Local Perceptions and Vertical Perspectives of a Large Scale Land Acquisition Project in Northern Sierra Leone

Despite increased scientific interest in the phenomenon of large-scale land acquisitions (LSLA), accurate data on implementation processes remain sparse. This paper aims at filling this gap by providing empirical in-depth knowledge on the case of the Swiss-based Addax Bioenergy Ltd. in Sierra Leone. Extensive fieldwork allowed the interdisciplinary research team 1) the identification of different actors that are necessary for the implementation on a vertical level and 2) the documentation of the heterogeneous group of project affected people’s perceptions and strategies on a horizontal level. Findings reveal that even a project labeled as best-practice example by UN agencies triggers a number of problematic processes for affected communities. The loss of natural resources that comes along with the land lease and the lack of employment possibilities mostly affects already vulnerable groups. On the other hand, strategies and resistance of local people also affect the project implementation. This shows that the horizontal and vertical levels are not separate entities. They are linked by social networks, social interactions, and means of communication and both levels take part in shaping the project’s impacts.

Dynamics of a local Alpine flooding event in October 2011: moisture source and large-scale circulation

Alpine heavy precipitation events often affect small catchments, although the circulation pattern leading to the event extends over the entire North Atlantic. The various scale interactions involved are particularly challenging for the numerical weather prediction of such events. Unlike previous studies focusing on the southern Alps, here a comprehensive study of a heavy precipitation event in the northern Alps in October 2011 is presented with particular focus on the role of the large-scale circulation in the North Atlantic/European region. During the event exceptionally high amounts of total precipitable water occurred in and north of the Alps. This moisture was initially transported along the flanks of a blocking ridge over the North Atlantic. Subsequently, strong and persistent northerly flow established at the upstream flank of a trough over Europe and steered the moisture towards the northern Alps. Lagrangian diagnostics reveal that a large fraction of the moisture emerged from the West African coast where a subtropical upper-level cut-off low served as an important moisture collector. Wave activity flux diagnostics show that the ridge was initiated as part of a low-frequency, large-scale Rossby wave train while convergence of fast transients helped to amplify it locally in the North Atlantic. A novel diagnostic for advective potential vorticity tendencies sheds more light on this amplification and further emphasizes the role of the ridge in amplifying the trough over Europe. Operational forecasts misrepresented the amplitude and orientation of this trough. For the first time, this study documents an important pathway for northern Alpine flooding, in which the interaction of synoptic-scale to large-scale weather systems and of long-range moisture transport from the Tropics are dominant. Moreover, the trapping of moisture in a subtropical cut-off near the West African coast is found to be a crucial precursor to the observed European high-impact weather.

Factor structure of the Bern Psychopathology Scale in a sample of patients with schizophrenia spectrum disorders.

BACKGROUND The Bern Psychopathology Scale (BPS) is based on a system-specific approach to classifying the psychopathological symptom pattern of schizophrenia. It consists of subscales for three domains (language, affect and motor behaviour) that are hypothesized to be related to specific brain circuits. The aim of the study was to examine the factor structure of the BPS in patients with schizophrenia spectrum disorders. METHODS One hundred and forty-nine inpatients with schizophrenia spectrum disorders were recruited at the Department of Psychiatry II, Ulm University, Germany (n=100) and at the University Hospital of Psychiatry, Bern, Switzerland (n=49). Psychopathology was assessed with the BPS. The VARCLUS procedure of SAS(®) (a type of oblique component analysis) was used for statistical analysis. RESULTS Six clusters were identified (inhibited language, inhibited motor behaviour, inhibited affect, disinhibited affect, disinhibited language/motor behaviour, inhibited language/motor behaviour) which explained 40.13% of the total variance of the data. A binary division of attributes into an inhibited and disinhibited cluster was appropriate, although an overlap was found between the language and motor behaviour domains. There was a clear distinction between qualitative and quantitative symptoms. CONCLUSIONS The results argue for the validity of the BPS in identifying subsyndromes of schizophrenia spectrum disorders according to a dimensional approach. Future research should address the longitudinal assessment of dimensional psychopathological symptoms and elucidate the underlying neurobiological processes.

