810 resultados para vegetation rehabilitation


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Strokes affect thousands of people worldwide leaving sufferers with severe disabilities affecting their daily activities. In recent years, new rehabilitation techniques have emerged such as constraint-induced therapy, biofeedback therapy and robot-aided therapy. In particular, robotic techniques allow precise recording of movements and application of forces to the affected limb, making it a valuable tool for motor rehabilitation. In addition, robot-aided therapy can utilise visual cues conveyed on a computer screen to convert repetitive movement practice into an engaging task such as a game. Visual cues can also be used to control the information sent to the patient about exercise performance and to potentially address psychosomatic variables influencing therapy. This paper overviews the current state-of-the-art on upper limb robot-mediated therapy with a focal point on the technical requirements of robotic therapy devices leading to the development of upper limb rehabilitation techniques that facilitate reach-to-touch, fine motor control, whole-arm movements and promote rehabilitation beyond hospital stay. The reviewed literature suggest that while there is evidence supporting the use of this technology to reduce functional impairment, besides the technological push, the challenge ahead lies on provision of effective assessment of outcome and modalities that have a stronger impact transferring functional gains into functional independence.

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The magnitude and direction of the coupled feedbacks between the biotic and abiotic components of the terrestrial carbon cycle is a major source of uncertainty in coupled climate–carbon-cycle models1, 2, 3. Materially closed, energetically open biological systems continuously and simultaneously allow the two-way feedback loop between the biotic and abiotic components to take place4, 5, 6, 7, but so far have not been used to their full potential in ecological research, owing to the challenge of achieving sustainable model systems6, 7. We show that using materially closed soil–vegetation–atmosphere systems with pro rata carbon amounts for the main terrestrial carbon pools enables the establishment of conditions that balance plant carbon assimilation, and autotrophic and heterotrophic respiration fluxes over periods suitable to investigate short-term biotic carbon feedbacks. Using this approach, we tested an alternative way of assessing the impact of increased CO2 and temperature on biotic carbon feedbacks. The results show that without nutrient and water limitations, the short-term biotic responses could potentially buffer a temperature increase of 2.3 °C without significant positive feedbacks to atmospheric CO2. We argue that such closed-system research represents an important test-bed platform for model validation and parameterization of plant and soil biotic responses to environmental changes.

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The radiocarbon-dated palaeoecological study of Lago Riane (Ligurian Apennines, NW Italy) presented here forms part of a wider investigation into the relationships between Holocene vegetation succession, climate change and human activities in the northern Apennines. The record of vegetation history from Lago Riane indicates that, since the end of the last glaciation, climate change and prehistoric human activities, combined with several local factors, have strongly influenced the pattern and timing of natural vegetation succession. The pollen record indicates an important change in vegetation cover at Lago Riane at ~8500–8200 cal. years b.p., coincident with a well-known period of rapid climate change. At ~6100 cal. years b.p., Fagus woodland colonised Lago Riane during a period of climate change and expansion of Late Neolithic human activities in the upland zone of Liguria. A marked decline in Abies woodland, and the expansion of Fagus woodland, at ~4700 cal. years b.p., coincided with further archaeological evidence for pastoralism in the mountains of Liguria during the Copper Age. At ~3900–3600 cal. years b.p. (Early to Middle Bronze Age transition), a temporary expansion of woodland at Lago Riane has been provisionally attributed to a decline in human pressure on the environment during a period of short-term climate change

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Sediments from the Black Sea, a region historically dominated by forests and steppe landscapes, are a valuable source of detailed information on the changes in regional terrestrial and aquatic environments at decadal to millennial scales. Here we present multi-proxy environmental records (pollen, dinoflagellate cysts, Ca, Ti and oxygen isotope data) from the uppermost 305 cm of the core 22-GC3 (42°13.53′N, 36°29.55′E) collected from a water depth of 838 m in the southern part of the Black Sea in 2007. The records span the last ~ 18 kyr (all ages are given in cal kyr BP). The pollen data reveal the dominance of the Artemisia-steppe in the region, suggesting rather dry/cold environments ~ 18–14.5 kyr BP. Warming/humidity increase during melt-water pulses (~ 16.1–14.5 kyr BP), indicated by δ18O records from the 22-GC3 core sediment and from the Sofular Cave stalagmite, is expressed in more negative δ13C values from the Sofular Cave, usually interpreted as the spreading of C3 plants. The records representing the interstadial complex (~ 14.5–12.9 kyr BP) show an increase in temperature and moisture, indicated by forest development, increased primary productivity and reduced surface run-off, whereas the switch from primary terrigenous to primary authigenic Ca origin occurs ~ 500 yr later. The Younger Dryas cooling is clearly demonstrated by more negative δ13C values from the Sofular Cave and a reduction of pines. The early Holocene (11.7–8.5 kyr BP) interval reveals relatively dry conditions compared to the mostly moist and warm middle Holocene (8.5–5 kyr BP), which is characterized by the establishment of the species-rich warm mixed and temperate deciduous forests in the low elevation belt, temperate deciduous beech-hornbeam forests in the middle and cool conifer forest in upper mountain belt. The border between the early and middle Holocene in the vegetation records coincides with the opening of the Mediterranean corridor at ~ 8.3 kyr BP, as indicated by a marked change in the dinocyst assemblages and in the sediment lithology. Changes in the pollen assemblages indicate a reduction in forest cover after ~ 5 kyr BP, which was likely caused by increased anthropogenic pressure on the regional vegetation.

