Preferential Paths of Air-water Two-phase Flow in Porous Structures with Special Consideration of Channel Thickness Effects.

Accurate understanding and predicting the flow paths of immiscible two-phase flow in rocky porous structures are of critical importance for the evaluation of oil or gas recovery and prediction of rock slides caused by gas-liquid flow. A 2D phase field model was established for compressible air-water two-phase flow in heterogenous porous structures. The dynamic characteristics of air-water two-phase interface and preferential paths in porous structures were simulated. The factors affecting the path selection of two-phase flow in porous structures were analyzed. Transparent physical models of complex porous structures were prepared using 3D printing technology. Tracer dye was used to visually observe the flow characteristics and path selection in air-water two-phase displacement experiments. The experimental observations agree with the numerical results used to validate the accuracy of phase field model. The effects of channel thickness on the air-water two-phase flow behavior and paths in porous structures were also analyzed. The results indicate that thick channels can induce secondary air flow paths due to the increase in flow resistance; consequently, the flow distribution is different from that in narrow channels. This study provides a new reference for quantitatively analyzing multi-phase flow and predicting the preferential paths of immiscible fluids in porous structures

Experimental measurement-based quantum computing beyond the cluster-state model

The paradigm of measurement-based quantum computation opens new experimental avenues to realize a quantum computer and deepens our understanding of quantum physics. Measurement-based quantum computation starts from a highly entangled universal resource state. For years, clusters states have been the only known universal resources. Surprisingly, a novel framework namely quantum computation in correlation space has opened new routes to implement measurement-based quantum computation based on quantum states possessing entanglement properties different from cluster states. Here we report an experimental demonstration of every building block of such a model. With a four-qubit and a six-qubit state as distinct from cluster states, we have realized a universal set of single-qubit rotations, two-qubit entangling gates and further Deutsch's algorithm. Besides being of fundamental interest, our experiment proves in-principle the feasibility of universal measurement-based quantum computation without using cluster states, which represents a new approach towards the realization of a quantum computer.Comment: 26 pages, final version, comments welcom

Estimation of colorectal adenoma recurrence with dependent censoring

<p>Abstract</p> <p>Background</p> <p>Due to early colonoscopy for some participants, interval-censored observations can be introduced into the data of a colorectal polyp prevention trial. The censoring could be dependent of risk of recurrence if the reasons of having early colonoscopy are associated with recurrence. This can complicate estimation of the recurrence rate.</p> <p>Methods</p> <p>We propose to use midpoint imputation to convert interval-censored data problems to right censored data problems. To adjust for potential dependent censoring, we use information from auxiliary variables to define risk groups to perform the weighted Kaplan-Meier estimation to the midpoint imputed data. The risk groups are defined using two risk scores derived from two working proportional hazards models with the auxiliary variables as the covariates. One is for the recurrence time and the other is for the censoring time. The method described here is explored by simulation and illustrated with an example from a colorectal polyp prevention trial.</p> <p>Results</p> <p>We first show that midpoint imputation under an assumption of independent censoring will produce an unbiased estimate of recurrence rate at the end of the trial, which is often the main interest of a colorectal polyp prevention trial, and then show in simulations that the weighted Kaplan-Meier method using the information from auxiliary variables based on the midpoint imputed data can improve efficiency in a situation with independent censoring and reduce bias in a situation with dependent censoring compared to the conventional methods, while estimating the recurrence rate at the end of the trial.</p> <p>Conclusion</p> <p>The research in this paper uses midpoint imputation to handle interval-censored observations and then uses the information from auxiliary variables to adjust for dependent censoring by incorporating them into the weighted Kaplan-Meier estimation. This approach can handle a situation with multiple auxiliary variables by deriving two risk scores from two working PH models. Although the idea of this approach might appear simple, the results do show that the weighted Kaplan-Meier approach can gain efficiency and reduce bias due to dependent censoring.</p

Magnetoresistance in Sn-Doped In2O3Nanowires

In this work, we present transport measurements of individual Sn-doped In2O3nanowires as a function of temperature and magnetic field. The results showed a localized character of the resistivity at low temperatures as evidenced by the presence of a negative temperature coefficient resistance in temperatures lower than 77 K. The weak localization was pointed as the mechanism responsible by the negative temperature coefficient of the resistance at low temperatures

One-step fabrication of biocompatible chitosan-coated ZnS and ZnS:Mn2+ quantum dots via a γ-radiation route

