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Heterogeneous Information Networks (HINs) are ubiquitous in our daily life, as they can describe complex interactions among various types of objects. Heterogeneous information network embedding aims to project the network elements of HINs into low-dimensional node representation vectors, which can facilitate effective analyze of HINs. To learn appropriate HIN embeddings, most existing methods usually adopt meta-paths to capture the heterogeneous semantic information, which require domain knowledge and trial-and-error to find suitable meta-paths. Besides, most existing methods fail to preserve high-order local structural information, and pay little attention to the implicit semantics in HINs. In this paper, we propose a local structural aware heterogeneous information network embedding model named LSA-HNE. Specifically, we first design a relational self-attention graph neural network model to aggregate heterogeneous information and automatically extract semantic similarity without using meta-paths. In addition, we employ a biased random walk based sampling method to extract the local structural information and preserve the implicit semantics in HINs. The experiments conducted on four real-world datasets show that our proposed model is effective compared with the state-of-the-art methods.

Abstract Background Several models have been developed to predict asymptomatic carotid stenosis (ACS), however these models did not pay much attention to people with lower level of stenosis (

ObjectiveTo analyze treatment strategies, prognosis, and related risk factors of patients with postinfarction ventricular septal rupture, as well as the impact of timing of surgical intervention.MethodsA total of 23 patients diagnosed with postinfarction ventricular septal rupture who were non-selectively admitted to Shanxi Provincial Cardiovascular Hospital between October 2017 and August 2021 were included in this study. The relevant clinical data, operation-related conditions, and follow-up data were summarized for all patients. The Kaplan-Meier method and log-rank test were used for the cumulative incidence of unadjusted mortality in patients with different treatment methods. Multivariate logistic regression was used to evaluate the independent risk factors for in-hospital patient mortality.ResultsThe mean age of the study patients was 64.43 ± 7.54 years, 12(52.2%) were females. There was a significant difference in terms of postoperative residual shunt between the surgical and interventional closure groups (5.9 vs. 100%, respectively; P < 0.001). The overall in-hospital mortality rate was 21.7%; however, even though the surgical group had a lower mortality rate than the interventional closure group (17.6 vs. 33%, respectively), this difference was not statistically significant (P = 0.576). Univariate analysis showed that in-hospital survival group patients were significantly younger than in-hospital death group patients (62.50 ± 6.53 vs. 71.40 ± 7.37 years, respectively; P = 0.016), and that women had a significantly higher in-hospital mortality rate than men (P = 0.037). The average postoperative follow-up time was 18.11 ± 13.92 months; as of the end of the study all 14 patients in the surgical group were alive, Two out of four patients survived and two patients died after interventional closure. Univariate analysis showed that interventional closure was a risk factor for long-term death (P < 0.05).ConclusionSurgical operation is the most effective treatment for patients with postinfarction ventricular septal rupture; however, the best timing of the operation should be based on the patient's condition and comprehensively determined through real-time evaluation and monitoring. We believe that delaying the operation time as much as possible when the patient's condition permits can reduce postoperative mortality. Interventional closure can be used as a supplementary or bridge treatment for surgical procedures.

People from all social circles are concerned about the big data,because all of them think that big data is valuable.However,different people have different value expectation,all of which are the goals when implementing big data project.Multiple kinds of definitions and understandings of big data were attempted to indicate,and then different research perspectives and different value expectations from different people were introduced.Furthermore,some practical and feasible methods,ideas and strategies were given after briefly expressing the relevant research status and industrialization status.

The hierarchical and porous nanomaterials usually present excellently physicochemical functions. Here, we report the successful preparation of three different ZnSnO3 nanocubes using different surfactant by one-pot hydrothermal method. The as-prepared hierarchical and porous ZnSnO3 nanocube was assisted by NaF, which exhibited the largest specific surface area and the maximum quantity of oxygen vacancy. Moreover, the film sensor made of hierarchical and porous ZnSnO3 nanocubes showed the most superior gas sensing performance to formaldehyde compared with that of the other two nanocubes. This unique hierarchical and porous ZnSnO3 nanocubes hold substantial promise to be a potential gas-sensing material to detect formaldehyde. Keywords: ZnSnO3, Hierarchical, Porous materials, Sensors, Formaldehyde

Elliptic Curve Cryptography (ECC) represents a promising public-key cryptography system due to its ability to achieve the same level of security as RSA with a significantly smaller key size. ECC stands out for its time efficiency and optimal resource utilization. This paper introduces two distinct new software implementations of ECC over the finite field GF(p), utilizing character arrays and bit sets. Our implementations operate on ECC curves of the form y² ≡ x³+ax+b mod p. We have optimized the point addition operation and scalar multiplication on a real SEC (Standards for Efficient Cryptography) ECC curve over a prime field. Furthermore, we have tested and validated the Elliptic Curve ElGamal encryption/decryption system and the Elliptic Curve Digital Signature Algorithm (ECDSA) on a real SEC ECC curve with two different implementations of the big integer classes, and compared and analyzed their performances. [ABSTRACT FROM AUTHOR]