In the positional level condition the first noun was animate whereas the second was inanimate. We found activation of Broca's and adjacent areas, previously indicated as responsible for syntactic processing. Additionally, a later onset of the activation in three brain areas in the functional level condition suggests that there is indeed a competition for assignment of subjecthood. The results constrain theories of grammatical encoding, which differ in whether they assume two separate processing levels or only one.The aim of the present fMRI study was to investigate the neural circuits of two stages of grammatical encoding in sentence production. Participants covertly produced sentences on the basis of three words (one verb and two nouns). In the  Words that must be selected and retrieved from the mental lexicon are two nouns  and a verb (to chase). Then the syntactic functions are assigned, namely the subject function (the cat), the object function  and the verb function (to chase). At this level, the functions of the words are defined but their order is not. Third, there is the positional level during which a hierarchical constituent structure is established allowing the speaker to put the elements in the correct order (constituent assembly) and during which the morphological processes (inflection) take place. This level determines that, for example, the cat is placed at the beginning of the sentence and that the verb to chase carries the right morphological markers for third person singular present. So it is at this level that the previously specified functions are combined with information about, for example, the tense, the aspect and the number. Finally, the fourth level of phonological encoding level retrieves and assembles the sounds of the sentence before articulation The aim of this study was to investigate the neural circuits involved in grammatical encoding, that is, the processing level that specifies the structure of an utterance. This level plays its part after the creation of a message to convey the intended meaning and before the retrieval of the phonological features of a sentence, and consists of a number of processes that realize the intended concepts into a linguistic plan . The psyhot under the belt, when collar is intended my boy terrifies the cat next door when my cat terrifies the boy next door is intended I went to get my park trucked the words truck and park switch position, but the suffix -ed is in the correct location suggesting that inflectional morphemes are part of the phrasal frame. An experiment investigating subject-verb agreement revealed that agreement relations are processed before word order determination takes place The two-stage model of grammatical encoding  is supported by various sources of evidence. For instance, important support for the model comes from speech error analyses. Semantic substitutions as in the arrow and the bag” or a short sentence as “the arrow is next to the bag”. Semantically or phonologically related distracter words accompanied the stimuli presentation. Onset naming latencies were longer in presence of a distracter that was semantically related to either of the two nouns, whereas facilitation occurred with a phonological related distracter only for the first noun. The results suggested that before producing such an utterance, both target lemmas need to be selected. When two thematic roles (agent and theme) are equally accessible because both are animate , they compete for the grammatical assignment to the role of subject. On the contrary, when the agent is animate and the theme is inanimate , no competition occurs for the assignment in the subject position.The two-stage model is also consistent with studies that tested the effects of conceptual and lexical variables on speaker's assignment of subjecthood to nouns. McDonald, Bock, Kelly The study of neural circuits involved in grammatical encoding has not received the same level of attention as behavioural studies. Because of the difficulty to control variables involved in the production of utterances, especially in the experimental setting of fMRI, many authors concentrated on the study of the neural circuits involved in single word processing, providing evidence about how words are lexically organized, represented and retrieved the red square launches the blue ellipse), in a further condition they produced just a sequence of noun phrases with a local syntactic structure but not a sentence level syntactic structure , and in a third condition they just produced a list of single words with no syntactic relationship . Relative to the baseline conditions, the full sentence condition elicited the activation of the left anterior rolandic operculum which varied with the complexity of the syntactic processing. Golestani Among the few neuroimaging studies Haller, Radue, Erb, Grodd, Kircher In the present fMRI experiment we aimed to map the functional and positional level of grammatical encoding. Animate nouns are likely to be assigned the grammatical function of subject. We hypothesize that the production of a simple subject-verb-object sentence with two animate nouns introduces a competition for subjecthood or a competition at the functional level of processing. We expect that a similar sentence with an animate and inanimate noun does not induce such a competition.In the functional level condition, participants were visually presented with three words  and required to covertly produce a non reversible, semantically plausible sentence (the cat chases the mouse). In the positional level condition, the same materials were used except for the direct object that was inanimate . Also in this case participants were asked to covertly produce a non reversible, semantically plausible sentence . To isolate regions involved in covert sentence production, a covert word reading task was introduced. Participants were required to covertly read the words visually presented. By comparing the functional and the positional level conditions we mapped the regions of activation of the functional level; where words are retrieved and the competition between two animate entities takes place. By comparing positional and word reading conditions we mapped the areas involved at the positional level of processing, where no competition is required, but where speakers still have to build the constituent structure and the correct word order.The Ethic Committee of the Ghent University Hospital approved the research. Participants gave written informed consent according to the institutional guidelines of the Ethic Committee of the Ghent University Hospital.Twenty healthy participants  between 19 and 30 years old (mean ± SD: 23.2±3.3 years) took part in the study. All participants were native Dutch speakers with a normal or corrected-to-normal vision and right-handed as assessed by a handedness inventory achtervolgen/to chase, leeuw/lion, zebra/zebra vs achtervolgen/to chase, leeuw/lion, auto/car).Forty pairs of triplets (one verb and two nouns) were built. Each pair of triplets included a verb in the infinitive form (e.g. achtervolgen/to chase) and an animate noun (e.g. leeuw/lion). The triplets differed in the second noun chosen so that in one case it represented an animate entity (zebra/zebra) whereas in the other case it represented an inanimate entity (auto/car), resulting in two paired triplets (leeuw achtervolgt een zebra/the lion chases the zebra), given the triplets ; in the other they only had to covertly read the triplets of words . This resulted in a 2×2 factorial design with level of processing: functional (FUN) or positional (POS) and task: reading (READ) or sentence generation (SEN) as factors. Four different lists of four blocks each were built. Each block included ten triplets per condition. Before running the experiment, an independent sample of twenty participants performed the task out loud to verify that the triplets did not elicit passive sentences that could introduce additional confounding syntactic complexity. The results showed that participants produced active forms for 97% of the triplets. Frequency of occurrence for the nouns in the two conditions (zebra vs. auto) was calculated by means of the SUBTLEX-NL Verbs were always put at the beginning of the triplets to avoid any biased order for the two nouns. The position of the nouns in the triplets was balanced. Triplets were built so that there was always one noun that could be a much more plausible agent than the other . Two tasks were chosen: in one task participants had to covertly produce a sentence . At the beginning of the experiment participants were instructed about the tasks they had to perform.In order to inform the participants about the task to execute, each block either started with the instruction “read words” or with the instruction “produce sentence”, displayed on screen for 7 seconds. Within blocks, the word triplets in the functional and positional level conditions were intermixed and the order of the blocks and lists was counterbalanced across subjects. Both tasks were performed in silence to avoid any speech related movement artefacts. To build in a low-level measure of task performance and alertness, participants pressed a button when finishing the appropriate task for each trial.Finally, several studies have demonstrated different activation patterns in human visual cortex for animate and inanimate objects www.pstnet.com).Stimulus presentation and response collection across the entire study was controlled using E-Prime  with an eight-channel PA head coil for radio-frequency transmission and signal reception. Whole brain functional images were acquired using a T2*-weighted sequence sensitive to BOLD contrast; 664 for the main experiment and 107 for the localizer task . A 3-D high-resolution T1-anatomical image of the whole brain was also obtained for coregistration with the functional images .www.fil.ion.ucl.ac.uk/spm). The first four volumes of all EPI series were omitted from the analysis to allow the magnetisation to approach a dynamic equilibrium. First, the slices of each functional image were temporally realigned with the acquisition time of the middle slice. Next, motion artefacts were removed from the functional images by realigning all images to the mean image using a rigid body spatial transformation The neuroimaging data were analysed using statistical parametric mapping (SPM5) , hence the finite impulse response model encompassed a total period of 15.78 sec, time locked to the start of each trial. This resulted in a total of 24 vectors that formed the covariates of interest in a general linear model http://afni.nimh.nih.gov/pub/dist/doc/program_help/3dClustSim.html). For each subject, the final SPM(t)s were superimposed on the high-resolution anatomical scan in order to identify the corresponding anatomical regions of significantly activated clusters, and the anatomical details were compared with the atlas of For each participant we calculated linear contrasts of the corresponding beta weights for each time bin, averaged across sessions. This resulted in one SPM(t)-map per time bin for each contrast of interest. These SPM(t)s were then passed on to the second-stage analysis and modelled as a one-way ANOVA with time bin as factor