187 research outputs found

    Generic Construction of Server-Aided Revocable Hierarchical Identity-Based Encryption with Decryption Key Exposure Resistance

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    In this paper, we extend the notion of server-aided revocable identity-based encryption (SR-IBE) to the hierarchical IBE (HIBE) setting and propose a generic construction of server-aided revocable hierarchical IBE (SR-HIBE) schemes with decryption key exposure resistance (DKER) from any (weak) L-level revocable HIBE scheme without DKER and (L+1)-level HIBE scheme. In order to realize the server-aided revocation mechanism, we use the “double encryption” technique, and this makes our construction has short ciphertext size. Furthermore, when the maximum hierarchical depth is one, we obtain a generic construction of SR-IBE schemes with DKER from any IBE scheme and two-level HIBE scheme

    Testing Two Student Nurse Stress Instruments in Chinese Nursing Students:A Comparative Study Using Exploratory Factor Analysis

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    Background. The development and transformation of nursing within professional tertiary education have exerted a great pressure and challenge upon nursing students. Stress experienced by nursing students is a common precursor of psychological distress and attrition. However, no scale is specifically used to evaluate the sources of stress experienced by nursing students in Mainland China. Aims and Objective. This study is aimed at testing and comparing the reliability and validity including sensitivity and specificity of two nursing students’ stress instruments, the Chinese version of Student Nurse Stress Index Scale (SNSI-CHI), and the Stressors in Student Nursing Scale (SINS-CN) in Chinese nursing students, and describing the stress status of nursing students in China. Methods. A cross-sectional survey was conducted in two nursing schools in Henan Province from August 2017 to January 2018. Data were collected by using a questionnaire comprising the Chinese version of SNSI (SNSI-CHI), the Chinese version of SINS (SINS-CN), and the Chinese Perceived Stress Scale (CPSS). Homogeneity and stability, content, construct and concurrent validity, and sensitivity and specificity were assessed. Results. The Cronbach’s alpha (α) of SNSI-CHI was 0.90, and the item-to-total correlations ranged from 0.35 to 0.66. The Cronbach’s α of SINS-CN was 0.93, and the item-to-total correlations ranged from 0.19 to 0.61. The findings of exploratory factor analysis (EFA) confirmed a good construct validity of SNSI-CHI and SINS-CN. The Pearson’s rank correlation coefficients, between total scores of SNSI-CHI and CPSS and SINS-CN and CPSS, were assessed to 0.38 (P<0.01) and 0.39 (P<0.01), respectively. Regarding the CPSS, as the criterion, the cut-points of SNSI-CHI and SINS-CN for the area under the receiver operator characteristic (ROC) curve were 0.77and 0.66, respectively. Conclusion. Both scales are valid and reliable for evaluating the source of stress of student nurses in China. Each has its own characteristics, but the SNSI-CHI demonstrated marginal advantage over the SINS-CN. The SNSI-CHI is short, is easily understood, and with clear dimension for the nursing students, and the SNSI-CHI is more acceptable for the users in China

    Association of N-acetylcysteine use with contrast-induced nephropathy: an umbrella review of meta-analyses of randomized clinical trials

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    BackgroundThe effectiveness of N-acetylcysteine (NAC) in treating contrast-induced nephropathy (CIN) has been the subject of conflicting meta-analyses, but the strength of the evidence for these correlations between NAC use and CIN has not been measured overall.ObjectiveTo evaluate the data from randomized clinical studies (RCTs) that examined the relationships between NAC use and CIN in meta-analyses.MethodsBetween the creation of the database and April 2023, searches were made in PubMed, Cochrane Library, EMBASE, and Web of Science. N-acetylcysteine, contrast-induced nephropathy, or contrast-induced renal disease were among the search keywords used, along with terms including systematic review and meta-analysis. The Assessment of Multiple Systematic Reviews, version 2, which assigned grades of extremely low, low, moderate, or high quality to each meta-analysis’s scientific quality, was used to evaluate each meta-analysis. The confidence of the evidence in meta-analyses of RCTs was evaluated using the Grading of Recommendation, Assessment, Development and Evaluations method, with evidence being rated as very low, low, moderate, or high.ResultsIn total, 493 records were screened; of those, 46 full-text articles were assessed for eligibility, and 12 articles were selected for evidence synthesis as a result of the screening process. Based on the pooled data, which was graded as moderate-quality evidence, it can be concluded that NAC can decrease CIN (OR 0.72, 95% CI 0.65–0.79, p &lt; 0.00001) and blood levels of serum creatinine (MD −0.09, 95% CI −0.17 to −0.01, p = 0.03). In spite of this, there were no associations between NAC and dialysis requirement or mortality in these studies.ConclusionThe results of this umbrella review supported that the renal results were enhanced by NAC. The association was supported by moderate-quality evidence.Systematic review registration[https://clinicaltrials.gov/], identifier [CRD42022367811]

    FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Objection

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    Multi-sensor modal fusion has demonstrated strong advantages in 3D object detection tasks. However, existing methods that fuse multi-modal features through a simple channel concatenation require transformation features into bird's eye view space and may lose the information on Z-axis thus leads to inferior performance. To this end, we propose FusionFormer, an end-to-end multi-modal fusion framework that leverages transformers to fuse multi-modal features and obtain fused BEV features. And based on the flexible adaptability of FusionFormer to the input modality representation, we propose a depth prediction branch that can be added to the framework to improve detection performance in camera-based detection tasks. In addition, we propose a plug-and-play temporal fusion module based on transformers that can fuse historical frame BEV features for more stable and reliable detection results. We evaluate our method on the nuScenes dataset and achieve 72.6% mAP and 75.1% NDS for 3D object detection tasks, outperforming state-of-the-art methods

    International innovation collaboration of business and higher education in a framework of the Chinese global initiative "One belt - one road: background and prospects

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    The actual direction of development of small and medium-sized businesses in Ukraine at the present stage is the activation of foreign economic activity and the development of foreign commodity markets. Expansion of cooperation with foreign partners and joint implementation of geostrategic projects appear to be a promising direction for solving this problem. Great prospects for small and medium-sized businesses in Ukraine are associated with participation in the projects of the Chinese global initiative "One Belt, One Road". The purpose of this study is to study the trends of interaction between Ukraine and China in the economic sphere and to determine the possibilities of expanding the access of Ukrainian companies to the implementation of projects within the framework of the geostrategic concept "One Belt, One Road". The article is devoted to the results of a study of Chinese - Ukrainian economic cooperation with the participation of small and medium-sized businesses. According to the results of the study are highlighted processes of the spread of global value chains and the increasing role of small and medium-sized businesses in creating added value in the Interaction between China and Ukraine in the field of participation of small and medium-sized businesses in the implementation of projects of the global initiative "One Belt, One Road" was indicated. Besides of foreign trade relations analysis, perspectives of joint education and research projects as the important indicator of the smart future business development and application of the legal framework of Ukrainian-Chinese relations were indicated

    Observation of first-order quantum phase transitions and ferromagnetism in twisted double bilayer graphene

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    Twisted graphene multilayers are highly tunable flatband systems for developing new phases of matter. Thus far, while orbital ferromagnetism has been observed in valley polarized phases, the long-range orders of other correlated phases as well as the quantum phase transitions between different orders mostly remain unknown. Here, we report an observation of Coulomb interaction driven first-order quantum phase transitions and ferromagnetism in twisted double bilayer graphene (TDBG). At zero magnetic field, the transitions are revealed in a series of step-like abrupt resistance jumps with prominent hysteresis loop when either the displacement field (D) or the carrier density (n) is tuned across symmetry-breaking boundary near half filling, indicating a formation of ordered domains. It is worth noting that the good turnability and switching of these states gives a rise to a memory performance with a large on/off ratio. Moreover, when both spin and valley play the roles at finite magnetic field, we observe abundant first-order quantum phase transitions among normal metallic states from charge neutral point, orbital ferromagnetic states from quarter filling, and spin-polarized states from half filling. We interpret these first-order phase transitions in the picture of phase separations and spin domain percolations driven by multi-field tunable Coulomb interactions, in agreement with Lifshitz transition from Hartree-Fock calculations. The observed multi-filed tunable domain structure and its hysteresis resembles the characteristics of multiferroics, revealing intriguing magnetoelectric properties. Our result enriches the correlated phase diagram in TDBG for discovering novel exotic phases and quantum phase transitions, and it would benefit other twisted moir\'e systems as well

    Detection Study of Bipolar Depression Through the Application of a Model-Based Algorithm in Terms of Clinical Feature and Peripheral Biomarkers

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    Objectives: The nature of the diagnostic classification of mood disorder is a typical dichotomous data problem and the method of combining different dimensions of evidences to make judgments might be more statistically reliable. In this paper, we aimed to explore whether peripheral neurotrophic factors could be helpful for early detection of bipolar depression.Methods: A screening method combining peripheral biomarkers and clinical characteristics was applied in 30 patients with major depressive disorder (MDD) and 23 patients with depressive episode of bipolar disorder. By a model-based algorithm, some information was extracted from the dataset and used as a “model” to approach penalized regression model for stably differential diagnosis for bipolar depression.Results: A simple and efficient model of approaching the diagnosis of individuals with depressive symptoms was established with a fitting degree (90.58%) and an acceptable cross-validation error rate. Neurotrophic factors of our interest were successfully screened out from the feature selection and optimized model performance as reliable predictive variables.Conclusion: It seems to be feasible to combine different types of clinical characteristics with biomarkers in order to detect bipolarity of all depressive episodes. Neurotrophic factors of our interest presented its stable discriminant potentiality in unipolar and bipolar depression, deserving validation analysis in larger samples
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