Filter neurons for specific optic flow patterns in the fly's visual systems

The control of locomotion in a given environment requires information about instantaneous self-motion. Visually oriented animals, including man, may gain such information by analyzing the momentary optic flow pattern generated over both eyes during relative movement between animal and environment. Optic flow patterns can be described by vector fields where each single vector indicates the direction and velocity of the local relative movement at a certain position within the visual field. An optic flow pattern depends upon a set of motion parameters, namely (i) the direction of gaze and (ii) the rotatory and (iii) translatory components of self-motion. The translatory flow vectors also depend an the distance between visual objects and the eyes. Therefore, optic flow fields contain valuable information about the 3D-layout of the surroundings and instantaneous self-motion (Koenderink and van Doorn, 1987). About 50 motion-sensitive, wide-field interneurons which are assumed to be' involved in locomotor control are located in the third visual neuropil (lobula plate) of the blowfly's (Calliphora erythrocephala) visual system (Hausen, 1993). The output of many direction-specific movement detectors (EMDS) with small receptive fields are spatially integrated in a retinotopic manner an the dendrites of these interneurons. Are such interneurons adapted to sense specific aspects of the momentary optic flow field? To address this question, we investigated the receptive field organization of 10 identifiable interneurons of the so called vertical-system (VS; Hengstenberg, 1982) in great detail. We recorded intracellularly from the VS-neurons to determine the spatial distribution of local preferred directions and motion sensitivities at 52 positions spaced equally over the ipsilateral visual hemisphere (for method see: Menzel and Hengstenberg, 1991; Krapp and Hengstenberg 1992). The resulting response fields of the VS-neurons (about 90 recordings) show striking similarities to optic flow fields generated by specific motions in space (Krapp and Hengstenberg, 1994). By applying an iterative least square formalism (Koenderink and van Doorn, 1987) to the response fields we calculated the optimal self-motion parameters (translatory and rotatory component) for each VS-neuron. These parameters describe an optic flow field that best fits the respective measured response field. To find out whether the VS-neurons are functionally tuned more to the translatory or to the rotatory component of self-motion we systematically varied the optimal motion parameters. The error between the measured response field and the calculated optic flow field increases if both the translatory and the rotatory component deviate from the optimal motion parameters. The increase in the error is almost the same if only the rotatory component is varied. In contrast, if the translatory component is varied and the rotatory component is kept optimal the increase in the error is considerably smaller. The analysis of the response fields of the VS-neurons leads to the following conclusion: the VS-neurons are functionally tuned to sense rotations around different horizontally aligned body axes. The neurons VS1-VS3 are optimized to sense optic flow fields generated during nose-up pitch. VS4-VS7 are filter neurons for counterclockwise roll and VS8-VS10 are adapted to rotations around an axis that lies between the pitch and roll axes. Thus, the signals of the VS-neurons could contribute directly to visual flight control and gaze stabilization

The significance of motivation in student-centred learning : a reflective case study

The theoretical underpinnings of student-centred learning suggest motivation to be an integral component. However, lack of clarification of what is involved in motivation in education often results in unchallenged assumptions that fail to recognise that what motivates some students may alienate others. This case study, using socio-cognitive motivational theory to analyse previously collected data, derives three fuzzy propositions which, collectively, suggest that motivation interacts with the whole cycle of episodes in the teachinglearning process. It argues that the development of the higherlevel cognitive competencies that are implied by the term, student-centred learning, must integrate motivational constructs such as goal orientation, volition, interest and attributions into pedagogical practices

The impact of climate change on incomes and convergence in Africa

© 2019 Elsevier Ltd Climate change is projected to detrimentally affect African countries’ economic development, while income inequalities across economies is among the highest on the planet. However, it is projected that income levels would converge on the continent. Hitherto there is limited evidence on how climate change could affect projected income convergence, accelerating, slowing down, or even reversing this process. Here, we analyze convergence considering climate-change damages, by employing an economic model embedding the three dimensions of risks at the country-level: exposure, vulnerability and hazards. The results show (1) with historical mean climate-induced losses between 10 and 15 percent of GDP per capita growth, the majority of African economies are poorly adapted to their current climatic conditions, (2) Western and Eastern African countries are projected to be the most affected countries on the continent and (3) As a consequence of these heightened impacts on a number of countries, inequalities between countries are projected to widen in the high warming scenario compared to inequalities in the low and without warming scenarios. To mitigate the impacts of economic development and inequalities across countries, we stress (1) the importance of mitigation ambition and Africa's leadership in keeping global mean temperature increase below 1.5 °C, (2) the need to address the current adaptation deficit as soon as possible, (3) the necessity to integrate quantitatively climate risks in economic and development planning and finally (4) we advocate for the generalization of a special treatment for the most vulnerable countries to access climate-related finance. The analysis raises issues on the ability of African countries to reach their SDGs targets and the potential increasing risk of instability, migration across African countries, of decreased trade and economic cooperation opportunities as a consequence of climate change – exacerbating its negative consequences