Marginal lands or marginal people? Analysing key processes determining the outcomes of large-scale land acquisitions in Lao PDR and Cambodia

This chapter aims to overcome the gap existing between case study research, which typically provides qualitative and process-based insights, and national or global inventories that typically offer spatially explicit and quantitative analysis of broader patterns, and thus to present adequate evidence for policymaking regarding large-scale land acquisitions. Therefore, the chapter links spatial patterns of land acquisitions to underlying implementation processes of land allocation. Methodologically linking the described patterns and processes proved difficult, but we have identified indicators that could be added to inventories and monitoring systems to make linkage possible. Combining complementary approaches in this way may help to determine where policy space exists for more sustainable governance of land acquisitions, both geographically and with regard to processes of agrarian transitions. Our spatial analysis revealed two general patterns: (i) relatively large forestry-related acquisitions that target forested landscapes and often interfere with semi-subsistence farming systems; and (ii) smaller agriculture-related acquisitions that often target existing cropland and also interfere with semi-subsistence systems. Furthermore, our meta-analysis of land acquisition implementation processes shows that authoritarian, top-down processes dominate. Initially, the demands of powerful regional and domestic investors tend to override socio-ecological variables, local actors’ interests, and land governance mechanisms. As available land grows scarce, however, and local actors gain experience dealing with land acquisitions, it appears that land investments begin to fail or give way to more inclusive, bottom-up investment models.

Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

Large-scale dust jets in the coma of 67P/Churyumov-Gerasimenko as seen by the OSIRIS instrument onboard Rosetta

Context. During the most recent perihelion passage in 2009 of comet 67P/Churyumov-Gerasimenko (67P), ground-based observations showed an anisotropic dust coma where jet-like features were detected at similar to 1.3 AU from the Sun. The current perihelion passage is exceptional as the Rosetta spacecraft is monitoring the nucleus activity since March 2014, when a clear dust coma was already surrounding the nucleus at 4.3 AU from the Sun. Subsequently, the OSIRIS camera also witnessed an outburst in activity between April 27 and 30, and since mid-July, the dust coma at rh similar to 3.7-3.6 AU preperihelion is clearly non-isotropic, pointing to the existence of dust jet-like features. Aims. We aim to ascertain on the nucleus surface the origin of the dust jet-like features detected as early as in mid-July 2014. This will help to establish how the localized comet nucleus activity compares with that seen in previous apparitions and will also help following its evolution as the comet approaches its perihelion, at which phase most of the jets were detected from ground-based observations. Determining these areas also allows locating them in regions on the nucleus with spectroscopic or geomorphological distinct characteristics. Methods. Three series of dust images of comet 67P obtained with the Wide Angle Camera (WAC) of the OSIRIS instrument onboard the Rosetta spacecraft were processed with different enhancement techniques. This was made to clearly show the existence of jet-like features in the dust coma, whose appearance toward the observer changed as a result of the rotation of the comet nucleus and of the changing observing geometry from the spacecraft. The position angles of these features in the coma together with information on the observing geometry, nucleus shape, and rotation, allowed us to determine the most likely locations on the nucleus surface where the jets originate from. Results. Geometrical tracing of jet sources indicates that the activity of the nucleus of 67P gave rise during July and August 2014 to large-scale jet-like features from the Hapi, Hathor, Anuket, and Aten regions, confirming that active regions may be present on the nucleus localized at 60. northern latitude as deduced from previous comet apparitions. There are also hints that large-scale jets observed from the ground are possibly composed, at their place of origin on the nucleus surface, of numerous small-scale features.

Cerebellar mechanisms for motor learning: Testing predictions from a large-scale computer simulation

