderma tigrinum, Fuligo leviderma, and Physarum melleum) were identified by 16S rRNA amplicon sequencing. The six plasmodia harbored 38 to 52 bacterial operational taxonomic units (OTUs) that belonged to 7 phyla, 16 classes, 23 orders, 40 families, and 53 genera. The dominant phyla were Bacteroidetes, Firmicutes, and Proteobacteria. Most OTUs were shared among the six myxomycetes, while unique bacteria in each species only accounted for a tiny proportion of the total OTUs. Conclusions Although each of the six myxomycetes plasmodia had different bacterial community compositions, a high similarity was observed in the plasmodia-associated bacterial communities' functional composition. The high enrichment for gram-negative (> 90%) and aerobic (> 99%) bacteria in plasmodia suggest that myxomycetes may positively recruit certain kinds of bacteria from the surrounding environment.

Electromagnetic coil launch is an important branch of electromagnetic launch (EML) technology, which is suitable for launching anti-torpedo torpedo (ATT). This paper focuses on the EML parameters and the interception probability of the EML two ATTs salvo. Based on the launching model of a multi-stage coil launcher, the trajectory model of the ATT and the attacking torpedo, a calculation method for the EML two ATTs salvo parameters is proposed, with the conditions of capture and interception given reasonably. An adaptive particle swarm optimization (APSO) algorithm is proposed to calculate the optimal launching parameters, by designing the adaptive inertia weight and time-varying study factors. According to the analysis of the simulation with Monte Carlo method, EML will improve the interception probability effectively, and the interception probability is affected by the launching range. The results demonstrate good performance of the proposed APSO in calculating EML parameters for the two ATTs salvo in certain combat situation. Implications of these results are particular regarding the command and decision in the anti-torpedo combat.

With the deep integration of computer technology into social life,more and more short text messages are spreaded all over the web platform.Aiming at the problem of data sparsity of short texts,a robust heterogeneous information network framework(HTE) for modeling short texts,which can integrate any type of additional information and capture the relationship between them to solve the data sparsity problem,is constructed.Based on this framework,six short text expansion methods are designed using different external knowledge,and the short text features are enriched by introducing entity information such as entities,entity categories,inter-entity relationships and textual information such as text topics from Wikipedia and Freebase knowledge bases.Finally,the similarity measurement result is used to verify the experimental effect.By comparing the six text expansion me-thods with the traditional three similarity measures on two short text datasets and the current mainstream short text matching algorithms,the results of the proposed six text expansion methods are improved.Compared with BERT,the similarity measurement results of the best method improves by 5.97%.The proposed framework is robust and can include any type of external know-ledge,and the proposed method can overcome the data sparsity problem of short texts and can perform similarity metrics on short texts with high accuracy in an unsupervised manner.

The transportation sector is under increasing pressure to reduce greenhouse gas emissions by decarbonizing its operations. One prominent solution that has emerged is the adoption of electric vehicles (EVs). As the electric vehicles market experiences rapid growth, the utilization of lithium-ion batteries (LiB) has become the predominant choice for energy storage. However, it is important to note that lithium-ion battery technology is sensitive to factors, like excessive voltage and temperature. Therefore, the development of an accurate battery model and a reliable state of charge (SOC) estimator is crucial to safeguard against the overcharging and over-discharging of the battery. Numerous studies have been conducted to address lithium-ion battery cell modeling and SOC estimations. These studies have explored variations in the number of RC networks within the model and different estimation methods. However, it is worth mentioning that the capacity of a single lithium-ion battery cell is relatively low and cannot be directly employed in electric vehicles. To meet the total capacity and voltage requirements for electric vehicles, multiple cells are typically connected in series or parallel configurations to form a battery pack. Surprisingly, this aspect has often been overlooked in previous research. To tackle this overlooked challenge, our study introduces a comprehensive battery pack model and an advanced Battery Management System (BMS). We then integrate these components into an electric vehicle model. Subsequently, we simulate the integrated EV-BMS model under the conditions of four different urban driving scenarios to replicate real-world driving conditions. The BMS that we have developed includes an Extended Kalman Filter (EKF)-based SOC estimation system, a mechanism for controlling coolant flow, and a passive cell-balancing algorithm. These components work together to ensure the safe and efficient operation of the battery pack within the electric vehicles.