Factors contributing to morning rain in the upper Río Chagres Basin, Panamá

The Upper Chagres River Basin plays an important role in the stable operation of the Panama Canal. Previous studies have shown that there is a salient regional difference in the diurnal variation of precipitation in the basin. Precipitation during the rainy season peaks in the early afternoon throughout the basin, but precipitation is also observed in the morning at sites in the northern part of the basin. However, the cause of this is not clear due to limited ground observation. To address this issue, we conducted dynamical downscaling experiments with a horizontal grid spacing of 5 and 2 km and nested in a global atmospheric model with horizontal grid spacing of approximately 20 km. The results showed that the 2 km convection-permitting model successfully reproduced regional differences in observed diurnal variations. The downscaled results indicated that intensified low-level northeasterly winds over the southern Caribbean Sea triggered favorable conditions for morning rain with an orographic effect under the seaside coastal regime in the western Caribbean Sea. This is in contrast to precipitation peaks in the early afternoon under a landside coastal regime

Fabrication and Characteristics of Chitosan Sponge as a Tissue Engineering Scaffold

Cells, growth factors, and scaffolds are the three main factors required to create a tissue-engineered construct. After the appearance of bovine spongiform encephalopathy (BSE), considerable attention has therefore been focused on nonbovine materials. In this study, we examined the properties of a chitosan porous scaffold. A porous chitosan sponge was prepared by the controlled freezing and lyophilization of different concentrations of chitosan solutions. The materials were examined by scanning electron microscopy, and the porosity, tensile strength, and basic fibroblast growth factor (bFGF) release profiles from chitosan sponge were examined in vitro. The morphology of the chitosan scaffolds presented a typical microporous structure, with the pore size ranging from 50 to 200 m. The porosity of chitosan scaffolds with different concentrations was approximately 75-85%. A decreasing tendency for porosity was observed as the concentration of the chitosan increased. The relationship between the tensile properties and chitosan concentration indicated that the ultimate tensile strength for the sponge increased with a higher concentration. The in vitro bFGF release study showed that the higher the concentration of chitosan solution became, the longer the releasing time of the bFGF from the chitosan sponge was

Exploring super-resolution spatial downscaling of several meteorological variables and potential applications for photovoltaic power

We applied a perfect prognosis approach to downscale four meteorological variables that affect photovoltaic (PV) power output using four machine learning (ML) algorithms. In addition to commonly investigated variables, such as air temperature and precipitation, we also focused on wind speed and surface solar radiation, which are not frequently examined. The downscaling performance of the four variables followed the order of: temperature &gt; surface solar radiation &gt; wind speed &gt; precipitation. Having assessed the dependence of the downscaling accuracy on the scaling factor, we focused on a super-resolution downscaling. We found that the convolutional neural network (CNN) generally outperformed the other linear and non-linear algorithms. The CNN was further able to reproduce extremes. With the rapid transition from coal to renewables, the need to evaluate low solar output conditions at a regional scale is expected to benefit from CNNs. Because weather affects PV power output in multiple ways, and future climate change will modify meteorological conditions, we focused on obtaining exemplary super-resolution application by evaluating future changes in PV power outputs using climate simulations. Our results confirmed the reliability of the CNN method for producing super-resolution climate scenarios and will enable energy planners to anticipate the effects of future weather variability.</p

Exploring super-resolution spatial downscaling of several meteorological variables and potential applications for photovoltaic power

We applied a perfect prognosis approach to downscale four meteorological variables that affect photovoltaic (PV) power output using four machine learning (ML) algorithms. In addition to commonly investigated variables, such as air temperature and precipitation, we also focused on wind speed and surface solar radiation, which are not frequently examined. The downscaling performance of the four variables followed the order of: temperature &gt; surface solar radiation &gt; wind speed &gt; precipitation. Having assessed the dependence of the downscaling accuracy on the scaling factor, we focused on a super-resolution downscaling. We found that the convolutional neural network (CNN) generally outperformed the other linear and non-linear algorithms. The CNN was further able to reproduce extremes. With the rapid transition from coal to renewables, the need to evaluate low solar output conditions at a regional scale is expected to benefit from CNNs. Because weather affects PV power output in multiple ways, and future climate change will modify meteorological conditions, we focused on obtaining exemplary super-resolution application by evaluating future changes in PV power outputs using climate simulations. Our results confirmed the reliability of the CNN method for producing super-resolution climate scenarios and will enable energy planners to anticipate the effects of future weather variability.</p

Panama&rsquo;s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation

Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation

Retinal Detachment-Induced Müller Glial Cell Swelling Activates TRPV4 Ion Channels and Triggers Photoreceptor Death at Body Temperature.