and treating participants as a random variable SEN + POSSEN]>[FUNREAD + POSREAD]). To ensure that the identified clusters at the second-stage analysis displayed a signal compatible with the hemodynamic character of the BOLD measure, the contrast weights were selected to reflect a canonical hemodynamic function subsampled at each time bin.A number of contrasts of interest were calculated. First, we identified the sentence generation network, irrespective of the level of processing ([FUNSEN≠ POSSEN] inclusively masked with [FUNSEN + POSSEN]>[FUNREAD + POSREAD]). As we had no a priori hypothesis, we used an F-test to identify potential differences at any of the time bins. To further gain insight in these differences, we conducted a time course analysis using MarsBar SEN and POSSEN in each time bin. Next, the per cent signal change was calculated and plotted per time bin, resulting in a peristimulus time histogram. A paired t-test was then computed for each time bin to assess the statistical significance of the potential differences between FUNSEN and POSSEN.Second, we used the resulting group SPM(t) associated with the sentence generation network as a refined search space to detect potential differences between the two sentence generation tasks ( inclusively masked with [FUNSEN>FUNREAD], and [POSSEN> FUNSEN] inclusively masked with [POSSEN> POSREAD]. Again, the contrast weights reflected a canonical hemodynamic function sub-sampled at each time bin.Furthermore, we tested if either of the sentence generation tasks recruited specific additional areas beyond the sentence generation network, by calculating the following contrasts in the voxels not included in the sentence generation network: [FUNCommon sentence generation related activity was observed in a left lateralized network with significant clusters in the inferior frontal sulcus extending into the inferior frontal gyrus, the superior frontal sulcus, pre-SMA, anterior and middle IPS, and fusiform gyrus see . The locWithin this network, three clusters showed differential sentence generation related activity see . In the Finally, only sentence generation at the functional level compared to positional level recruited extra areas that did not belong to the sentence generation network. This type of sentence generation additionally recruited bilateral precuneus . Positional sentence generation compared to functional sentence generation did not recruit any extra areas not belonging to the sentence generation network.Our data confirm that sentence generation in general requires neural circuits that several studies have indicated as responsible for syntactic processing In a paper by Friederici et al. We also observed activation of the visual word form area (VWFA). Traditionally, this area is taken to support the activity connected with the initial word recognition stages during reading. However, Price et al. Activation of the pre-SMA is in general attributed to motor sequence control. However, only in recent years this area has been the object of intense scrutiny and the results provide evidence that it may be involved in several processes, from motor control to eye movements A difference in the hemodynamic activation between functional and positional level of processing was observed within the sentence generation network. Pre- SMA, VWFA, and the inferior frontal sulcus extending into the inferior frontal gyrus showed a delayed hemodynamic response onset in sentence generation at the functional level with respect to the positional level. None of these brain areas were involved in categorizing nouns as animate or inanimate, ruling out a possible semantic effect. In addition, one may argue that the competition effect observed originates during conceptualization, so that in the triplets chase/lion/zebra “lion” and “zebra” would be in competition to become the agent, hence there would be competition to conceptualise the event as a lion chasing a zebra or a zebra chasing a lion. However, as already described in the material section, the verb and the two nouns were selected to form a non-reversible sentence. As the triplets were paired and functional level condition differed from positional level only because of the two animate nouns, our interpretation is that the delay observed in areas crucial for production is given by the competition for subject position. Behavioural data seem to support this view. Since Bock and Warren Though Broca's area has been associated with competition in sentence processing the driver showed the overalls with the stains to the mechanics” (non-shifted form) has a grammatical alternative expressed in “the driver showed to the mechanics the overall with the stains” (shifted form). The two forms share the same relations but differ in how the constituents are ordered. On a two-stage view, the shifted version should have primed the non-shifted version. However, no such priming occurred and the authors concluded that dominance relations  and linear relations  are determined in a single stage. The results obtained here seem to contradict this view, rather suggesting that different neural circuits are involved at different stages of sentence production. To conclude, in an fMRI experiment we investigated the functional and positional level of processing. Though it is only a first step inside the syntactic box, the results provide some insights that may contribute to identify the neural paths supporting sentence production.Some behavioural data on syntactic priming effects challenged the idea that grammatical encoding consists of a series of different processes each devoted to the elaboration of a specific syntactic sub-process. For example, Pickering, Branigan, Mclean,


How do the feedbacks between tectonics, sediment transport and climate work to shape the topographic evolution of the Earth? This question has been widely addressed via numerical models constrained with thermochronological and geomorphological data at scales ranging from local to orogenic. Here we present a novel numerical model that aims at reproducing the interaction between these processes at the continental scale. For this purpose, we combine in a single computer program: 1) a thin-sheet viscous model of continental deformation; 2) a stream-power surface-transport approach; 3) flexural isostasy allowing for the formation of large sedimentary foreland basins; and 4) an orographic precipitation model that reproduces basic climatic effects such as continentality and rain shadow. We quantify the feedbacks between these processes in a synthetic scenario inspired by the India-Asia collision and the growth of the Tibetan Plateau. We identify a feedback between erosion and crustal thickening leading locally to a <50% increase in deformation rates in places where orographic precipitation is concentrated. This climatically-enhanced deformation takes place preferentially at the upwind flank of the growing plateau, specially at the corners of the indenter (syntaxes). We hypothesize that this may provide clues for better understanding the mechanisms underlying the intriguing tectonic aneurisms documented in the Himalayas. At the continental scale, however, the overall distribution of topographic basins and ranges seems insensitive to climatic factors, despite these do have important, sometimes counterintuitive effects on the amount of sediments trapped within the continent. The dry climatic conditions that naturally develop in the interior of the continent, for example, trigger large intra-continental sediment trapping at basins similar to the Tarim Basin because they determine its endorheic/exorheic drainage. These complex climatic-drainage-tectonic interactions make the development of steady-state topography at the continental scale unlikely. The surface of the Earth’s continents is primarily shaped by a competition between the relief-generating tectonic deformation and the relief-reducing erosion and surface transport of rock. As topography grows above sea level  by tectonic motions, so do the energy, transport capacity, and efficiency of most erosion and surface transport mechanisms. In the continental scale, the main transport agent for surface sediment transport is the river network. While the combined effects of tectonics and erosion on the topography of continents have long been studied, only in the last 3 decades have numerical models provided some quantitative understanding of classical geomorphological concepts such as base level, retrogressive erosion, river piracy, or peneplanation.More subtly, models of orogenic growth have shown that surface mass transport on the surface of the solid Earth not only responds to the tectonic deformation to shape geomorphological features, but it also actively modifies the distribution of stress within the crust and the subsequent tectonic deformation patterns. Field evidence for this phenomenon remains scarce –3, but aThis feedback has been addressed generally through 2D models (in cross section) and at the local and orogenic scales, whereas river networks drive surface transport typically parallel to the geological structures and far from the collision area. The question remains as to whether the asymmetrical fluvial transport may have an influence on lithospheric deformation  and how Separately, a growing view has developed that sees tectonic uplift and topographic changes  as controls on the atmosphere and ocean circulation and therefore as global climate drivers  incorporating a fully thermally-coupled formulation to a thin-sheet model of lithospheric deformation; 2) incorporating regional isostasy to a thin sheet deformation model to allow the formation of flexural sedimentary basins; 3) incorporating orographic precipitation; and 4) accounting for evaporation and climate continentalisation as mechanisms potentially leading to the formation of closed, endorheic lakes acting as surface water sinks and sediment traps. The source code of the programs solving the equations involved is publicly available to allow the reproducibility of the results. We now present a comprehensive description of the algorithms and formulations of the physical processes that we consider responsible for the main trends of the continental-scale topographic evolution.UhuruTISC after the two independent codes from which it derives: the thin-sheet thermomechanical model Uhuru . S. S32]. SThe horizontal velocity field of the thin sheet is calculated in response to prescribed velocity at the boundary  and the gravitational potential energy related to lateral thickness and density variations of the sediment layer, the crust, and the lithospheric mantle . The resThe topographic growth is simulated via the viscous deformation of a thin sheet representing the lithosphere, assuming mechanical coupling between crust and lithospheric mantle. The rheological behaviour of the thin sheet is depth-averaged, and hence the internal geometry of the tectonically deformed crust and sediments is out of the scope of this study. Because the typical scale for faulting is two orders of magnitude smaller than the orogenic or basinal features of our model, sediment is simply thickened in the same factor as the lithosphere does. At each time step and each cell of the model, the additional