Biocompatible chitosan-coated ZnS quantum dots [CS-ZnS QDs] and chitosan-coated ZnS:Mn2+ quantum dots [CS-ZnS:Mn2+ QDs] were successfully fabricated via a convenient one-step γ-radiation route. The as-obtained QDs were around 5 nm in diameter with excellent water-solubility. These QDs emitting strong visible blue or orange light under UV excitation were successfully used as labels for PANC-1 cells. The cell experiments revealed that CS-ZnS and CS-ZnS:Mn2+ QDs showed low cytotoxicity and good biocompatibility, which offered possibilities for further biomedical applications. Moreover, this convenient synthesis strategy could be extended to fabricate other nanoparticles coated with chitosan

An Anaerobic-Type α-Ketoglutarate Ferredoxin Oxidoreductase Completes the Oxidative Tricarboxylic Acid Cycle of Mycobacterium tuberculosis

Aerobic organisms have a tricarboxylic acid (TCA) cycle that is functionally distinct from those found in anaerobic organisms. Previous reports indicate that the aerobic pathogen Mycobacterium tuberculosis lacks detectable α-ketoglutarate (KG) dehydrogenase activity and drives a variant TCA cycle in which succinyl-CoA is replaced by succinic semialdehyde. Here, we show that M. tuberculosis expresses a CoA-dependent KG dehydrogenase activity, albeit one that is typically found in anaerobic bacteria. Unlike most enzymes of this family, the M. tuberculosis KG: ferredoxin oxidoreductase (KOR) is extremely stable under aerobic conditions. This activity is absent in a mutant strain deleted for genes encoding a previously uncharacterized oxidoreductase, and this strain is impaired for aerobic growth in the absence of sufficient amounts of CO2. Interestingly, inhibition of the glyoxylate shunt or exclusion of exogenous fatty acids alleviates this growth defect, indicating the presence of an alternate pathway that operates in the absence of β-oxidation. Simultaneous disruption of KOR and the first enzyme of the succinic semialdehyde pathway (KG decarboxylase; KGD) results in strict dependence upon the glyoxylate shunt for growth, demonstrating that KG decarboxylase is also functional in M. tuberculosis intermediary metabolism. These observations demonstrate that unlike most organisms M. tuberculosis utilizes two distinct TCA pathways from KG, one that functions concurrently with β-oxidation (KOR-dependent), and one that functions in the absence of β-oxidation (KGD-dependent). As these pathways are regulated by metabolic cues, we predict that their differential utilization provides an advantage for growth in different environments within the host

SV-IV Peptide1–16 reduces coagulant power in normal Factor V and Factor V Leiden

Native Factor V is an anticoagulant, but when activated by thrombin, Factor X or platelet proteases, it becomes a procoagulant. Due to these double properties, Factor V plays a crucial role in the regulation of coagulation/anticoagulation balance

A predictive model relating daily fluctuations in summer temperatures and mortality rates

<p>Abstract</p> <p>Background</p> <p>In the context of climate change, an efficient alert system to prevent the risk associated with summer heat is necessary. The authors' objective was to describe the temperature-mortality relationship in France over a 29-year period and to define and validate a combination of temperature factors enabling optimum prediction of the daily fluctuations in summer mortality.</p> <p>Methods</p> <p>The study addressed the daily mortality rates of subjects aged over 55 years, in France as a whole, from 1975 to 2003. The daily minimum and maximum temperatures consisted in the average values recorded by 97 meteorological stations. For each day, a cumulative variable for the maximum temperature over the preceding 10 days was defined.</p> <p>The mortality rate was modelled using a Poisson regression with over-dispersion and a first-order autoregressive structure and with control for long-term and within-summer seasonal trends. The lag effects of temperature were accounted for by including the preceding 5 days. A "backward" method was used to select the most significant climatic variables. The predictive performance of the model was assessed by comparing the observed and predicted daily mortality rates on a validation period (summer 2003), which was distinct from the calibration period (1975–2002) used to estimate the model.</p> <p>Results</p> <p>The temperature indicators explained 76% of the total over-dispersion. The greater part of the daily fluctuations in mortality was explained by the interaction between minimum and maximum temperatures, for a day <it>t </it>and the day preceding it. The prediction of mortality during extreme events was greatly improved by including the cumulative variables for maximum temperature, in interaction with the maximum temperatures. The correlation between the observed and estimated mortality ratios was 0.88 in the final model.</p> <p>Conclusion</p> <p>Although France is a large country with geographic heterogeneity in both mortality and temperatures, a strong correlation between the daily fluctuations in mortality and the temperatures in summer on a national scale was observed. The model provided a satisfactory quantitative prediction of the daily mortality both for the days with usual temperatures and for the days during intense heat episodes. The results may contribute to enhancing the alert system for intense heat waves.</p