Investigation of ozone deposition to vegetation under warm and dry conditions near the Eastern Mediterranean coast.

Dry deposition of ozone (O) to vegetation is an important removal pathway for tropospheric O, while O uptake through plant stomata negatively affects vegetation and leads to climate change. Both processes are controlled by vegetation characteristics and ambient conditions via complex mechanisms. Recent studies have revealed that these processes can be fundamentally impacted by coastal effects, and by dry and warm conditions in ways that have not been fully characterized, largely due to lack of measurements under such conditions.

Measurement-based investigation of ozone deposition to vegetation under the effects of coastal and photochemical air pollution in the Eastern Mediterranean.

Dry deposition of ozone (O) to vegetation is an important pathway for its removal from the troposphere, and it can lead to adverse effects in plants and changes in climate. However, our mechanistic understanding of O dry deposition is insufficient to adequately account for it in global and regional models, primarily because this process is highly complicated by feedback mechanisms and sensitivity to specific characteristics of vegetative environment and atmospheric dynamics and composition. We hypothesized that measuring dry deposition of O to vegetation near the Eastern Mediterranean (EM) coast, where large variations in meteorological conditions and photochemical air pollution frequently occur, would enable identifying the mechanisms controlling O deposition to vegetation.

Texture coarseness responsive neurons and their mapping in layer 2-3 of the rat barrel cortex in vivo.

Texture discrimination is a fundamental function of somatosensory systems, yet the manner by which texture is coded and spatially represented in the barrel cortex are largely unknown. Using in vivo two-photon calcium imaging in the rat barrel cortex during artificial whisking against different surface coarseness or controlled passive whisker vibrations simulating different coarseness, we show that layer 2-3 neurons within barrel boundaries differentially respond to specific texture coarsenesses, while only a minority of neurons responded monotonically with increased or decreased surface coarseness. Neurons with similar preferred texture coarseness were spatially clustered.

Prognostic data-driven clinical decision support - formulation and implications.

Existing Clinical Decision Support Systems (CDSSs) typically rely on rule-based algorithms and focus on tasks like guidelines adherence and drug prescribing and monitoring. However, the increasing dominance of Electronic Health Record technologies and personalized medicine suggest great potential for prognostic data-driven CDSS. A major goal for such systems would be to accurately predict the outcome of patients' candidate treatments by statistical analysis of the clinical data stored at a Health Care Organization.