weight of rock related to the thin-sheet thickening and to erosion/sedimentation is added to the total load resting on the flexural plate.H. We need to find the distribution of the mean horizontal velocity u1,u2 and the correspondent thickening at each point of this thin sheet. Under the assumption of plane stress, where the vertical shear stresses are null, the deformation of the lithosphere can be treated in terms of vertically-averaged magnitudes. The momentum equations are vertically averaged within the plate, to reduce the three-dimensional problem to a planform model, where the horizontal velocity components do not change with depth (a detailed formulation is available in . I. I37]. ITe. The expression used to calculate the flexural deflection w(x) is , ρa is the density difference between the underlying viscous asthenosphere and the fluid overlaying the system (air or water), and qi is the load distribution . x and y are the horizontal coordinates equivalent to x1, x2 in the previous section. The equation can be developed . A. A31]. Asensu ), i.e., sensu . This trStudies of river incision and sediment transport have provided quantitative models of landscape evolution driven by surface water flow , using a steady flow approach to calculate erosion and transport along river channels. This means that no transitory effects in water flow (such as floods) are accounted, and that at each time step, the precipitation in the entre model domain equals the evaporation in the endorheic lakes plus the water reaching the ocean or exiting the domain through the boundaries.The approach developed here is based on that developed by  and implτb:Erosion is approached as a power law function of basal shear stress zt is the elevation of the surface of the solid Earth relative to the present sea level, positive upwards. Note that the spatial coordinates x, y, z are respectively equivalent to x1, x2, -x3 in the previous sections. Both the erodability kb and a are positive constants. We use a value of a = 1.5 W=kwQaw/qeq to reflect the sediment saturation of the river as q approaches qeq. For q>qeq, all excess sediment load q-qeq is deposited.We calculate Similar formulations have been proposed to explain the incision along rivers and the transition to aggradation, such as the stream power model ; the uniAll equations are solved using the finite difference method, using the same rectangular grid as for the thin-sheet equations.precipitation.This model component is partly based on that developed in , 31]. W. W31]. Wx,y can be written asEach topographic cell has a certain water discharge as a result of the addition of local runoff (rainwater delivered to the drainage network) and water coming from the tributary surrounding nodes. The resulting discharge is transferred to the lower node of the river (determined by the maximum slope) after evapotranspiration has been subtracted. Underground flow is ignored. The water balance in a cell located at Q is the local water discharge, P is rain precipitation (the component collected as surface runoff), E evaporation, and Δx, Δy are the dimensions of the cell. Conservation of total water flowing all over the model at a given time must also be accomplished:Where We chose the climatic parameters to predict a precipitation distribution similar to the present one in the India-Asia collision zone and to best account for the present mean discharge of the main rivers. The code tracks precipitation waters towards enclosed lakes situated at local topographic minima of the basins and calculates the extension of these lakes accounting for surface evaporation that, when exceeding the amount of collected water, triggers endorheism by cancelling the lake outlet. Transitory flow effects are not accounted for, and the amount of water leaving the model by evaporation or along the boundaries equals the total amount of precipitation at every time step.A specific feature of this surface process model is that the formation of lakes in local topographic minima is explicitly accounted for. The motivation behind this is the aim at capturing the key role of the geometry of lakes during drainage evolution, since they determine the localization of intramountain sedimentation in the water body and of erosion along the outlet. Lakes are geomorphologically important because they redefine the local base level that shapes the distribution of erosion. In practice, we first calculate the drainage network including the extension of lakes, ignoring the potential lake closure and reduction caused by evaporation. We do this by tracking all nodes in the grid from the lowest to the highest in elevation, which allows an efficient detection of the local topographic minima.P is the mean precipitation rate in the lake’s hydrographic basin of area Alb; E is the evaporation at the lake’s surface; and Al is the area of the closed lake. The level of lakes changes as a function of lake evaporation E, precipitation runoff P, and river supply R.To account for endorheic basin formation, lake evaporation has been incorporated in the model as an improvement on the algorithm of . The amoEvaporation can eventually cancel the lake's water excess see  and thenIf the water level of a closed lake rises higher than the lowest surrounding topographic saddle , then the drainage becomes open. Normally, incision along the outlet river will lead to a relative fast integration of the lake into the drainage network (drainage capture).x,y direction while the air column moves vertically following the local topography. Humid air enters the model through the upwind boundaries of the model domain and then follows the mean wind direction (assumed constant in this paper). The air column changes in water content by exchanging water with the surface of the solid Earth via condensation (precipitation) and evaporation, both controlled by the level of water saturation of the air column. As the air column is forced to move uphill, it reduces its capacity to contain vapour, eventually losing water by precipitation. Also over flat regions the air produces precipitation by turbulent flow. In this way the model captures the gradual continentalization of weather (aridification) as air moves inland. The content of water in the air column only increases by evaporation, when passing over the sea or a lake. The model is water conservative: the amount of atmospheric water entering the domain through the boundaries equals the amount of water leaving it either as air moisture or as surface water, for each time step of the model evolution.Before calculating water discharge and river incision, the model needs to estimate the precipitation and evaporation distribution throughout the evolving topography. We have developed an algorithm based on a previous cross-section model by . To accozt is the ground elevation, ρv is the vapor density, es is the saturation vapor pressure at a given temperature T, Rv = 461.5 J kg-1 K-1 is the vapor gas constant, and es0 = 611 Pa is the saturation vapor pressure at T0 = 273 K. Air temperature varies with altitude above the ground (z-zt) asTzt is the ground temperature (at z = zt), Tsl is the ground temperature at sea level, in K, and Γ = 0.0065 K/m is the standard temperature lapse rate in the atmosphere. As a result, the maximum water content in an air column The orographic precipitation and evaporation module is a pseudo-3D adaptation of the pseudo-2D (cross-section) model developed in  to paramn  changes as a result of the incoming humid air, plus the evaporation supplied from the surface minus the precipitation. Vapour mass conservation provides the spatial derivative of Hw:dl’ is a distance differential in the wind direction, P is the precipitation, E the evaporation, and uw is the absolute value of the mean horizontal wind speed. Such approach captures the vapor mass balance between the incoming wind and the evaporation/precipitation exchange with the ground, which has been neglected in previous surface process models but is of capital importance in this paper because humid air is expected to cross a series of topographic highs and lows containing lakes that reload the air with moisture.The actual water content in an air column Hw to approach or retreat from the saturation value P’ is the condensation produced by the air column above any given location x, and α’ [L T-1] is a constant controlling the precipitation occurring due to turbulent air flow when saturation is not reached. Processes such as air uplift after a humidity reload over a lake or an ocean may result in P’. Note that the orographic effect on condensation is contained in Hw is reduced by precipitation as air moves inland. The adopted boundary condition is RH  and witE0 is a reference evaporation rate for a hypothetical dry, calm air , and β is the proportionality constant with wind velocity.Where For the initial set-up of the reference model  and the positive x as East (E), and we will use the terms Tarim and India to refer to the rigid block and the indenter, respectively.For computing-efficiency reasons , the modelling domain is shifted northwards together with the indenter . Thus, Although the model allows for lateral changes of the elastic thickness, for the reference setup we adopt again for simplicity a constant elastic thickness of 65 km, a compromise between values estimated for the Tarim  a) a43]) aWe impose a relative humidity of the incoming air of RH = 1, entering the model from the southeast with a 30-degrees azimuth wind direction.Other climatic, erosional, and tectonic parameters are listed in t = 50 My, which represents the present day if comparing with the India-Tibet analogue. Note that the origin of the y axis moves in t = 20 Myr this foreland basin has become fluvial, drained by two main rivers towards both sides of the indenter, in a position similar to the present-day Indus and Ganges rivers. Deposition in this basin takes place by fluvial aggradation, as it will be seen later. Meanwhile, the hinterland of the range  has become a large plateau with a large endorheic basin centred on a large closed lake at an elevation above 1200 m. The rest of this plateau drains towards the boundaries of the model except for its central northern part that drains towards another closed endorheic basin formed on the pre-imposed rigid block . The little amount of precipitation collected by this basin, together with its high evaporation rates (both caused by the dry climatic conditions forming in this lee-side of the plateau), cause this ‘Tarim’ lake to remain small in area and below sea level. Note that all the endorheic lakes in the model acquire exactly the surface area needed to evaporate the water supplied by rivers. The lake system in the high plateau is later captured by the eastern rivers at t = 30 Myr, and eventually becomes captured too by the Tarim drainage (t = 40 Myr).The topographic evolution of the reference model is shown in t = 50 My, . One such area is the northern edge of the indenter. The foreland basin formed on the northern boundary of the indenter match to first degree the Cenozoic sedimentary thickness of the Indus and Ganges basins, with maximum values that change along the E-W strike from 2 to 7 km and a basin width ranging from 250 to 700 km Figs  