Spatial and seasonal variation in leaf temperature within the canopy of a tropical forest

Understanding leaf temperature (Tleaf) variation in the canopy of tropical forests is critical for accurately calculating net primary productivity because plant respiration and net photosynthesis are highly sensitive to temperature. The objectives of this study were to (1) quantify the spatiotemporal variation of Tleaf in a semi-deciduous tropical forest in Panama and (2) create a season-specific empirical model to predict Tleaf in the canopy. To achieve this, we used a 42 m tall construction crane for canopy access and monitored the microenvironment within the canopy of mature, 20-35 m tall trees of 5 tropical tree species during the wet and the dry season. Tleaf was correlated to photosynthetic photon flux density (PPFD) in the wet season but not in the dry season, possibly due to seasonal differences in wind speed, physiology, and canopy phenology. A structural equation model showed that Tleaf is best explained by air temperature (Tair) and PPFD in the wet season, whereas in the dry season, Tair alone predicted most of the variation in Tleaf. These results suggest the utility of an empirical approach to estimate Tleaf variability where simple meteoro logical data are available. This approach can be incorporated in future models of vegetation-atmosphere carbon and water exchange models of mature tropical forests with similar seasonality. © Inter-Research 2016

The lock-in phase in the urotropine-sebacic acid system

The 1,10-decanedioic acid-1,3,5,7-tetraazatricyclo[3.3.1.1(3,7)]decane (1/1) system, C10H18O4.C6H12N4, was studied at 215 (2) K. Its analysis provides important information with regard to the long-standing acid-carboxylate controversy in the urotropine-alkanedioic acid system. In the present structure, all the chain end-groups display a clear acid character. The asymmetric unit of this commensurate modulated phase contains two molecules of diacid as well as two molecules of urotropine. Furthermore, the chain packing suggests a possible order parameter for the lock-in transition

The forensiX evidence collection tube and its impact on DNA preservation and recovery

Biological samples are vulnerable to degradation from the time they are collected until they are analysed at the laboratory. Biological contaminants, such as bacteria, fungi, and enzymes, as well as environmental factors, such as sunlight, heat, and humidity, can increase the rate of DNA degradation. Currently, DNA samples are normally dried or frozen to limit their degradation prior to their arrival at the laboratory. In this study, the effect of the sample drying rate on DNA preservation was investigated, as well as a comparison between drying and freezing methods. The drying performances of two commercially available DNA collection tools (swab and drying tube) with different drying rates were evaluated. The swabs were used to collect human saliva, placed into the drying tubes, and stored in a controlled environment at 25°C and 60% relative humidity, or frozen at −20°C, for 2 weeks. Swabs that were stored in fast sample drying tubes yielded 95% recoverable DNA, whereas swabs stored in tubes with slower sample drying rates yielded only 12% recoverable DNA; saliva stored in a microtube at −20°C was used as a control. Thus, DNA sampling tools that offer rapid drying can significantly improve the preservation of DNA collected on a swab, increasing the quantity of DNA available for subsequent analysis

Validation and Optimization of Barrow Neurological Institute Score in Prediction of Adverse Events and Functional Outcome After Subarachnoid Hemorrhage-Creation of the HATCH (Hemorrhage, Age, Treatment, Clinical State, Hydrocephalus) Score.

BACKGROUND: The Barrow Neurological Institute (BNI) score, measuring maximal thickness of aneurysmal subarachnoid hemorrhage (aSAH), has previously shown to predict symptomatic cerebral vasospasms (CVSs), delayed cerebral ischemia (DCI), and functional outcome. OBJECTIVE: To validate the BNI score for prediction of above-mentioned variables and cerebral infarct and evaluate its improvement by integrating further variables which are available within the first 24 h after hemorrhage. METHODS: We included patients from a single center. The BNI score for prediction of CVS, DCI, infarct, and functional outcome was validated in our cohort using measurements of calibration and discrimination (area under the curve [AUC]). We improved it by adding additional variables, creating a novel risk score (measure by the dichotomized Glasgow Outcome Scale) and validated it in a small independent cohort. RESULTS: Of 646 patients, 41.5% developed symptomatic CVS, 22.9% DCI, 23.5% cerebral infarct, and 29% had an unfavorable outcome. The BNI score was associated with all outcome measurements. We improved functional outcome prediction accuracy by including age, BNI score, World Federation of Neurologic Surgeons, rebleeding, clipping, and hydrocephalus (AUC 0.84, 95% CI 0.8-0.87). Based on this model we created a risk score (HATCH-Hemorrhage, Age, Treatment, Clinical State, Hydrocephalus), ranging 0 to 13 points. We validated it in a small independent cohort. The validated score demonstrated very good discriminative ability (AUC 0.84 [95% CI 0.72-0.96]). CONCLUSION: We developed the HATCH score, which is a moderate predictor of DCI, but excellent predictor of functional outcome at 1 yr after aSAH

Spatio-temporal Gaussian process models for extended and group object tracking with irregular shapes

Extended object tracking has become an integral part of many autonomous systems during the last two decades. For the first time, this paper presents a generic spatio-temporal Gaussian process (STGP) for tracking an irregular and non-rigid extended object. The complex shape is represented by key points and their parameters are estimated both in space and time. This is achieved by a factorization of the power spectral density function of the STGP covariance function. A new form of the temporal covariance kernel is derived with the theoretical expression of the filter likelihood function. Solutions to both the filtering and the smoothing problems are presented. A thorough evaluation of the performance in a simulated environment shows that the proposed STGP approach outperforms the state-of-the-art approach, with up to 90% improvement in the accuracy in position, 95% in velocity and 7% in the shape, while tracking a simulated asymmetric non-rigid object. The tracking performance improvement for a non-rigid irregular real object is up to 43% in position, 68% in velocity, 10% in the recall and 115% in the precision measures