Nonlocality activation in a photonic quantum network

Bell nonlocality refers to correlations between two distant, entangled particles that challenge classical notions of local causality. Beyond its foundational significance, nonlocality is crucial for device-independent technologies like quantum key distribution and randomness generation. Nonlocality quickly deteriorates in the presence of noise, and restoring nonlocal correlations requires additional resources. These often come in the form of many instances of the input state and joint measurements, incurring a significant resource overhead. Here, we experimentally demonstrate that single copies of Bell-local states, incapable of violating any standard Bell inequality, can give rise to nonlocality after being embedded into a quantum network of multiple parties. We subject the initial entangled state to a quantum channel that broadcasts part of the state to two independent receivers and certify the nonlocality in the resulting network by violating a tailored Bell-like inequality. We obtain these results without making any assumptions about the prepared states, the quantum channel, or the validity of quantum theory. Our findings have fundamental implications for nonlocality and enable the practical use of nonlocal correlations in real-world applications, even in scenarios dominated by noise.Comment: Main text and Supplementary Information. Comments welcom

Sub-megahertz homogeneous linewidth for Er in Si via in situ single photon detection

We studied the optical properties of a resonantly excited trivalent Er ensemble in Si accessed via in situ single photon detection. A novel approach which avoids nanofabrication on the sample is introduced, resulting in a highly efficient detection of 70 excitation frequencies, of which 63 resonances have not been observed in literature. The center frequencies and optical lifetimes of all resonances have been extracted, showing that 5% of the resonances are within 1 GHz of our electrically detected resonances and that the optical lifetimes range from 0.5 ms up to 1.5 ms. We observed inhomogeneous broadening of less than 400 MHz and an upper bound on the homogeneous linewidth of 1.4 MHz and 0.75 MHz for two separate resonances, which is a reduction of more than an order of magnitude observed to date. These narrow optical transition properties show that Er in Si is an excellent candidate for future quantum information and communication applications.Comment: 12 pages, 13 figure

Millisecond electron spin coherence time for erbium ions in silicon

Spins in silicon that are accessible via a telecom-compatible optical transition are a versatile platform for quantum information processing that can leverage the well-established silicon nanofabrication industry. Key to these applications are long coherence times on the optical and spin transitions to provide a robust system for interfacing photonic and spin qubits. Here, we report telecom-compatible Er3+ sites with long optical and electron spin coherence times, measured within a nuclear spin-free silicon crystal (<0.01% 29Si) using optical detection. We investigate two sites and find 0.1 GHz optical inhomogeneous linewidths and homogeneous linewidths below 70 kHz for both sites. We measure the electron spin coherence time of both sites using optically detected magnetic resonance and observe Hahn echo decay constants of 0.8 ms and 1.2 ms at around 11 mT. These optical and spin properties of Er3+:Si are an important milestone towards using optically accessible spins in silicon for a broad range of quantum information processing applications.Comment: 14 pages, 6 figure

Profiles of physical, emotional and psychosocial wellbeing in the Lothian birth cohort 1936

<p>Abstract</p> <p>Background</p> <p>Physical, emotional, and psychosocial wellbeing are important domains of function. The aims of this study were to explore the existence of separable groups among 70-year olds with scores representing physical function, perceived quality of life, and emotional wellbeing, and to characterise any resulting groups using demographic, personality, cognition, health and lifestyle variables.</p> <p>Methods</p> <p>We used latent class analysis (LCA) to identify possible groups.</p> <p>Results</p> <p>Results suggested there were 5 groups. These included High (n = 515, 47.2% of the sample), Average (n = 417, 38.3%), and Poor Wellbeing (n = 37, 3.4%) groups. The two other groups had contrasting patterns of wellbeing: one group scored relatively well on physical function, but low on emotional wellbeing (Good Fitness/ Low Spirits,n = 60, 5.5%), whereas the other group showed low physical function but relatively well emotional wellbeing (Low Fitness/Good Spirits, n = 62, 5.7%). Salient characteristics that distinguished all the groups included smoking and drinking behaviours, personality, and illness.</p> <p>Conclusions</p> <p>Despite there being some evidence of these groups, the results also support a largely one-dimensional construct of wellbeing in old age—for the domains assessed here—though with some evidence that some individuals have uneven profiles.</p

