The effect of composition modification on the optical polarization independence in semiconductor strain quantum wells

Polarization independent quantum well (QW) materials operating under electro-absorption effect in optical switching and modulation devices are of intense interest recently. This is a theoretical analysis of the optical properties of strained InGaAs/InP QWs. The method of composition modification based on interdiffusion will be introduced to merge the heavy- and light- hole states in order to achieve polarization insensitivity. Results presented here show that the diffused QWs with and without as-growth tensile strain can both serve in polarization independent electro-absorption requirements. With a suitable design in the interdiffused QW materials, the optical polarization independence can operate from 1.465 to 1.540 µrn (tunability of 75*nm) with a maximum absorption change of 2000 cm-1 . In the case studied here, over 75% reduction in the required as-growth tensile strain is achieved as compared with the conventional rectangular QWs. This provides us with a simpler way to achieve high strain optical polarization independence through interdiffusion.published_or_final_versio

A model of dengue fever

BACKGROUND: Dengue is a disease which is now endemic in more than 100 countries of Africa, America, Asia and the Western Pacific. It is transmitted to the man by mosquitoes (Aedes) and exists in two forms: Dengue Fever and Dengue Haemorrhagic Fever. The disease can be contracted by one of the four different viruses. Moreover, immunity is acquired only to the serotype contracted and a contact with a second serotype becomes more dangerous. METHODS: The present paper deals with a succession of two epidemics caused by two different viruses. The dynamics of the disease is studied by a compartmental model involving ordinary differential equations for the human and the mosquito populations. RESULTS: Stability of the equilibrium points is given and a simulation is carried out with different values of the parameters. The epidemic dynamics is discussed and illustration is given by figures for different values of the parameters. CONCLUSION: The proposed model allows for better understanding of the disease dynamics. Environment and vaccination strategies are discussed especially in the case of the succession of two epidemics with two different viruses

On the Relation Between Jupiter's Aurora and the Dawnside Current Sheet

Jupiter's auroral emission is a spectacular phenomenon that provides insight into energy release processes related to the coupling of its magnetosphere and ionosphere. This energy release is influenced by solar wind conditions. Using joint observations from Juno and the Hubble Space Telescope (HST), we statistically investigate the relationship between auroral power and current sheet variations under different solar wind conditions. In this study, we reveal that during global main auroral brightening events that are closely connected to solar wind compressions, the dawn side current sheet is substantially thinner than during times when a quiet auroral morphology is present. Furthermore, the total current intensity in the current sheet is found to increase under solar wind compression conditions compared to the quiet period. These findings provide important observational evidence for how magnetospheric dynamics driven by solar wind behavior affect auroral activity, deepening our understanding of the coupling between Jupiter's magnetosphere and ionosphere

Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation

Design considerations and analysis planning of a phase 2a proof of concept study in rheumatoid arthritis in the presence of possible non-monotonicity

BACKGROUND: It is important to quantify the dose response for a drug in phase 2a clinical trials so the optimal doses can then be selected for subsequent late phase trials. In a phase 2a clinical trial of new lead drug being developed for the treatment of rheumatoid arthritis (RA), a U-shaped dose response curve was observed. In the light of this result further research was undertaken to design an efficient phase 2a proof of concept (PoC) trial for a follow-on compound using the lessons learnt from the lead compound. METHODS: The planned analysis for the Phase 2a trial for GSK123456 was a Bayesian Emax model which assumes the dose-response relationship follows a monotonic sigmoid "S" shaped curve. This model was found to be suboptimal to model the U-shaped dose response observed in the data from this trial and alternatives approaches were needed to be considered for the next compound for which a Normal dynamic linear model (NDLM) is proposed. This paper compares the statistical properties of the Bayesian Emax model and NDLM model and both models are evaluated using simulation in the context of adaptive Phase 2a PoC design under a variety of assumed dose response curves: linear, Emax model, U-shaped model, and flat response. RESULTS: It is shown that the NDLM method is flexible and can handle a wide variety of dose-responses, including monotonic and non-monotonic relationships. In comparison to the NDLM model the Emax model excelled with higher probability of selecting ED90 and smaller average sample size, when the true dose response followed Emax like curve. In addition, the type I error, probability of incorrectly concluding a drug may work when it does not, is inflated with the Bayesian NDLM model in all scenarios which would represent a development risk to pharmaceutical company. The bias, which is the difference between the estimated effect from the Emax and NDLM models and the simulated value, is comparable if the true dose response follows a placebo like curve, an Emax like curve, or log linear shape curve under fixed dose allocation, no adaptive allocation, half adaptive and adaptive scenarios. The bias though is significantly increased for the Emax model if the true dose response follows a U-shaped curve. CONCLUSIONS: In most cases the Bayesian Emax model works effectively and efficiently, with low bias and good probability of success in case of monotonic dose response. However, if there is a belief that the dose response could be non-monotonic then the NDLM is the superior model to assess the dose response

Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

Antibody to P. falciparum in Pregnancy Varies with Intermittent Preventive Treatment Regime and Bed Net Use

Antibodies towards placental-binding P. falciparum are thought to protect against pregnancy malaria; however, environmental factors may affect antibody development.Using plasma from pregnant Malawian women, we measured IgG against placental-binding P. falciparum parasites by flow cytometry, and related results to intermittent preventive treatment (IPTp) regime, and bed net use. Bed net use was associated with decreased antibody levels at mid-pregnancy but not at 1 month post partum (1 mpp). At 1 mpp a more intensive IPTp regime was associated with decreased antibody levels in primigravidae, but not multigravidae.Results suggest bed nets and IPTp regime influence acquisition of pregnancy-specific P. falciparum immunity

Parkinson-related parkin reduces α-Synuclein phosphorylation in a gene transfer model

α-Synuclein aggregates in Lewy bodies and plays a central role in the pathogenesis of a group of neurodegenerative disorders, known as "Synucleinopathies", including Parkinson's disease. Parkin mutations result in loss of parkin E3-ubiquitin ligase activity and cause autosomal recessive early onset parkinsonism