Using region-specific injection of hyaluronic acid, we developed a mouse model of acute retinal detachment (RD) to investigate molecular mechanisms of photoreceptor cell death triggered by RD. We focused on the transient receptor potential vanilloid 4 (TRPV4) ion channel, which functions as a thermosensor, osmosensor, and/or mechanosensor. After RD, the number of apoptotic photoreceptors was reduced by ∼50% in TRPV4KO mice relative to wild-type mice, indicating the possible involvement of TRPV4 activation in RD-induced photoreceptor cell death. Furthermore, TRPV4 expressed in Müller glial cells can be activated by mechanical stimuli caused by RD-induced swelling of these cells, resulting in release of the cytokine MCP-1, which is reported as a mediator of Müller glia-derived strong mediator for RD-induced photoreceptor death. We also found that the TRPV4 activation by the Müller glial swelling was potentiated by body temperature. Together, our results suggest that RD adversely impacts photoreceptor viability via TRPV4-dependent cytokine release from Müller glial cells and that TRPV4 is part of a novel molecular pathway that could exacerbate the effects of hypoxia on photoreceptor survival after RD. Identification of the mechanisms of photoreceptor death in retinal detachment is required for establishment of therapeutic targets for preventing loss of visual acuity. In this study, we found that TRPV4 expressed in Müller glial cells can be activated by mechanical stimuli caused by RD-induced swelling of these cells, resulting in release of the cytokine MCP-1, which is reported as a mediator of Müller glia-derived strong mediator for RD-induced photoreceptor death. We also found that the TRPV4 activation by the Müller glial swelling was potentiated by body temperature. Hence, TRPV4 inhibition could suppress cell death in RD pathological conditions and suggests that TRPV4 in Müller glial cells might be a novel therapeutic target for preventing photoreceptor cell death after RD

Choroidal congestion mouse model: Could it serve as a pachychoroid model?

Pachychoroid spectrum diseases have been described as a new clinical entity within the spectrum of macular disorders. "Pachychoroid" is defined as choroidal thickening associated with dilated outer choroidal vessels often showing retinal pigment epithelium (RPE) degeneration. Although various clinical studies on the pachychoroid spectrum diseases have been conducted, the pathophysiology of pachychoroid has yet to be fully elucidated. In this study, we attempted to establish a mouse model of pachychoroid. We sutured vortex veins in eyes of wild type mice to imitate the vortex vein congestion in pachychoroid spectrum diseases. Fundus photography and ultra-widefield indocyanine green angiography showed dilated vortex veins from the posterior pole to the ampulla in eyes after induction of choroidal congestion. Optical coherence tomography and tissue sections presented choroidal thickening with dilatation of choroidal vessels. The RPE-choroid/retina thickness ratios on the tissue sections in the treated day 1 and day 7 groups were significantly greater than that in the control group (0.19±0.03 and 0.16±0.01 vs. 0.12±0.02, P<0.05 each). Moreover, immunohistochemistry using RPE flatmount revealed focal RPE degeneration in the treated eyes. Furthermore, inflammatory response-related genes were upregulated in eyes with choroidal congestion induction, and macrophages migrated into the thickened choroid. These results indicated that vortex vein congestion triggered some pachychoroid features. Thus, we have established a choroidal congestion mouse model by suturing vortex veins, which would potentially be useful for investigating the pathophysiology of pachychoroid spectrum diseases

Synchrotron radiation microbeam X-ray fluorescence analysis of zinc concentration in remineralized enamel in situ.

OBJECTIVE: Remineralization is an indispensable phenomenon during the natural healing process of enamel decay. The incorporation of zinc (Zn) into enamel crystal could accelerate this remineralization. The present study was designed to investigate the concentration and distribution of Zn in remineralized enamel after gum chewing. METHODS: The experiment was performed at the Photon Factory. Synchrotron radiation was monochromatized and X-rays were focused into a small beam spot. The X-ray fluorescence (XRF) from the sample was detected with a silicon (Si) (lithium (Li)) detector. X-ray beam energy was tuned to detect Zn. The examined samples were small enamel fragments remineralized after chewing calcium phosphate-containing gum in situ. The incorporation of Zn atom into hydroxyapatite (OHAP), the main component of enamel, was measured using Zn K-edge extended X-ray absorption fine structure (EXAFS) with fluorescence mode at the SPring-8. RESULTS: A high concentration of Zn was detected in a superficial area 10-mum deep of the sectioned enamel after gum chewing. This concentration increased over that in the intact enamel. The atomic distance between Zn and O in the enamel was calculated using the EXAFS data. The analyzed atomic distances between Zn and O in two sections were 0.237 and 0.240nm. CONCLUSION: The present experiments suggest that Zn is effectively incorporated into remineralized enamel through the physiological processes of mineral deposition in the oral cavity through gum-chewing and that Zn substitution probably occurred at the calcium position in enamel hydroxyapatite