Holograms, the optical devices to reconstruct predesigned images, show many applications in our daily life. However, applications of hologram are still limited by the constituent materials and therefore their working range is trapped at a particular electromagnetic region. In recent years, the metasurfaces, an array of subwavelength antenna with varying sizes, show the abilities to manipulate the phase of incident electromagnetic wave from visible to microwave frequencies. Here, we present a reflective-type and high-efficiency meta-hologram fabricated by metasurface for visible wavelength. Using gold cross nanoantennas as building blocks to construct our meta-hologram devices with thickness ∼ λ/4, the reconstructed images of meta-hologram show polarization-controlled dual images with high contrast, functioning for both coherent and incoherent light sources within a broad spectral range and under a wide range of incidence angles. The flexibility demonstrated here for our meta-hologram paves the road to a wide range of applications related to holographic images at arbitrary electromagnetic wave region.

Fluorochemical-treated paper was tested to determine the amount of migration that occurs into foods and food-simulating liquids and the characteristics of the migration. Migration characteristics of fluorochemicals from paper were examined in Miglyol, butter, water, vinegar, water-ethanol solutions, emulsions and pure oil containing small amounts of emulsifiers. Additionally, microwave popcorn and chocolate spread were used to investigate migration. Results indicate that fluorochemicals paper additives do migrate to food during actual package use. For example, we found that microwave popcorn contained 3.2 fluorochemical mg kg(-1) popcorn after popping and butter contained 0.1 mg kg(-1) after 40 days at 4 degrees C. Tests also indicate that common food-simulating liquids for migration testing and package material evaluation might not provide an accurate indication of the amount of fluorochemical that actually migrates to food. Tests show that oil containing small amounts of an emulsifier can significantly enhance migration of a fluorochemical from paper.

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The boundary effect on the diffusiophoretic behavior of a particle is analyzed theoretically by considering the diffusiophoresis of a charged sphere under arbitrary surface potential and double-layer thickness at an arbitrary position in an uncharged spherical cavity. We show that the phenomenon under consideration is governed by double-layer relaxation, chemiosmotic/diffusioosmotic flow, and two types of competing double-layer polarization. The presence of the cavity has a profound influence on the diffusiophoretic behavior of the particle, especially when the surface potential is high. For instance, the scaled diffusiophoretic velocity of the particle has a local maximum as the position of the particle varies; it may have a local maximum and local minimum as the thickness of the double-layer varies. The significance of the effect of double-layer relaxation depends upon the level of surface potential and magnitude of the electric Peclet number.

Although short-lived vertebrates can serve as model animals for understanding the mechanism of aging, whether the annual fish Nothobranchius rachovii is suitable for studying aging remains an open question. In this study, histochemical, biochemical, and genetic techniques were used to determine the age-related markers at three different developmental stages of the annual fish N. rachovii. Histochemical studies revealed that the expression of senescence-associated beta-galactosidase and accumulation of lipofuscin increased with age. In biochemical assays, lipid peroxidation and protein oxidation increased with age, whereas the activities of catalase, glutathione peroxidase, and superoxide dismutase decreased with age. Genetic analysis established that the activities of telomerase had no apparent relationship with age, but telomere lengths reduced with age from 11.5 +/- 1.98 to 3.58 +/- 0.74 kb. Taken together, these results indicate that the annual fish N. rachovii may be useful as an animal model for the study of aging.

The boundary effect on the diffusiophoresis of a colloidal particle is investigated theoretically by considering a soft spherical particle at an arbitrary position in a spherical cavity. The particle, which comprises a rigid core and an ion-penetrable layer, simulates biocolloids and particles covered by an artificial membrane layer. The diffusiophoretic behavior of the particle is governed by two types of DLP, the electrophoresis arising from the difference in the diffusivities of ionic species and diffusioosmotic flow. The influences of the thickness of the double layer, the size of the cavity, and the nature and the position of the particle on its diffusiophoretic behavior are discussed. We show that the presence of a boundary can have a profound influence on the behavior of a particle. The effect of electrophoresis can also lead to interesting diffusiophoretic behavior.

Background: A predictive model can provide physicians, relatives, and patients the accurate information regarding the severity of disease and its predicted outcome. In this study, we used an automated machine-learning-based approach to construct a prognostic model to predict the functional outcome in patients with primary intracerebral hemorrhage (ICH). Methods: We retrospectively collected data on demographic characteristics, laboratory studies and imaging findings of 333 patients with primary ICH. The functional outcomes at the 1st and 6th months after ICH were defined by the modified Rankin scale. All of the attributes were used for preprocessing and for automatic model selection with Automatic Waikato Environment for Knowledge Analysis. Confusion matrix and areas under the receiver operating characteristic curves (AUC) were used to test the predictive performance. Results: Among the models tested, the random forest provided the best predictive performance for functional outcome. The overall accuracy for predicting the 1st month outcome was 83.1%, with 77.4% sensitivity and 86.9% specificity, and the AUC was 0.899. The overall accuracy for predicting the 6th month outcome was 83.9%, with 72.5% sensitivity and 90.6% specificity, and the AUC was 0.917. Conclusions: Using an automatic machine learning technique to predict functional outcome after ICH is feasible, and the random forest model provides the best predictive performance across all tested models. This prediction model may provide information regarding functional outcome for clinicians that will help provide appropriate medical care for patients and information for their caregivers.

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