The cerebellum is the major brain structure that contributes to our ability to improve movements through learning and experience. We have combined computer simulations with behavioral and lesion studies to investigate how modification of synaptic strength at two different sites within the cerebellum contributes to a simple form of motor learning—Pavlovian conditioning of the eyelid response. These studies are based on the wealth of knowledge about the intrinsic circuitry and physiology of the cerebellum and the straightforward manner in which this circuitry is engaged during eyelid conditioning. Thus, our simulations are constrained by the well-characterized synaptic organization of the cerebellum and further, the activity of cerebellar inputs during simulated eyelid conditioning is based on existing recording data. These simulations have allowed us to make two important predictions regarding the mechanisms underlying cerebellar function, which we have tested and confirmed with behavioral studies. The first prediction describes the mechanisms by which one of the sites of synaptic modification, the granule to Purkinje cell synapses (gr → Pkj) of the cerebellar cortex, could generate two time-dependent properties of eyelid conditioning—response timing and the ISI function. An empirical test of this prediction using small, electrolytic lesions of the cerebellar cortex revealed the pattern of results predicted by the simulations. The second prediction made by the simulations is that modification of synaptic strength at the other site of plasticity, the mossy fiber to deep nuclei synapses (mf → nuc), is under the control of Purkinje cell activity. The analysis predicts that this property should confer mf → nuc synapses with resistance to extinction. Thus, while extinction processes erase plasticity at the first site, residual plasticity at mf → nuc synapses remains. The residual plasticity at the mf → nuc site confers the cerebellum with the capability for rapid relearning long after the learned behavior has been extinguished. We confirmed this prediction using a lesion technique that reversibly disconnected the cerebellar cortex at various stages during extinction and reacquisition of eyelid responses. The results of these studies represent significant progress toward a complete understanding of how the cerebellum contributes to motor learning. ^

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

Competition may explain the fine-scale spatial patterns and genetic structure of two co-occurring plant congeners

1. The spatial distribution of individual plants within a population and the population’s genetic structure are determined by several factors, like dispersal, reproduction mode or biotic interactions. The role of interspecific interactions in shaping the spatial genetic structure of plant populations remains largely unknown. 2. Species with a common evolutionary history are known to interact more closely with each other than unrelated species due to the greater number of traits they share. We hypothesize that plant interactions may shape the fine genetic structure of closely related congeners. 3. We used spatial statistics (georeferenced design) and molecular techniques (ISSR markers) to understand how two closely related congeners, Thymus vulgaris (widespread species) and T. loscosii (narrow endemic) interact at the local scale. Specific cover, number of individuals of both study species and several community attributes were measured in a 10 × 10 m plot. 4. Both species showed similar levels of genetic variation, but differed in their spatial genetic structure. Thymus vulgaris showed spatial aggregation but no spatial genetic structure, while T. loscosii showed spatial genetic structure (positive genetic autocorrelation) at short distances. The spatial pattern of T. vulgaris’ cover showed significant dissociation with that of T. loscosii. The same was true between the spatial patterns of the cover of T. vulgaris and the abundance of T. loscosii and between the abundance of each species. Most importantly, we found a correlation between the genetic structure of T. loscosii and the abundance of T. vulgaris: T. loscosii plants were genetically more similar when they were surrounded by a similar number of T. vulgaris plants. 5. Synthesis. Our results reveal spatially complex genetic structures of both congeners at small spatial scales. The negative association among the spatial patterns of the two species and the genetic structure found for T. loscosii in relation to the abundance of T. vulgaris indicate that competition between the two species may account for the presence of adapted ecotypes of T. loscosii to the abundance of a competing congeneric species. This suggests that the presence and abundance of close congeners can influence the genetic spatial structure of plant species at fine scales.

Use of Feynman diagrams in large-scale neural networks with nonlinear behaviour

A new proposal to the study of large-scale neural networks is reported. It is based on the use of similar graphs to the Feynman diagrams. A first general theory is presented and some interpretations are given. A propagator, based on the Green's function of the neuron, is the basis of the method. Application to a simple case is reported.

Large-Scale smart grids as system of systems

Smart Grids are advanced power networks that introduce intelligent management, control, and operation systems to address the new challenges generated by the growing energy demand and the appearance of renewal energies. In the literature, Smart Grids are presented as an exemplar SoS: systems composed of large heterogeneous and independent systems that leverage emergent behavior from their interaction. Smart Grids are currently scaling up the electricity service to millions of customers. These Smart Grids are known as Large-Scale Smart Grids. From the experience in several projects about Large-Scale Smart Grids, this paper defines Large-Scale Smart Grids as a SoS that integrate a set of SoS and conceptualizes the properties of this SoS. In addition, the paper defines the architectural framework for deploying the software architectures of Large-Scale Smart Grid SoS.