Nuclear magnetic resonance imaging of the vitreous body

Imaging with proton nuclear magnetic resonance is a valuable new tool for studying the vitreous body of the eye. It is particularly suited for the detection of vitreal liquefaction and intraocular hemorrhage because of the dependence of the signal on the physical environment of water. Conversely, the vitreous body provides a new model for studying changes in proton relaxation times of protein solutions in biological systems.     

Respiratory function and pulmonary lesions in pigs infected with porcine reproductive and respiratory syndrome virus

Pulmonary dysfunction was evaluated in pigs infected with porcine reproductive and respiratory syndrome virus (PRRSV, isolate VR-2332) and compared to clinical and pathological findings. Infected pigs developed fever, reduced appetite, respiratory distress and dullness at 9 days post-inoculation (dpi). Non-invasive pulmonary function tests using impulse oscillometry and rebreathing of test gases (He, CO) revealed peripheral airway obstruction, reduced lung compliance and reduced lung CO-transfer factor. PRRSV-induced pulmonary dysfunction was most marked at 9–18 dpi and was accompanied by a significantly increased respiratory rate and decreased tidal volume. Expiration was affected more than inspiration. On histopathological examination, multifocal areas of interstitial pneumonia (more severe and extensive at 10 dpi than 21 dpi) were identified as a possible structural basis for reduced lung compliance and gas exchange disturbances.     

Prevalence of Giardia in the feces of pups

Fecal specimens were collected from 117 healthy pups (79 privately owned pups and 38 pups from an animal shelter) and analyzed for Giardia. Giardia cysts or trophozoites were found in 35.9% of the dog feces.     

Nitrogen retention and plant uptake on a highly weathered central Amazonian Ferralsol amended with compost and charcoal

Leaching losses of N are a major limitation of crop production on permeable soils and under heavy rainfalls as in the humid tropics. We established a field trial in the central Amazon (near Manaus, Brazil) in order to study the influence of charcoal and compost on the retention of N. Fifteen months after organic‐matter admixing (0–0.1 m soil depth), we added ¹⁵N‐labeled (NH₄)₂SO₄ (27.5 kg N ha^–1 at 10 atom% excess). The tracer was measured in top soil (0–0.1 m) and plant samples taken at two successive sorghum (Sorghum bicolor L. Moench) harvests. The N recovery in biomass was significantly higher when the soil contained compost (14.7% of applied N) in comparison to only mineral‐fertilized plots (5.7%) due to significantly higher crop production during the first growth period. After the second harvest, the retention in soil was significantly higher in the charcoal‐amended plots (15.6%) in comparison to only mineral‐fertilized plots (9.7%) due to higher retention in soil. The total N recovery in soil, crop residues, and grains was significantly (p < 0.05) higher on compost (16.5%), charcoal (18.1%), and charcoal‐plus‐compost treatments (17.4%) in comparison to only mineral‐fertilized plots (10.9%). Organic amendments increased the retention of applied fertilizer N. One process in this retention was found to be the recycling of N taken up by the crop. The relevance of immobilization, reduced N leaching, and gaseous losses as well as other potential processes for increasing N retention should be unraveled in future studies.     

Unitary control in quantum ensembles: maximizing signal intensity in coherent spectroscopy

Experiments in coherent magnetic resonance, microwave, and optical spectroscopy control quantum-mechanical ensembles by guiding them from initial states toward target states by unitary transformation. Often, the coherences detected as signals are represented by a non-Hermitian operator. Hence, spectroscopic experiments, such as those used in nuclear magnetic resonance, correspond to unitary transformations between operators that in general are not Hermitian. A gradient-based systematic procedure for optimizing these transformations is described that finds the largest projection of a transformed initial operator onto the target operator and, thus, the maximum spectroscopic signal. This method can also be used in applied mathematics and control theory.     

A nonlinear,low data requirement model for producing spatially explicit fishery forecasts

Spatial variability can confound accurate estimates of catch per unit effort (CPUE), especially in highly migratory species. The incorporation of spatial structure into fishery stock assessment models should ultimately improve forecasts of stock biomass. Here, we describe a nonlinear time series model for producing spatially explicit forecasts of CPUE that does not require ancillary environmental or demographic data, or specification of a model functional form. We demonstrate this method using spatially resolved (1° × 1° cells) CPUE time series of North Pacific albacore in the California Current System. The spatial model is highly significant (P < 0.00001) and outperforms two spatial null models. We then create a spatial forecast map for years beyond the range of data. Such approaches can guide spatial management of resources and provide a complement to more data‐intensive, highly parameterized population dynamics and ecosystem models currently in use.     

牛奶加工中的链接过程与灌装技术

产品配套可应用于各种饮料,也适用于涉及的相关行业。传统市场产品相互配套已有一段时间,例如乳品企业不仅生产和灌装牛奶混合饮料、酸奶饮料以及添加果料和香精的乳清饮料,同     

Uncertainty in the spatial prediction of soil texture: Comparison of regression tree and Random Forest models

Within the southern Ecuadorian Andes, landslides have an impact on landscape development. Landslide risk estimation as well as hydrological modelling requires physical soil data. Statistical models were adapted to predict the spatial distribution of soil texture from terrain parameters. For this purpose, 56 soil profiles were analysed horizon-wise by pipette and laser method. Results by pipette compared to laser method showed the expected shift to higher silt and lower clay contents. Linear regression equations were adapted. The performance of regression tree (RT) and Random Forest (RF) models was compared by hundredfold model runs on random Jackknife partitions. Digital soil maps of sand, silt and clay percentage mean and standard deviation indicate model variability and prediction uncertainty.RF models performed better than RT models. All terrain factors considered in the analysis influenced soil texture of the surface horizon, but altitude a.s.l. was assigned the highest variable importance during model construction. Shallow subsurface flow is considered responsible for increasing sand/clay ratios with increasing altitude, on steep slopes and with overland flow distance to the channel network by removing clay particles downslope. Deeper soil layers are not influenced by this process and therefore, did not show the same texture properties. However, the influence of parent material and landslides on the spatial distribution of soil texture cannot be neglected. Model performance, most probably, could be improved by a bigger dataset.