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Abstract Background Postoperative refracture of osteoporotic compression fractures in the elderly due to underlying illnesses is a complicated matter involving several variables. A multidisciplinary approach involving orthopedics, geriatrics, endocrinology, and rehabilitation medicine is necessary for an investigation of these issues. investigating the impact of older patients’ underlying medical conditions on the refracture of osteoporotic compression fractures following surgery. Methods A retrospective analysis was conducted on 2383 patients between August 2013 and August 2023. 550 patients with comorbid geriatric underlying diseases were screened, 183 patients underwent refractories, and 367 patients were classified as non-refractories. The patients were then divided into two groups: those undergoing refractories and those not, and the underlying diseases of the patients in both groups were examined using ROC curves and unifactorial and multifactorial logistic regression analyses. Results Among the patients gathered, the frequency of re-fracture was 33.3%. A statistically significant difference was observed when re-fracture was linked to patients with long-term alcohol consumption, operated vertebrae ≤ 1, hypertension, COPD, diabetes mellitus, stroke sequelae, conservative treatment of coronary heart disease, trauma, mental abnormality, scoliosis, and chronic renal disease. Having hypertension decreased the risk of re-fracture (P = 0.018, OR = 0.548), while alcohol intake ≥ 10years (P = 0.003, OR = 2.165), mental abnormality (P

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.

To alleviate the difficulty in detecting and recognizing erect rail barricades, a forward-looking three-dimensional(3D) imaging sonar is used to improve the effectiveness of erect rail barricade recognition, and a single shot detector(SSD)-based 3D point cloud(PCSSD) target recognition method is proposed. First, the original beam domain data are processed using a threshold filter and pass-through filter. Next, forward projection of the filtered 3D point cloud data is performed, and the grayscale depth image and pseudo color depth image are obtained. The SSD was then used to recognize the targets from the pseudo color depth image. Subsequently, the depth range of the selected targets is calculated based on the characteristics of the targets recognized from the grayscale depth image. Finally, erect rail barricades in the form of 3D point clouds were detected by combining the two-dimensional detection results and the corresponding depth range. A feature extraction block based on the multi-scale attention mechanism was proposed, and a novel target detector SSD-MV3ME was used for the design. On the 3D point cloud erect rail barricades dataset GTZ, under the condition of the same detection time, the detection accuracy of SSD-MV3ME was higher than that of the lightweight target detection model SSD-MV3 by 1.05%, and the model parameters had less than 2 482 kB. The results show that the PCSSD based on SSD-MV3ME is more suitable for erect rail barricade recognition tasks.

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.