and 6. AThe precipitation rates vary from >9 m/yr in the southern flank of the plateau to less than 0.1 mm/yr in the Tarim-like basin Figs  and 7, wIn Tarim block that roughly matches previous reports for the Tien-Shan range . A. A26]. AThe timing of both rock and surface uplift in the Tibet is a matter of intense discussion with paleodrainage, paleoelevation, and paleoclimatic evidence being interpreted as both favouring northeastward growth of the plateau , 56] or or56] orThe climate continentalization of the Asian interior has been previously linked both to the surface uplift of the Tibetan Plateau and to global cooling. The lack of consensus on the age of aridification prevents the elucidation of the relative quantitative importance of these factors , 58], b, b58], bThe model explicitly accounts for the interplay between lithospheric and surface processes in both directions: first, surface processes determine the way mass is redistributed in space and time, thus modifying the isostatic vertical motions and the subsequent tectonic deformation that accommodates plate motions. Secondly, the crustal and lithospheric tectonics control and organize the non-linear nature of drainage networks, and the localization of precipitation in response to topographic growth. In zones deformed by folding and thrusting, the local drainage evolution is controlled by the kinematics of such tectonic deformation. Other mechanisms such as lithospheric flexure can become relevant in determining the drainage network in less deformed areas such as at the external margin of foreland basins , 61] or or61] orε33, at t = 50 Myr relative to its average value. The results show that structural rheological contrasts such as the pre-existence of stronger lithospheric domains in the plate are more relevant in determining the localization of deformation, sedimentary basins, and topographic highs and lows, in front of climatic/erosional heterogeneities  due to this effect.In presence of inherited tectonic structures of moderate strength contrast, these dominate over climatic/erosional effects in shaping tectonic deformation, and the erosion/sedimentation effects become hardly detectable. For example: In our synthetic scenario, the deformation rates along a N-S transect from the Himalayas to the Tarim basin shows variations of <15% when changing between extreme-case climatic scenarios.The aridification of climate resulting from the growth of the orographic rain shadow during continental collision enhances intracontinental sediment trapping by promoting endorheism  in the plateau and the lee side of the orogen.The evolution of the drainage patterns responsible for surface rock redistribution and the location of sedimentary sinks can be significantly modified by climatic factors such as the evaporation regime and by orographic precipitation patterns. Enhanced rain in the upwind side of the continent and enhanced evaporation/precipitation ratios in the lee side determine the sediment and water overflow of sedimentary basins, and their possible colmatation and erosion. Large-scale drainage changes (river piracy) may have been favored by the presence of land-locked plateau basins that are captured as they grow in elevation and become eventually overfilled by sediment or water. This adds to the possible role of an abrupt tectonic uplift at the eastern Tibetan Plateau, proposed by ) and 2626). SurfWe show a first attempt to describe the evolution of topography at continental scales accounting for a process spectrum ranging from continental collision to orographic precipitation. A detailed set of mathematical formulations for these processes and the associated computer code to solve them are provided with this paper. Under the approximations adopted for this work and subject to the aforementioned limitations, the following conclusions  and the thickening rate (contours) in response to tectonic convergence and continental collision.(MOV)Click here for additional data file.


Although accumulating evidence over the past thirty years indicates that noise is an environmental stressor in residential settings, much of the data emanated from studies in high-intensity, noise impact zones around airports or major roads. Little is known about religious noise, especially at night, which is increasingly a growing concern for both the general public and policy-makers in sub-Saharan Africa. Using geographical information systems (GIS), this study measured and mapped exposure to religious noise in a rapidly urbanising municipality in Ghana. Quantitative noise risk assessment was used to evaluate the risk of religious noise-induced hearing loss to residents in the exposed neighbourhoods. The results show that all neighbourhoods where churches were situated had at least one location with significant risk of noise-induced hearing loss. However, there was no statistically significant relationship between neighbourhoods where religious noise exposure was the highest and where noise annoyance was the highest. The magnitude of the noise values for night-time exposure is remarkable particularly given that excessive night-time noise exposure has the greatest detrimental effect on public health. There is the need to focus on vulnerable groups, sensitive hours of the night, and possible confounding with air pollution in order to wholly address this potential hazard. The proliferation of environmental noise is a defining characteristic of the 21st century , and this technique gives unbiased estimations. Generally, these factors would describe some external limit (restriction) on the input data, which cannot simply be observed in the measured values. The constraint factor in the ordinary Kriging equations, called the Lagrange multiplicator, was used in this study. If the sum of all weighting coefficients is 1, Kriging expression can be written asPrevious equation also can be written as the matrixThe noise levels recorded at the churches and mosques and the various distances away from the noise sources all exceeded the EPA permissible level of 48 dB(A) for night time (2200–0600 h) expected for residential areas. These are presented in Tables Generally, dose for mosques decreased with increasing distance from the noise source. At the source, the magnitude of dose in decreasing order was as follows: White and Cream Mosque (Zongo Laka) > Green and Cream Mosque (Taifa) > Cream and Green Mosque (Night Market) > Yellow Mosque (Zongo Laka) > White Mosque (Night Market) > White and Green Mosque (Night Market). Residents who are chronically exposed to noise from the first three locations are at significant risk of noise-induced hearing loss whereas residents within the vicinity of White Mosque (Night Market) are at minimum risk. Also, in terms of neighbourhood, Night Market and Zongo Laka areas had the lowest and highest night-time noise exposure, respectively .Regarding churches, all neighbourhoods had at least one location with significant risk of noise-induced hearing loss . At the As observed in This study measured the levels of religious noise produced in the Ashaiman Municipality, a rapidly growing urban environment in Ghana, constructed a night-time noise map indicating the distribution of exposure in residential neighbourhoods of the Ashaiman Municipality, and assessed the risk of religious noise-induced hearing loss to residents in the exposed neighbourhoods. In this municipality there are several worksites for artisanal metal workers in the informal sector. These noise-intensity work environments deliver significant noise to this subset of the people  living in these neighbourhoods. Night-time noise adds to the daytime noise dose. The results showed that all the twenty-three churches and six mosques sampled produced night-time noise levels far exceeding the EPA's guidelines standard of 48 dB(A) for night (2200–0600 h). The noise maps generated also showed that most of the communities were exposed to high noise levels due to religious activities as most of them were within the extremely high, very high, and high noise exposure zones. Just a few communities were within the moderately high zone, but none of the communities was within the low noise exposure zone. The night-time noise levels obtained in this study are comparable to the observations of Armah et al.  in the CThe magnitude of the figure for night-time noise exposure is striking particularly given that excessive night-time noise exposure has the greatest detrimental effect on public health. If the foregoing exposure levels were extrapolated for the entire Accra and Tema areas it quickly becomes obvious that the magnitude of the problem is considerable. The impact that these levels of exposure are having on individual health and the quality of life as well as the economic impact in terms of reduced productively of residents is likely to be considerable also.Interestingly, there was no statistically significant relationship between neighbourhoods where religious noise exposure was the highest and where noise annoyance was the highest. This finding supports the results Armah et al.  obtainedSeldom are populations exposed to a single source of noise pollution. Usually, noise exposure is complex consisting of several simultaneous noise exposures . This means that the noise exposure estimates in this study could be far less than the expected composite noise levels. In any case, there is some level of risk of noise-induced hearing loss as shown in this study and the potential effects of exposure cannot be discounted. In fact, the effects of noise exposure depend on several factors, and the absence of a clear dose-effect relationship is certainly due to the complex interactions of these factors, including the noise characteristics, the individual sensitivity, and the context of the explored living environment . HoweverContinuous high level exposure can lead to aggression in a hostile, angry, and helpless population. It is often the population with the least income that suffers the most from noise in general. Future epidemiological noise research will need to focus on vulnerable groups, effect modifiers, sensitive hours of the night, coping mechanisms, differences between noise sources, possible confounding with air pollution, differences between objective (noise level) and subjective (noise perception) exposure, and multiple exposures .This study shows that night-time exposure to religious noise is a growing menace in urban residential areas in Ghana. As expected, noise dose for mosques and churches decreased with increasing distance from the noise source. The magnitude of the figure for night-time noise exposure is striking particularly given that excessive night-time noise exposure has the greatest detrimental effect on public health. All neighbourhoods where churches are situated had at least one location with significant risk of noise-induced hearing loss. However, there was no statistically significant relationship between neighbourhoods where religious noise exposure was the highest and where noise annoyance was the highest. Further research is required to focus on long-term effects of night-time noise exposure of different populations. In this context, the study of specific subgroups can be considered to be “at risk” .