The impact of climate change on incomes and convergence in Africa

© 2019 Elsevier Ltd Climate change is projected to detrimentally affect African countries’ economic development, while income inequalities across economies is among the highest on the planet. However, it is projected that income levels would converge on the continent. Hitherto there is limited evidence on how climate change could affect projected income convergence, accelerating, slowing down, or even reversing this process. Here, we analyze convergence considering climate-change damages, by employing an economic model embedding the three dimensions of risks at the country-level: exposure, vulnerability and hazards. The results show (1) with historical mean climate-induced losses between 10 and 15 percent of GDP per capita growth, the majority of African economies are poorly adapted to their current climatic conditions, (2) Western and Eastern African countries are projected to be the most affected countries on the continent and (3) As a consequence of these heightened impacts on a number of countries, inequalities between countries are projected to widen in the high warming scenario compared to inequalities in the low and without warming scenarios. To mitigate the impacts of economic development and inequalities across countries, we stress (1) the importance of mitigation ambition and Africa's leadership in keeping global mean temperature increase below 1.5 °C, (2) the need to address the current adaptation deficit as soon as possible, (3) the necessity to integrate quantitatively climate risks in economic and development planning and finally (4) we advocate for the generalization of a special treatment for the most vulnerable countries to access climate-related finance. The analysis raises issues on the ability of African countries to reach their SDGs targets and the potential increasing risk of instability, migration across African countries, of decreased trade and economic cooperation opportunities as a consequence of climate change – exacerbating its negative consequences

Arabidopsis Roots and Shoots Show Distinct Temporal Adaptation Patterns toward Nitrogen Starvation

Nitrogen (N) is an essential macronutrient for plants. N levels in soil vary widely, and plants have developed strategies to cope with N deficiency. However, the regulation of these adaptive responses and the coordinating signals that underlie them are still poorly understood. The aim of this study was to characterize N starvation in adult Arabidopsis (Arabidopsis thaliana) plants in a spatiotemporal manner by an integrative, multilevel global approach analyzing growth, metabolites, enzyme activities, and transcript levels. We determined that the remobilization of N and carbon compounds to the growing roots occurred long before the internal N stores became depleted. A global metabolite analysis by gas chromatography-mass spectrometry revealed organ-specific differences in the metabolic adaptation to complete N starvation, for example, for several tricarboxylic acid cycle intermediates, but also for carbohydrates, secondary products, and phosphate. The activities of central N metabolism enzymes and the capacity for nitrate uptake adapted to N starvation by favoring N remobilization and by increasing the high-affinity nitrate uptake capacity after long-term starvation. Changes in the transcriptome confirmed earlier studies and added a new dimension by revealing specific spatiotemporal patterns and several unknown N starvation-regulated genes, including new predicted small RNA genes. No global correlation between metabolites, enzyme activities, and transcripts was evident. However, this multilevel spatiotemporal global study revealed numerous new patterns of adaptation mechanisms to N starvation. In the context of a sustainable agriculture, this work will give new insight for the production of crops with increased N use efficiency

High precision measurement of the associated strangeness production in proton proton interactions

A new high precision measurement of the reaction pp -> pK+Lambda at a beam momentum of 2.95 GeV/c with more than 200,000 analyzed events allows a detailed analysis of differential observables and their inter-dependencies. Correlations of the angular distributions with momenta are examined. The invariant mass distributions are compared for different regions in the Dalitz plots. The cusp structure at the N Sigma threshold is described with the Flatt\'e formalism and its variation in the Dalitz plot is analyzed.Comment: accepted for publication in Eur. Phys. J.

First Model-Independent Measurement of the Spin Triplet pΛp\Lambda Scattering Length from Final State Interaction in the p⃗p→pK+Λ\vec{p}p \rightarrow pK^{+}\Lambda Reaction

The $\vec{p}p \rightarrow pK^{+}\Lambda$ reaction has been measured with the COSY-TOF detector at a beam momentum of $2.7\,\mathrm{GeV}/c$. The polarized proton beam enables the measurement of the beam analyzing power by the asymmetry of the produced kaon ($A_N^{K}$). This observable allows the $p\Lambda$ spin triplet scattering length to be extracted for the first time model independently from the final-state interaction in the reaction. The obtained value is $a_{t} = (-2.55 ^{+0.72}_{-1.39} {}_{\textrm{stat.}} \pm 0.6_{\textrm{syst.}} \pm 0.3_{\textrm{theo.}})\mathrm{fm}$. This value is compatible with theoretical predictions and results from model-dependent analyses.Comment: Revised version as accepted for publication in PR

Neuromorphometric characterization with shape functionals

This work presents a procedure to extract morphological information from neuronal cells based on the variation of shape functionals as the cell geometry undergoes a dilation through a wide interval of spatial scales. The targeted shapes are alpha and beta cat retinal ganglion cells, which are characterized by different ranges of dendritic field diameter. Image functionals are expected to act as descriptors of the shape, gathering relevant geometric and topological features of the complex cell form. We present a comparative study of classification performance of additive shape descriptors, namely, Minkowski functionals, and the nonadditive multiscale fractal. We found that the proposed measures perform efficiently the task of identifying the two main classes alpha and beta based solely on scale invariant information, while also providing intraclass morphological assessment