Experimental Quantum Randomness Processing

Coherently manipulating multipartite quantum correlations leads to remarkable advantages in quantum information processing. A fundamental question is whether such quantum advantages persist only by exploiting multipartite correlations, such as entanglement. Recently, Dale, Jennings, and Rudolph negated the question by showing that a randomness processing, quantum Bernoulli factory, using quantum coherence, is strictly more powerful than the one with classical mechanics. In this Letter, focusing on the same scenario, we propose a theoretical protocol that is classically impossible but can be implemented solely using quantum coherence without entanglement. We demonstrate the protocol by exploiting the high-fidelity quantum state preparation and measurement with a superconducting qubit in the circuit quantum electrodynamics architecture and a nearly quantum-limited parametric amplifier. Our experiment shows the advantage of using quantum coherence of a single qubit for information processing even when multipartite correlation is not present.Comment: 9 pages, 7 figure

Research on household emergency supplies storage from the theory of planned behavior and intention-behavior gap in the context of COVID-19

IntroductionIn the context of COVID-19 epidemic, household-level emergency supplies are becoming a critical link in the national emergency response mechanism for public health emergencies. The main goal of this study is to analyze the forming process of household emergency supplies storage intention and behavior based on the theory of planned behavior.MethodsA total of 486 valid questionnaires were obtained from China and analyzed using structural equation modeling.ResultsThe study found that subjective norms and perceived behavioral control had a positive impact on residents’ intention to store emergency supplies, while attitudes did not play a significant role. Community institutional trust and community network play significant moderating roles in the transformation from intentions to behaviors.DiscussionThis study explored the influencing factors of residents’ household emergency supplies storage, and introduced community institutional trust and community network as moderating variables to analyze the process of transformation of residents’ household emergency supplies storage intentions to behaviors from the perspective of community situation, and initially constructed a two-stage integration model including intention formation and behavior transformation. By analyzing the forming process of household emergency supplies behavior, this paper revealed the effective paths for the formation of household emergency supplies storage intention, and put forward policy suggestions from the government and community levels

Overall Survival Time Prediction for High-grade Glioma Patients based on Large-scale Brain Functional Networks

High-grade glioma (HGG) is a lethal cancer with poor outcome. Accurate preoperative overall survival (OS) time prediction for HGG patients is crucial for treatment planning. Traditional presurgical and noninvasive OS prediction studies have used radiomics features at the local lesion area based on the magnetic resonance images (MRI). However, the highly complex lesion MRI appearance may have large individual variability, which could impede accurate individualized OS prediction. In this paper, we propose a novel concept, namely brain connectomics-based OS prediction. It is based on presurgical resting-state functional MRI (rs-fMRI) and the non-local, large-scale brain functional networks where the global and systemic prognostic features rather than the local lesion appearance are used to predict OS. We propose that the connectomics features could capture tumor-induced network-level alterations that are associated with prognosis. We construct both low-order (by means of sparse representation with regional rs-fMRI signals) and high-order functional connectivity (FC) networks (characterizing more complex multi-regional relationship by synchronized dynamics FC time courses). Then, we conduct a graph-theoretic analysis on both networks for a jointly, machine-learning-based individualized OS prediction. Based on a preliminary dataset (N = 34 with bad OS, mean OS, ~400 days; N = 34 with good OS, mean OS, ~1030 days), we achieve a promising OS prediction accuracy (86.8%) on separating the individuals with bad OS from those with good OS. However, if using only conventionally derived descriptive features (e.g., age and tumor characteristics), the accuracy is low (63.2%). Our study highlights the importance of the rs-fMRI and brain functional connectomics for treatment planning

Efficient depolymerization of lignin through microwave-assisted Ru/C catalyst cooperated with metal chloride in methanol/formic acid media

Lignin, an abundant aromatic biopolymer, has the potential to produce various biofuels and chemicals through biorefinery activities and is expected to benefit the future circular economy. Microwave-assisted efficient degradation of lignin in methanol/formic acid over Ru/C catalyst cooperated with metal chloride was investigated, concerning the effect of type and dosage of metal chloride, dosage of Ru/C, reaction temperature, and reaction time on depolymerized product yield and distribution. Results showed that 91.1 wt% yield of bio-oil including 13.4 wt% monomers was obtained under the optimum condition. Yields of guaiacol-type compounds and 2,3-dihydrobenzofuran were promoted in the presence of ZnCl2. Formic acid played two roles: (1) acid-catalyzed cleavage of linkages; (2) acted as an in situ hydrogen donor for hydrodeoxygenation in the presence of Ru/C. A possible mechanism for lignin degradation was proposed. This work will provide a beneficial approach for efficient depolymerization of lignin and controllable product distribution

Clinical and genomic characterization of carbapenem-resistant Enterobacterales bloodstream infections in patients with hematologic malignancies

BackgroundCarbapenem-resistant Enterobacterales (CRE) bloodstream infections (BSIs) pose a significant risk to patients with hematologic malignancies, yet the distinct features and outcomes of these infections are not thoroughly understood.MethodsThis retrospective study examined the characteristics and clinical outcomes of patients with Enterobacterales BSIs at the Hematology Department of Fujian Medical University Union Hospital from 2018 to 2022. Whole-genome sequencing was conducted on 45 consecutive CRE BSI isolates during this period.ResultsA total of 301 patients with Enterobacterales BSIs were included, with 65 (21.6%) cases of CRE and 236 (78.4%) cases of carbapenem-susceptible Enterobacterales (CSE). CRE infections accounted for 16.9% to 26.9% of all Enterobacterales BSIs, and carbapenem-resistant Klebsiella pneumoniae (CRKP) was the predominant strain. The most frequent sequence type (ST) and carbapenemase among CRKP were ST11 (68.6%) and blaKPC-2 (80.0%), respectively. Perianal infections, multiple infection foci, and a history of multiple hospitalizations, ICU stays, and prior CRE infections were identified as risk factors for CRE BSIs. Patients in the CRE group experienced significantly higher proportions of infection-related septic shock (43.1% vs. 19.9%, P < 0.0003) and 30-day all-cause mortality (56.9% vs. 24.6%, P < 0.0001) compared to those in the CSE group. Patient’s age and disease subtypes, strain subtypes, and antimicrobial treatment regimens significantly influenced survival in patients with CRE BSIs.ConclusionsCRE BSIs are a frequent complication in patients with hematological malignancies undergoing treatment and are associated with poor survival rates. A comprehensive understanding of risk factors and ongoing surveillance of prevalent strains are essential for the effective management of these infections