In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players’ behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents’ behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data.The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for  The increasing demand for energy, the improved sensitivity to environmental issues, and the need for a secure supply are all contributing to a new vision of energy resource management , 2. ThisSuch a scenario induces unavoidable effects on the electricity market which reveals an unexpected sensitivity to the enhancement of distributed generation based on Renewable Energy Sources (RES) –8. In faCurrent electricity markets aim to reach efficient equilibrium prices at which both producers and distributors could sell electricity profitably. Typically, the electricity markets are hierarchically structured according to time-based criteria strictly connected to the power system’s constrains. In particular, the Short Term Market (ST) is usually structured into One-Day-Ahead Market (ODA), Intraday Market (ID) and Ancillary Service, Reserve and Balancing Market (ASR) . Almost In this paper we present a simplified model that, taking into account the power system constraints, allows us both the forecasting of the balancing market and the singling out of the contribution of various actors into the formation of the price. Our model is data-driven, since information on the day-ahead market transactions is used to tune the agent-based simulation of the market behaviour. In our model we take as static constraints: (i) the grid topology; (ii) the type of production per node and (iii) the transmission rules. Our dynamical constraints are the maximum and minimum generation from power stations and their ramp variation (i.e. how fast the amount of generated energy can be changed); such constraints influence factors like the short term availability of an energy source. The inputs of our model are typical consumer requests and the forecast of geo-related wind and solar energy generation. We model the balancing market by introducing agents aiming to maximise their profits; such agents mimic the market operators of conventional generators . The ageRESs have a fundamental impact on the functioning of the electricity market due to the technical constraints of power systems, which require an instantaneous balance between power production and demand. In fact, the electricity market is structured to guarantee matching between the offers from generators and the bids from consumers at each node of the power network according to an economic merit order . To perfThe most extensively studied market sector is the day-ahead market, which has been modelled both in terms of statistical analysis of historical data , game threal-time power reserve. In fact, ASR allows us to compensate for the unpredictable events and/or the forecasting errors that can occur to the whole power system. In particular, the Balancing Market (BM) has a fundamental role in guaranteeing the reliability of the power system in presence of the deregulated electricity market.On the other hand, few models have been proposed for the last market section , 19–21, The most important studies in ASR modelling aim to provide methods that allows the forecasting of the amount of power needed for network stabilization purposes , 19–21, Our model is characterised by three phases: sampling of the perturbations, training of the agents, and forecasting of the balancing market.In the first phase we use the information about the ODA and ID market to deduce realistic power flow configurations by taking into account the physical constraints of the electricity grid. We then introduce stochastic variations related to the geographic distribution of power consumption and RES generation; in such a way, we generate a statistical sample of configurations representing realistic and geo-related time patterns of the energy requests/productions to be balanced. In this paper we will consider only the simples stochastic model of variations, i.e. uncorrelated Gaussian fluctuations with zero mean and variances from historical data. The difference at each time between the total actual power requests and the volume of the ODA+ID market is the size of the balancing market. The result of this phase samples the statistics of fluctuations induced by renewable sources; hence, it has important applications for energy security (forecasting energy congestions and/or outages) and for maintaining quality of service. We show in In the second phase we use such balancing requirements together with the static and the dynamic constraints of conventional power plants to train the agents of the balancing market by optimising their bidding behaviour (see sec.2).Here the balancing market generators are only conventional; hence, optimising the usage and implementation of renewable resources to diminish short time market fluctuations is crucial to augment the sustainability of power production.The time evolution of the balancing market size.The time evolution of the electricity pricesThe market share for each technology typeIn the third phase we use the balancing market size and the trained agents’ biddings to evaluate market price evolution by performing a statistically significant number of simulations. In these simulations, each agent can place bids, both for positive (upward market) or negative (downward market) balancing needs. This data is produced throughout the day at fixed intervals on a geo-referenced grid; for the Italian balancing market, the bids are accepted each 15 minutes. Typical simulation outputs in the upward and the downward electricity balancing market are:In A significant result of our approach is the forecast of the detailed contribution of each primary energy source to the downward and upward electricity balancing market. In The use of renewable energy sources is creating a new energy market where it is of the utmost importance to be in condition to anticipate trends and needs from users and producers to reduce inefficiencies in energy management and optimize production. The future transformation of the traditional passive distribution network into a pro-active one is requiring the implementation of an energy system where production and power fluctuations can be efficiently managed. In particular, power fluctuations have the strongest impact on markets and on short-time energy-continuity requirements.Previous research on short time energy forecasting concentrates on next-day electricity prices, showing that the analysis of time-series yields accurate and efficient price-forecasting tools when using dynamic regression and transfer function models  or ARIMASince wind power is possibly the most erratic renewable source, it has been the focus of most investigations into short-time fluctuations. The analysis of possible evolutions in optimal short-term wind energy balancing highlights the needs for managing reserves through changes in market scheduling (higher and more regular) and in introducing stochastic planning methods as opposed to deterministic ones . In 23]23], togeIn this paper we model both the electric energy flows and the very short-term market size taking into account the variability of renewable energy generation and customer demands through a stochastic approach. Network and ramping constraints are explicitly taken into account through the AC power-flow model while market price prediction is modelled through an agent-based simulation of energy operators. The inputs of the model are the day-ahead prices and sizes, quantities that are possible to successfully predict , 18. Ourwhat-if” analysis of the energy planning. An important direction for our model to develop would be a deeper understanding and modelling of fluctuations. In fact, the probability-distribution of fluctuations in energy production has different statistics depending on the renewable type. Moreover, both spatial and temporal correlations among the fluctuations should be taken into account: as an example, weather-influenced fluctuations—like the ones from wind and solar generators—display naturally a cross correlation among nearby located sources; on the same pacing, the non-instantaneous character of weather variations also induces temporal correlations. Though our analysis stems from a theoretical approach to understanding the effect of stochastic components in an interconnected system, it has immediate practical implications since the computational burden of our method is compatible with the scheduling time of the balancing market, permitting the potential use of this software for “on-the-fly” decision support.In the current phase of transition from a centralised to a distributed generation system, our approach allows us to address the complex task of estimating the additional cost associated with the balancing of renewable energy sources. This evaluation allows us to better understand the real impact of green sources in diminishing the carbon footprint, since balancing—in absence of a well-developed technology of energy storage—still relies heavily on conventional generators. Moreover, by comparing the current situations with novel scenarios where new generators (nodes in the model) are introduced, our approach allows for a detailed geo-localised “what-if” analysis aimed at understanding how the introduction of new rules and policies affects the market. In fact, it has been shown that regulatory intervention affects—using cash-out arrangements—not only spot price dynamics, but also price volatility (i.e. fluctuations)  is an experimental parameter that assign a different weight to played and non-played actions.Agent update: Market outcomes are communicated to each agent, that updates his propensities in relation to the profit made in the session. Agents propensities at iteration To the best of our knowledge, Roth-Erev algorithms have been always applied by training agents over historical data. In this paper we overcome the need of historical data by training the agents on realistic system states that are synthetically generated.S1 Fig(TIF)Click here for additional data file.S2 FigNotice that the couplings among the electric network and the electricity market must be taken into account during the simulation.(TIF)Click here for additional data file.


