Middle Stone Age (MSA) site distributions in eastern Africa and their relationship to Quaternary environmental change, refugia and the evolution of Homo sapiens

This paper considers the evolution of Homo sapiens in eastern Africa in relation to refugia and bottlenecks around ~200 ka BP, at a macro scale. Middle Stone Age (MSA) lithics, site distributions and locations are analysed in relation to palaeovegetation maps of the last glacial/interglacial cycle, which are used as a proxy for earlier climate cycles. A ‘‘push and pull’’ model is then postulated for the spread of Homo sapiens out of refugia in eastern Africa, involving both volcanism (push) and habitat availability (pull). A date within OIS 5 is suggested for this expansion to other parts of the continent, and potentially further a?eld, contrary to a frequently proposed expansion within OIS 3. ©2008 Elsevier Ltd. All rights reserved.

ROLE OF LATERAL HYPOTHALAMUS ON FLUID, ELECTROLYTE, AND CARDIOVASCULAR-RESPONSES TO ACTIVATION OF THE MSA

In this study we investigated the influence of electrolytic lesion or of opioid agonist injections into the lateral hypothalamus (LH) on the dipsogenic, natriuretic, kaliuretic, antidiuretic, presser, and bradycardic effects of cholinergic stimulation of the medial septal area (MSA) in rats. Sham- and LH-lesioned male Holtzman rats received a stainless steel cannula implanted into the LH. Other groups of rats had cannulas implanted simultaneously into the MSA and LH. Carbachol (2 nmol) injection into the MSA induced water intake, presser, and bradycardic responses. LH lesion reduced all of these effects (1-3 and 15-18 days). Previous injection of synthetic opiate agonist, FK-33824 (100 ng), into the LH reduced the water intake, natriuresis, kaliuresis, and presser responses induced by carbachol injected into the MSA. These data show that both electrolytic lesion or injection of an opiate agonist in the LH reduces the fluid-electrolyte and cardiovascular responses to cholinergic activation of the MSA. The involvement of LH with central excitatory and inhibitory mechanisms related to fluid-electrolytic and cardiovascular control is suggested.

Improvements in the sensibility of MSA-GA tool using COFFEE objective function

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Occupational employment and wage estimates for Maine, statewide & Bangor Metropolitan Statistical Area (MSA), Maine; Lewiston-Auburn Metropolitan Statistical Area (MSA), Maine; Portland Metropolitan Statistical Area (MSA), Maine; Portsmouth-Rochester Primary Metropolitan Statistical Area (PMSA), New Hampshire (Portsmouth-Rochester PMSA, NH includes Kittery-York Labor Market Area, Maine); northeast balance of state, Maine; southwest balance of state, Maine.

Title from cover.

Multiple system atrophy (MSA): Topographic distribution of the alpha-synuclein-associated pathological changes

To study the topographic distribution of the pathology in multiple system atrophy (MSA). Pattern analysis was carried out using a-synuclein immunohistochemistry in 10 MSA cases. The glial cytoplasmic inclusions (GCI) were distributed randomly or in large clusters. The neuronal inclusions (NI) and abnormal neurons were distributed in regular clusters. Clusters of the NI and abnormal neurons were spatially correlated whereas the GCI were not spatially correlated with either the NI or the abnormal neurons. The data suggest that the GCI represent the primary change in MSA and the neuronal pathology develops secondary to the glial pathology.

A quantitative study of the pathological changes in ten patients with multiple system atrophy (MSA)

The densities of the glial cytoplasmic inclusions (GCI), neuronal inclusions (NI), and abnormal neurons were studied in the frontal cortex, hippocampus, cerebellum, basal ganglia and areas of the pons and medulla in 10 cases of multiple system atrophy (MSA). GCI density was greater in the substantia nigra and globus pallidus compared with the frontal cortex and hippocampus. Abnormal neurons were most abundant in the frontal cortex, substantia nigra, and inferior olivary nucleus. NI and abnormal neuron densities were positively correlated in the globus pallidus but negatively correlated in the hippocampus. The NI and GCI were only positively correlated in the pons. GCI in the pons and inferior olivary nucleus, NI in the substantia nigra, and abnormal neurons in the frontal cortex varied significantly between cases. The MSA cases did not cluster according to disease subtype. The data suggest that: 1) the greatest densities of pathological changes occur in the substantia nigra and globus pallidus, 2) density of the GCI is unrelated to that of the NI, and 3) there is overlapping pathology between the various subtypes of MSA.

Generative systems as relational bridges

Generative media systems present an opportunity for users to leverage computational systems to make sense of complex media forms through interactive and collaborative experiences. Generative music and art are a relatively new phenomenon that use procedural invention as a creative technique to produce music and visual media. These kinds of systems present a range of affordances that can facilitate new kinds of relationships with music and media performance and production. Early systems have demonstrated the potential to provide access to collaborative ensemble experiences to users with little formal musical or artistic expertise. This paper examines the relational affordances of these systems evidenced by selected field data drawn from the Network Jamming Project. These generative performance systems enable access to unique ensemble with very little musical knowledge or skill and they further offer the possibility of unique interactive relationships with artists and musical knowledge through collaborative performance. In this presentation I will focus on demonstrating how these simulated experiences might lead to understandings that may be of educational and social benefit. Conference participants will be invited to jam in real time using virtual interfaces and to view video artifacts that demonstrate an interactive relationship with artists.

Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.