ROBINS-I: a tool for assessing risk of bias in non-randomized studies of interventions

Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I ("Risk Of Bias In Non-randomised Studies-of Interventions"), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies

Patterns and associates of cognitive function, psychosocial wellbeing and health in the Lothian Birth Cohort 1936

BACKGROUND: Cognitive function, psychosocial wellbeing and health are important domains of function. Consistencies and inconsistencies in patterns of wellbeing across these domains may be informative about wellbeing in old age and the ways it is manifested amongst individuals. In this study we investigated whether there were groups of individuals with different profiles of scores across these domains. We also aimed to identify characteristics of any evident groups by comparing them on variables that were not used in identifying the groups. METHODS: The sample was the Lothian Birth Cohort 1936, which included 1091 participants born in 1936. They are a community-dwelling, narrow-age-range sample of 70-year-olds. Most had taken part in the Scottish Mental Survey 1947 at an average age of 11, making available a measure of childhood intelligence. We used latent class analysis (LCA) to explore possible profiles using 9 variables indicating cognitive functioning, psychosocial wellbeing and health status. Demographic, personality, and lifestyle variables – none of which were used in the LCA – were used to characterize the resulting profile groups. RESULTS: We accepted a 3-group solution, which we labeled High Wellbeing (65.3%), Low Cognition (20.3%), and Low Bio-Psychosocial (14.5%). Notably, the High Wellbeing group had significantly higher childhood IQ, lower Neuroticism scores, and a lower percentage of current smokers than the other 2 groups. CONCLUSION: The majority of individuals were functioning generally well; however, there was evidence of the presence of groups with different profiles, which may be explained in part in terms of cognitive ability differences. Results suggested that higher life-long intelligence, personality traits associated with less mental distress, and basic health practices such as avoiding smoking are important associates of wellbeing in old age

World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

BACKGROUND: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. METHODS: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40-80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. FINDINGS: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629-0·741) to 0·833 (0·783-0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40-64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. INTERPRETATION: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. FUNDING: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research

Application of Ligninolytic Enzymes in the Production of Biofuels from Cotton Wastes

The application of ligninolytic fungi and enzymes is an option to overcome the issues related with the production of biofuels using cotton wastes. In this dissertation, the ligninolytic fungus and enzymes were evaluated as pretreatment for the biochemical conversion of Cotton Gin Trash (CGT) in ethanol and as a treatment for the transformation of cotton wastes biochar in other substances. In biochemical conversion, seven combinations of three pretreatments (ultrasonication, liquid hot water and ligninolytic enzymes) were evaluated on CGT. The best results were achieved by the sequential combination of ultrasonication, hot water, and ligninolytic enzymes with an improvement of 10% in ethanol yield. To improve these results, alkaline-ultrasonication was evaluated. Additionally, Fourier Transform Infrared (FT-IR) and principal component analysis (PCA) were employed as fast methodology to identify structural differences in the biomass. The combination of ultrasonication-alkali hydrolysis, hot liquid water, and ligninolytic enzymes using 15% of NaOH improved 35% ethanol yield compared with the original treatment. Additionally, FT-IR and PCA identified modifications in the biomass structure after different types of pretreatments and conditions. In thermal conversion, this study evaluated the biodepolymerization of cotton wastes biochar using chemical and biological treatments. The chemical depolymerization evaluated three chemical agents (KMnO4, H2SO4, and NaOH), with three concentrations and two environmental conditions. The sulfuric acid treatments performed the largest transformations of the biochar solid phase; whereas, the KMnO4 treatments achieved the largest depolymerizations. The compounds released into the liquid phase were correlated with fulvic and humic acids and silicon compounds. The biological depolymerization utilized four ligninolytic fungi Phanerochaete chrysosporium, Ceriporiopsis subvermispora, Postia placenta, and Bjerkandera adusta. The greatest depolymerization was obtained by C. subvermispora. The depolymerization kinetics of C. subvermispora evidenced the production of laccase and manganese peroxidase and a correlation between depolymerization and production of ligninolytic enzymes. The modifications obtained in the liquid and solid phases showed the production of humic and fulvic acids from the cultures with C. subvermispora. The results of this research are the initial steps for the development of new processes using the ligninolytic fungus and their enzymes for the production of biofuels from cotton wastes