The textual content of the ShARe/CLEF  and i2b2 (https://i2b2.org/NLP/DataSets/) corpora needs to be requested with the individual corpus providers.Electronic health records and scientific articles possess differing linguistic characteristics that may impact the performance of natural language processing tools developed for one or the other. In this paper, we investigate the performance of four extant concept recognition tools: the clinical Text Analysis and Knowledge Extraction System (cTAKES), the National Center for Biomedical Ontology (NCBO) Annotator, the Biomedical Concept Annotation System (BeCAS) and MetaMap. Each of the four concept recognition systems is applied to four different corpora: the i2b2 corpus of clinical documents, a PubMed corpus of Medline abstracts, a clinical trails corpus and the ShARe/CLEF corpus. In addition, we assess the individual system performances with respect to one gold standard annotation set, available for the ShARe/CLEF corpus. Furthermore, we built a silver standard annotation set from the individual systems’ output and assess the quality as well as the contribution of individual systems to the quality of the silver standard. Our results demonstrate that mainly the NCBO annotator and cTAKES contribute to the silver standard corpora (F1-measures in the range of 21% to 74%) and their quality (best F1-measure of 33%), independent from the type of text investigated. While BeCAS and MetaMap can contribute to the precision of silver standard annotations (precision of up to 42%), the F1-measure drops when combined with NCBO Annotator and cTAKES due to a low recall. In conclusion, the performances of individual systems need to be improved independently from the text types, and the leveraging strategies to best take advantage of individual systems’ annotations need to be revised. The textual content of the PubMed corpus, accession numbers for the clinical trials corpus, and assigned annotations of the four concept recognition systems as well as the generated silver standard annotation sets are available from  Despite improvements in technology, the underlying molecular mechanisms for approximately half of the recognised human genetic disorders, are unknown . One of normalisation, or concept recognition in the case of normalising to ontological concepts.Ongoing research is traditionally published in scientific journals, including advances with respect to diseases, disease mechanisms and treatment opportunities . FurtherSeveral different methods are used to identify facts from textual data covering basic dictionary approaches as well as complex machine learning systems. With the differences in methods, we experience a variance in the adaptability to and the performance in a particular domain of each of the individual methods. In order to verify the different methods and provide a means of comparison, large text collections (‘corpora’) are needed that are annotated with respect to the information that is to be extracted by automated means. Examples for corpora include the Colorado Richly Annotated Full Text (CRAFT) corpus , the Penhttps://www.nlm.nih.gov/bsd/pmresources.html) with entities that are relevant to the medical domain, e.g. drugs, and protein and gene names. While the project delivered an approach for the generation of silver standard annotations  is annotated with muscle wasting  and decreased muscle tone . Due to the expression being split into several parts and scattered across the sentence, concept recognition tools fail to assign the correct annotations.Coordination of terms: An additional cause for missing and incorrect annotations in the SSC is the case of the coordination of terms. Terms are coordinated using lists and connectors such as and or or. A coordinated term such as abdomen soft, non-tender, non-distended refers to two separate annotations in the gold standard: abdomen soft (CUI:C0426663) and abdomen non-distended (CUI:C0424826). Term coordination is a known issue that has been addressed in existing entity tagging pipelines but none of the systems employed here deals well with the issue. This issue could be solved with adding additional preprocessing before annotating the text sources and building a silver standard.Ambiguity/lack of context-dependent synonyms: The last area for incorrect and missing annotations is the ambiguity of terms as well as the lack of context-dependent synonyms. A text span such as heroin abuse is annotated with heroin dependence/addiction (CUI:C0019337) in the gold standard. Neither of the systems was able to infer this annotation from the provided text and context in the original text source.Some of these problematic areas can be addressed in future work by adding appropriate pre-processing methodology into the SSC creation pipeline, e.g. resolving short forms or dealing with coordination. For other areas, however, more work is required still to find adequate solutions, especially the lack of context in clinical documentation as well as the complex nature of phenotype descriptions.In an earlier study , RebholzUsing four established concept recognition systems and a standard method to build a SSC for phenotype-related concepts reaches in the best case a F1-measure of 33% if only NCBO annotator and cTAKES are used for annotations. Even if four systems are combined, the obtained SSC is limited to mostly annotations of these two concept recognition systems. However, the best precision is achieved when combining MetaMap and BeCAS. While performance can be improved by adding pre-processing steps to the overall pipeline, the performance of the individual concept recognition systems needs to be improved. More consistent annotations across the four systems are required in order to be able to harvest these annotations for an automatically generated, high quality reference corpus for phenotype and disease-related concepts. Furthermore, the leveraging strategy for the output from the individual systems needs to be revised and adapted with respect to the domain of phenotypes and disease-related concepts.In this study, we used four different corpora (further explained in the following paragraphs) to build and assess the quality of an SSC generated by the application of four concept recognition systems and a standard leveraging strategy . As indiAnatomical Abnormality and Sign or Symptom, which are further summarised into semantic groups. In this study, we focus on CUIs and semantic types for the creation of the SSCs and the different evaluation strategies.To represent phenotypes and disease-related concepts in each of the corpora, we used the UMLS. The UMLS Metathesaurus forms the core of the UMLS and incorporates over 100 source vocabularies including the NCBI taxonomy  and SNOMTo evaluate the quality of the obtained SSC and provide a reference for the assessment as to which combination of systems achieves the highest quality of a SSC, we used the ShARe/CLEF corpus. The ShARe/CLEF corpus provides a gold standard annotation set based on UMLS’ CUIs.i2b2:https://i2b2.org/NLP/DataSets) consists of 693 clinical reports, made available under a restricted license by Partners HealthCare. The experiments described in this paper have been carried out on the complete 2010 Relations Challenge corpus . Reports consist of a series of section headings such as HISTORY OF PRESENT ILLNESS, ALLERGIES, followed by the actual description. The description ranges from a set of bullet points such as previous medication, to short descriptive enumerations such as findings at the clinical investigation, and finally, to longer free form phrases which are usually explanatory notes on the hospital course or the social history. This aspect is particularly important, because it may raise segmentation as well as tokenization challenges for any tool that relies on sentence splitting as a pre-processing step. We notice also that the length of the i2b2 texts is characterised by significant variation from the mean of 904 tokens.The i2b2 corpus . The overlap between the two corpora is 8,818 unique tokens, i.e., 24.69% of the PubMed corpus and 28.72% of the i2b2 corpus.Our PubMed corpus consists of 2,163 Medline abstracts and was retrieved by querying PubMed for the keyword Clinical trials corpus:http://clinicaltrials.gov/ using the keyword phenotype, since symptom would be too common in this collection. An interesting finding of the clinical trials corpus is its large token/uniqueness ratio of 12.94, compared to 1.60 in PubMed. This entails a high degree of repetition and a fairly restricted and uniform vocabulary of the language used within them. The overlap between the two corpora in terms of unique tokens is around 30%, i.e. 11,216 tokens.The clinical trials corpus consists of clinical trials downloaded from ShARe/CLEF corpus:https://sites.google.com/site/shareclefehealth/data) of 300 de-identified clinical records from the MIMIC II database with stand-off annotations for disorders. This is a mixed corpus that includes discharge summaries, echo reports and radiology reports used in an intensive care unit setting. 200 notes were designated for training and 100 for testing. Annotation was done by two annotators plus open adjudication. Access to the corpus required appropriate registration with MIMIC II and the completion of a US human subjects training certificate. In this study, we used only the 100 training documents, out of which one of the documents was empty. As can be seen in As a forth text corpus, we chose to use the ShARE/CLEF e-health 2013 Task 1 evaluation data set (Disease or syndrome and Sign or Symptom), but five groups are only represented with one concept.Out of the four corpora applied here, this corpus is the only one that possesses a gold standard annotation set. The gold standard annotation set includes 7,076 annotations in total: 5,351 that are mapped to a CUI , 1,723 that cannot be mapped to a UMLS CUI, and two that cannot be found in the text. The 5,351 CUIs fall into 15 semantic groups : NCBO annotator being a universal concept recognition tool for a broad range of ontologies, cTakes developed for the analysis of electronic health records using SNOMED CT and the RxNORM subset of UMLS, BeCAS designed to analyse the scientific literature for a number of concept types such as diseases and chemical entities, and MetaMap to annotate any text with concepts from the UMLS.NCBO annotator:http://bioportal.bioontology.org/annotator) is an online system that identifies and indexes biomedical concepts in unstructured text by exploiting a range of over 300 ontologies in the UMLS and NCBO BioPortal [The NCBO annotator , tokenization, lexical normalisation , POS tagging and shallow parsing using OpenNLP trained in-domain on Mayo Clinic EHRs, concept recognition, negation detection using NegEx [cTAKES from Mayo Clinic consists of a staged pipeline of modules that are both statistical and rule-based. The order of processing is somewhat similar to MetaMap and consists of the following stages: sentence boundary detection with OpenNLP (ng NegEx  and tempng NegEx  subset oBeCAS:http://bioinformatics.ua.pt/becas) [BeCAS (t/becas)  from thet/becas) , a depent/becas)  and the t/becas) . During MetaMap:http://metamap.nlm.nih.gov/) [MetaMap (ih.gov/)  is a widih.gov/)  and shalih.gov/) . String sentence-level and exact) and one inclusion rule. The inclusion rule determines the annotations that will be included in the