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We examine the effect of ozone damage to vegetation as caused by anthropogenic emissions of ozone precursor species and quantify it in terms of its impact on terrestrial carbon stores. A simple climate model is then used to assess the expected changes in global surface temperature from the resulting perturbations to atmospheric concentrations of carbon dioxide, methane, and ozone. The concept of global temperature change potential (GTP) metric, which relates the global average surface temperature change induced by the pulse emission of a species to that induced by a unit mass of carbon dioxide, is used to characterize the impact of changes in emissions of ozone precursors on surface temperature as a function of time. For NOx emissions, the longer-timescale methane perturbation is of the opposite sign to the perturbations in ozone and carbon dioxide, so NOx emissions are warming in the short term, but cooling in the long term. For volatile organic compound (VOC), CO, and methane emissions, all the terms are warming for an increase in emissions. The GTPs for the 20 year time horizon are strong functions of emission location, with a large component of the variability owing to the different vegetation responses on different continents. At this time horizon, the induced change in the carbon cycle is the largest single contributor to the GTP metric for NOx and VOC emissions. For NOx emissions, we estimate a GTP20 of −9 (cooling) to +24 (warming) depending on assumptions of the sensitivity of vegetation types to ozone damage.

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Our aim is to reconstruct the brain-body loop of stroke patients via an EEG-driven robotic system. After the detection of motor command generation, the robotic arm should assist patient’s movement at the correct moment and in a natural way. In this study we performed EEG measurements from healthy subjects performing discrete spontaneous motion. An EEG analysis based on the temporal correlation of the brain activity was employed to determine the onset of single motion motor command generation.

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Stroke is a medical emergency and can cause a neurological damage, affecting the motor and sensory systems. Harnessing brain plasticity should make it possible to reconstruct the closed loop between the brain and the body, i.e., association of the generation of the motor command with the somatic sensory feedback might enhance motor recovery. In order to aid reconstruction of this loop with a robotic device it is necessary to assist the paretic side of the body at the right moment to achieve simultaneity between motor command and feedback signal to somatic sensory area in brain. To this end, we propose an integrated EEG-driven assistive robotic system for stroke rehabilitation. Depending on the level of motor recovery, it is important to provide adequate stimulation for upper limb motion. Thus, we propose an assist arm incorporating a Magnetic Levitation Joint that can generate a compliant motion due to its levitation and mechanical redundancy. This paper reports on a feasibility study carried out to verify the validity of the robot sensing and on EEG measurements conducted with healthy volunteers while performing a spontaneous arm flexion/extension movement. A characteristic feature was found in the temporal evolution of EEG signal in the single motion prior to executed motion which can aid in coordinating timing of the robotic arm assistance onset.

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We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover, composition and 5 height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, 10 and are compared to scores based on the temporal or spatial mean value of the observations and a “random” model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), and the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global 15 vegetation models (DGVMs). SDBM reproduces observed CO2 seasonal cycles, but its simulation of independent measurements of net primary production (NPP) is too high. The two DGVMs show little difference for most benchmarks (including the interannual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified 20 several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change 25 impacts and feedbacks.

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Atmospheric CO2 concentration is hypothesized to influence vegetation distribution via tree–grass competition, with higher CO2 concentrations favouring trees. The stable carbon isotope (δ13C) signature of vegetation is influenced by the relative importance of C4 plants (including most tropical grasses) and C3 plants (including nearly all trees), and the degree of stomatal closure – a response to aridity – in C3 plants. Compound-specific δ13C analyses of leaf-wax biomarkers in sediment cores of an offshore South Atlantic transect are used here as a record of vegetation changes in subequatorial Africa. These data suggest a large increase in C3 relative to C4 plant dominance after the Last Glacial Maximum. Using a process-based biogeography model that explicitly simulates 13C discrimination, it is shown that precipitation and temperature changes cannot explain the observed shift in δ13C values. The physiological effect of increasing CO2 concentration is decisive, altering the C3/C4 balance and bringing the simulated and observed δ13C values into line. It is concluded that CO2 concentration itself was a key agent of vegetation change in tropical southern Africa during the last glacial–interglacial transition. Two additional inferences follow. First, long-term variations in terrestrial δ13Cvalues are not simply a proxy for regional rainfall, as has sometimes been assumed. Although precipitation and temperature changes have had major effects on vegetation in many regions of the world during the period between the Last Glacial Maximum and recent times, CO2 effects must also be taken into account, especially when reconstructing changes in climate between glacial and interglacial states. Second, rising CO2 concentration today is likely to be influencing tree–grass competition in a similar way, and thus contributing to the "woody thickening" observed in savannas worldwide. This second inference points to the importance of experiments to determine how vegetation composition in savannas is likely to be influenced by the continuing rise of CO2 concentration.