silver standard based on a given matching technique. Rebholz-Schuhmann et al. [The annotation process described in the previous section resulted in an individual corpus-specific set of annotations produced by each of the four systems. In order to create silver standard versions of our four corpora, we used two matching techniques , cTAKES (blood pressure), BeCAS  and MetaMap (patients with chronic conditions). For brevity, we have not included the annotated CUIs. An ideal situation would lead to an exact match between the annotations produced by a pair of systems – for example, blood pressure annotated by NCBO annotator and cTAKES. Consequently, blood pressure would be included within the silver standard based on either exact or a sentence-level matching, while quality of life is included in the sentence-level SSC in addition.The second component of this generation process is the matching technique, which determines the degree of alignment between a pair of annotations. In our study, we used two different matching techniques: exact and sentence-level. In the case of the exact comparison, an entity was considered to be a true positive (TP) if the CUI provided by the system is identical with the silver standard annotation and, at the same time, falls into exactly the same location. If an annotation does not match both criteria, it is assumed to be a false positive (FP). Due to the systems varying in text spans, we also introduced a more relaxed evaluation (sentence-level) by means that any annotation that possesses the correct CUI and falls into the same sentence as the one contained in the silver standard, is counted as a true positive (TP) while all other annotations are regarded as false positives (FP). To assess the performance of the individual systems, we calculated the precision P The performance measures were calculated with two different matching techniques for the location of the entities: For the ShARe/CLEF corpus, a gold standard annotation set was available, allowing the assessment of the quality of the generated SSC as well as the performance of the individual systems. Even though we could not compare the other three silver standard corpora to a gold annotation set, the comparison of the silver standard to the gold standard can highlight general problems with the annotation and combination strategies applied here that are transferable across corpora.We compared the performance of the four different systems and the quality of the silver standard annotations by calculation precision, recall and the harmonised f-measure. The evaluation procedure was kept identical to the evaluation of the individual systems against the silver standard to allow for comparability of the different results.To assess the contribution of the individual concept recognition systems to the quality of the resulting silver standard corpora, we conducted a reduction experiment on the ShARe/CLEF data. The experiment was set-up to incrementally lower the number of contributing systems and assess all possible combinations of systems. The number of systems included varied from two to four. The overall voting rules for the generating of the SSC were maintained even though the number of systems was reduced. Each obtained SSC was then compared to the GS annotation set to determine the most valuable combination of systems with respect to generating a GS with the applied inclusion rule and matching techniques.exact as well as sentence-level basis. In the case of the exact measurements (designated P(E), R(E), and F(E)), the CUI of the GS has to be matched in exactly the same text span by the SSC. In the case of the sentence-level matching, the entity CUI provided by the GS needs to be contained within the annotation set of the corresponding sentence of the SSC.The performance measures calculated were, as in previous settings, precision, recall and F1-measure. We calculated these measures on an


The objective is to study this interplay to better understand and interpret the results obtained with a non-contact tonometry test. A patient-specific finite element model of a healthy eye, accounting for the load free configuration, was used. The corneal tissue was modeled as an anisotropic hyperelastic material with two preferential directions. Three different sets of parameters within the human experimental range obtained from inflation tests were considered. The influence of the IOP was studied by considering four pressure levels (10–28 mmHg) whereas the influence of corneal thickness was studied by inducing a uniform variation (300–600 microns). A Computer Fluid Dynamics (CFD) air-jet simulation determined pressure loading exerted on the anterior corneal surface. The maximum apex displacement showed a linear variation with IOP for all materials examined. On the contrary, the maximum apex displacement followed a cubic relation with corneal thickness. In addition, a significant sensitivity of the apical displacement to the corneal stiffness was also obtained. Explanation to this behavior was found in the fact that the cornea experiences bending when subjected to an air-puff loading, causing the anterior surface to work in compression whereas the posterior surface works in tension. Hence, collagen fibers located at the anterior surface do not contribute to load bearing. Non-contact tonometry devices give useful information that could be misleading since the corneal deformation is the result of the interaction between the mechanical properties, IOP, and geometry. Therefore, a non-contact tonometry test is not sufficient to evaluate their individual contribution and a complete  The shape of the cornea is the consequence of the equilibrium between its mechanical structure and the forces acting upon it. The mechanical behavior of the cornea depends on its geometry  and material properties, which in-turn relies on the microstructure of the stroma. The combination of high-speed photography (Scheimpflug imaging) of corneal images and dynamic bidirectional applanation technologies has been recently proposed as a new potentially useful method for evaluating the mechanical behavior of the cornea ,2. Theseρ = -0.360, p<0.0001), applanation time  and applanation velocity . Unfortunately, they did not report any correlation of corneal central thickness (CCT) with the deformation amplitude of the cornea. In a recent review, Roberts  describes the level of dispersion along fiber directions. A value of k = 0 implies that fibers are perfectly aligned (no dispersion), whereas k = 1/3 indicates that fibers are randomly distributed and the material behaves isotropically. Equation , intermediate  and large  stiffness, were considered in our simulations . These sThe viscoelastic behavior of the tissue was neglected since a very fast applied load, as the case of the air-puff, will result in an almost pure elastic response during the loading , and corThe sclera was considered as an isotropic hyperelastic material  and was ε), a new initial configuration is computed  IOP, ii) corneal thickness, and iii) material behavior (stiffness), on the maximum corneal displacement. Numerical simulations have been performed on the finite element software ABAQUS (Dassault Systemes), using a conventional personal computer  requiring a computation time of approximately 45 minutes to perform a full simulation. Visualizations of the results carried out with the software ParaView  .This fact is better demonstrated in σ>0, λ>1) due to the effect of the IOP. However, during the air-pulse, the state of stress in the anterior surface changes from a traction state to a compression state . A similar conclusion was stated in the experimental study conducted by Kling and Marcos [According to our simulations, the maximum displacement of the apex due to the air pulse varies linearly with IOP for all corneal stiffness considered, with the largest displacement corresponding to the lowest IOP value. This result was consistent with previous results , where ad Marcos . Hence, a-priori, e.g. Cornea’s stiffness.Figs. As shown in It should also be pointed out that, when the cornea is under the action of the IOP, the state of stress of the cornea corresponds to a pure traction membrane state, which means that the full cornea works in tension when it is subjected to its physiological IOP (i.e. no bending effects exists and it behaves as expected according to the shells and laminates theory), as shown in p<0.0001). Numerical results from our study also suggest this. Our results show a cubic relationship between the maximum apical displacement and the corneal thickness. This cubic dependence obeys to the bending deformation induced in the cornea during the action of the air-pulse, as expected in a thin shell subjected to bending. This cubic dependency helps to explain the increment in corneal displacement on patients that have undergone LASIK surgery and whose cornea has suffered a significant reduction of thickness and curvature. A similar situation is found in patients with narrow diseased corneas affected by ectasia.In addition to the corneal stiffness and IOP, the clinical study by Huseynova et al  reportedHence, the corneal response to an air puff is influenced by the mechanical properties of the cornea, the IOP, and topology . Therefore, analysis based on the evaluation of corneal response to an air pulse pressure, provides a response of the combined contribution of these effects, without being able to uncouple the precise contribution of each factor. By this, the corneal mechanical properties cannot be assumed to be directly related to the parameters defining the corneal response to the air pulse. This fact has been also demonstrated by Glass et al  who havein-silico methodology to a larger set of healthy and pathological patients in order to determine the impact of patient-to-patient geometric variability and IOP on maximum corneal displacements and other proposed mechanical biomarkers.A final comment is devoted to the limitation of this study. Corneal material has been assumed as hyperelastic, neglecting the intrinsic viscoelastic behavior of the tissue. However, since we were only interested in the maximum apex displacement, attained during the pressure rising phase of the air puff, and taking into account that a very fast load will result on an almost pure elastic response , it can in-silico methodology allows computing a sensitivity analysis of the mechanical properties of the corneal tissue, the IOP and the geometry of the cornea on the corneal deformation of patient specific geometric eye models. This type of analysis is not possible with standard non-contact tonometry devices since it has been demonstrated that they measure the combined contribution of all these factors on the corneal response. Thus, a cornea with high stiffness and low IOP may show the same deformation response as a cornea with low stiffness and high IOP. In addition, systems based on non-contact tonometry for characterizing the corneal biomechanics evaluates the mechanical response of the cornea under bending, whereas the corneal response to variations of the IOP depends on a pure membrane behavior of the cornea, a condition that is only achieved in biaxial or inflation loading. These results indicate that a complete in-vivo corneal mechanical characterization would require more than one test in order to determine the membrane and bending behavior of the cornea independently.In conclusion, the proposed


Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved . The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices. In many clinical applications, accurate measurements of hand movements and/or postures are required ,2. A dev® model  CG1801 ). All computations were conducted using a custom MATLAB program .The transformation matrix, T, was applied to the coordinates of each 3D point of the hand surface  and 36 orientations. The candidate orientations were set at −90° to 90° in five-degree increments. For a single candidate location, an intersection plane, intS, was defined that intersects with the candidate position, is directed along the candidate orientation, and is placed normal to the x–y plane. The 3D hand-surface data points intersecting with intS were defined as the points that were within 0.15 mm from intS. An illustration of deriving the curve along the hand surface is shown in After the transformation, the curve along the hand surface was derived for 44 candidate positions . The radius of the best-fit circle was defined as the radius of curvature of the sensor. The first point and end point of the trimmed curve was connected to the center of the best-fit circle, and the angle made by these lines was considered the bending angle of the sensor. When the radius of the best-fit circle exceeded a preset threshold (60 mm), sensor output was considered to be 0 V.The degree of deformation of the bending sensor was computed from the hand surface data and the sensor outputs were simulated from the deformed shape. From the estimated shape of the sensor, the sensor output was estimated by deriving the radius of curvature and the bending angle of the sensor. In order to derive the radius of curvature and bending angle of the sensor placed on a certain location, the curve along the hand surface exceeding the length of the two-inch Bend Sensor®, the sensor output with respect to the bending angle and the radius of curvature was modeled using Equation (3). The sensor output has a linear relationship with the bending angle and radius of curvature. The contribution of the radius of curvature to the sensor output is negligible when the radius of curvature exceeds 60 mm. V: Estimated sensor output, θ: Bending angle, and r: Radius of curvature.Through testing of the two-inch Bend SensorFor each candidate location on the hand surface, 45 sensor outputs were estimated, as there were 45 sets of 3D hand surface data with different thumb postures. The 45 sensor outputs were plotted with respect to the CMC-joint flexion and abduction angle, derived from the definition introduced in x, y) with i = 1; minimizing sensor sensitivity to other movement is i = 2; minimizing normalized RMSE is i = 3. Least squares linear regression to determine the slope of the curve was performed to correlate sensor outputs with CMC-joint angles (abduction or flexion angle), and the magnitude of the slope was determined. The magnitude of the slope represents the sensitivity of the sensor with respect to the corresponding CMC-joint angle. In order to find the optimal location of the CMC-joint angle sensor, the sensitivity to the targeted CMC-joint movement (abduction or flexion) should be maximized while the sensitivity to the other CMC-joint movement (flexion or abduction) should be minimized. The normalized root mean square error (RMSE) of the linear regression for the sensor output with respect to the targeted movement was also determined. Minimization of the normalized RMSE, minimizes crosstalk. The normalization was performed with respect to the variation of the sensor output and the CMC-joint angle. The magnitude of the slope and the normalized RMSE of the linear regression model were used as parameters for the cost functions shown in Equations (4) and (5): abJ and flexJ, at which the sensitivity to the targeted CMC-joint movement is maximized while the crosstalk with respect to the other CMC-joint movement is minimized. The weightings were set as w1 = 20, w2 = 1, and w3 = 5, as the most important factor in the cost function was to maximize the sensor sensitivity with respect to the targeted movement. The representative sensor response result with the CMC-joint-angle sensor placed at the optimal location is illustrated in The optimal sensor locations of the CMC-joint abduction sensor and CMC-joint flexion sensor were derived from the location that minimized the cost functions, x position and y position was normalized by the length of The optimal locations of the CMC-joint angle sensors (abduction and flexion sensors) were determined for ten subjects, and the average locations are illustrated in ectively a that weectively . In the versus target joint angle. A conceptual graph  derived from the 3D hand surface data when the sensor is placed in the optimal location. Representative plots are shown in al graph  illustrai.e., normalized area = 0), the sensor output will map to the target joint angle following a certain function . Therefore, minimizing the normalized area is important to achieve a truly decoupled measurement of CMC-joint angle.In an ideal case, where there is no variability in sensor output at a fixed CMC-joint angle combination (flexion and abduction angle), the signal of the sensor for the measurement of the targeted CMC-joint angle (flexion or abduction angle) will be only disturbed and variate by the other CMC-joint angle (abduction or flexion angle) movement. It is important to have a smaller normalized area to minimize crosstalk. If the sensor does not have any crosstalk with the other joint motion  also includes noise present in sensor output and noise present in the surface contour obtained from 3D scanning. However, the effects of such noise/uncertainty on the overall variability of the sensor output are much smaller than those from potential crosstalk. For example, the standard deviation of CMC-joint angle from surface data derived from a single hand was 2.2°. If we assume that the degree of variation remains similar across all postures, the normalized area due to measurement noise would be 0.136, much smaller than the majority of normalized areas from the simulation results (~0.7). Given the relative magnitudes of these sources of variability, we can consider crosstalk from the untargeted sensor outputs the primary source of variability that accounts for the normalized area.The normalized areas  of the optimally-located CMC-joint abduction and flexion sensor for each subject are shown in  surface , the deg® . The flexible fabric strap was partially (either one or two ends of the strap) sewed on a glove structure, in order to fix the sensor at the optimal position, while reducing the strain effect delivered through the glove structure. The flexion sensor was placed at the single optimal location, in which the sensor pointed toward the CMC-joint and originated from the midpoint of the third metacarpal. The abduction sensor was placed at two optimal locations: Location 1 across the index metacarpal and Location 2 across the adductor pollicis . The circumduction motion was selected in order to collect various CMC-joint abduction and flexion angle combinations. The marker positions and sensor outputs were collected using a Vicon motion capture system  consisting of eight T-series cameras and Giganet DAQ box . The CMC-joint angles were calculated using a custom MATLAB program. Four male subjects (age range: 22–35 years) consented and participated in the experiment. None of them were chosen from the pool of the ten subjects who participated in the experiment in the previous section because we wanted to check how the optimal sensor locations apply to the other subjects. Obviously, the sensing error can be minimized by customizing sensor locations for individual users; however, individual customization might not be practical in typical applications. It might be reasonable to assume that small-, medium-, and large-size glove systems would be practical in final product design. For the evaluation experiment, we prototyped a medium size sensing system (width: 80–90 mm) and recruited subjects who fit in the range of medium size.After placing the sensors, reflective markers were placed on the hand as shown in Representative results of the sensor output with respect to the targeted CMC-joint angle (abduction and flexion angle) are shown in vs. target joint angle for each subject. The average normalized area of the abduction sensor, in the location with lower crosstalk, was 0.281, while the average normalized area for the flexion sensor was 0.279. Sensor hysteresis was quantified as 0.099 by testing the bending sensor through multiple bend-and-extend cycles. Discounting the hysteresis effects, the measured magnitude of crosstalk was similar to the simulated values, suggesting a high validity of the simulated results.Abduction sensor results suggest that the optimal abduction sensor location  was either one of the two previously determined optimal locations that are illustrated in blue lines in i.e., whether it is in the increasing phase or the decreasing phase). The accuracy of the estimations is expected to improve by compensating for the hysteresis effect.As this study focuses on the improvements made by placing the sensors in optimal locations, sensor calibration was performed in a simple manner. The calibration for the CMC sensors was conducted using the relationship between CMC-joint angles and sensor outputs  for CMC-joint measurement were determined using a novel systematic method that employed a 3D scanning technique. Our optimization-based simulation resulted in similar sensor locations for most subjects, while the specific position and orientation varied slightly across subjects. The optimally located flexion sensor originates from the middle of the dorsal hand and is oriented toward the CMC-joint. Interestingly, the optimal location/orientation of the abduction sensor showed two distinct trends. One was similar to that of the adductor pollicis muscle, while the other was placed across the second metacarpal. When the sensors were optimally placed, the magnitude of crosstalk with movements other than the targeted DOF was minimized, such that the movement of the targeted joint angle was the dominant effect on sensor output.While challenging to accurately measure using compact equipment, measurement of the thumb CMC-joint angle is important when estimating the thumb configuration in hand rehabilitation applications and in clinical assessment. In this study, the optimal locations of bending sensors  , additio®), the proposed methodology is general and could be extended to any other type of flexible sensors by considering sensor dynamics. Furthermore, the results of this study could be employed in the design of wearable robots for the hand, for which the use of an estimated thumb posture as a feedback output would be critical for the accurate control of motion.Although the optimal sensor locations were found for specific bending sensors (Bend SensorIn conclusion, the accurate hand sensing system enables more precise hand assessment as well as functional training of skillful hand tasks specifically during rehabilitation procedures. It can be applied to general training systems such as a virtual-reality based game applications. Moreover, the methodology provided in this study can be applied to enhance accuracy of other wearable sensing systems.