Biological anthropology

Summary

Biological anthropology, also known as physical anthropology, is a scientific discipline concerned with the biological and behavioral aspects of human beings, their extinct hominin ancestors, and related non-human primates, particularly from an evolutionary perspective. This subfield of anthropology systematically studies human beings from a biological perspective. Branches As a subfield of anthropology, biological anthropology itself is further divided into several branches. All branches are united in their common orientation and/or application of evolutionary theory to understanding human biology and behavior.

Bioarchaeology is the study of past human cultures through examination of human remains recovered in an archaeological context. The examined human remains usually are limited to bones but may include preserved soft tissue. Researchers in bioarchaeology combine the skill sets of human osteology, paleopathology, and archaeology, and often consider the cultural and

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https://en.wikipedia.org/wiki/Biological_anthropology

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Structural connectomics in brain diseases

Philipp Baumann, Alessandra Griffa, Patric Hagmann, Jean-Philippe Thiran

Imaging the connectome in vivo has become feasible through the integration of several rapidly developing fields of science and engineering, namely magnetic resonance imaging and in particular diffusion MRI on one side, image processing and network theory on the other side. This framework brings in vivo brain imaging closer to the real topology of the brain, contributing to narrow the existing gap between our understanding of brain structural organization on one side and of human behavior and cognition on the other side. Given the seminal technical progresses achieved in the last few years, it may be ready to tackle even greater challenges, namely exploring disease mechanisms. In this review we analyze the current situation from the technical and biological perspectives. First, we critically review the technical solutions proposed in the literature to perform clinical studies. We analyze for each step (i.e. MRI acquisition, network building and network statistical analysis) the advantages and potential limitations. In the second part we review the current literature available on a selected subset of diseases, namely, dementia, schizophrenia, multiple sclerosis and others, and try to extract for each disease the common findings and main differences between reports.

Elsevier2013

Natural and artificial societies often divide the workload between specialized members. For example, an ant worker may preferentially perform one of many tasks such as brood rearing, foraging and nest maintenance. A robot from a rescue team may specialize in search, obstacle removal, or transportation. Such division of labor is considered crucial for efficient operation of multi-agent systems and has been studied from two perspectives. First, scientists address the "how" question seeking for mechanical explanations of division of labor. The focus has been put on behavioral and environmental factors and on task allocation algorithms leading to specialization. Second, scientists address the "why" question uncovering the origins of division of labor. The focus has been put on evolutionary pressures and optimization procedures giving rise to specialization. Studies have usually addressed one of these two questions in isolation, but for a full understanding of division of labor the explanation of the origins of specific mechanisms is necessary. Here, we rise to this challenge and study three major transitions related to division of labor. By means of theoretical analyses and evolutionary simulations, we construct a pathway from the occurrence of cooperation, through fixed castes, up to dynamic task allocation. First, we study conditions favoring the evolution of cooperation, as it opens the doors for the potentially following specialization. We demonstrate that these conditions are sensitive to the mechanisms of intra-specific selection (or "selection methods"). Next, we take an engineering perspective and we study division of labor at the genetic level in teams of artificial agents. We devise efficient algorithms to evolve fixed assignments of agents to castes (or "team compositions"). To this end, we propose a novel technique that exchanges agents between teams, which greatly eases the search for the optimal composition. Finally, we take a biological perspective and we study division of labor at the behavioral level in simulated ant colonies. We quantify the efficiency of task allocation algorithms, which have been used to explain specialization in social insects. We show that these algorithms fail to induce precise reallocation of the workforce in response to changes in the environment. We overcome this issue by modeling task allocation with artificial neural networks, which lead to near optimal colony performance. Overall, this work contributes both to biology and to engineering. We shed light on the evolution of cooperation and division of labor in social insects, and we show how to efficiently optimize teams of artificial agents. We resolve the encountered methodological issues and demonstrate the power of evolutionary simulations to address biological questions and to tackle engineering problems.

EPFL2013

Temporal Super-Resolution Microscopy Using a Hue-Encoded Shutter

Sylvain Calinon, Christian Jaques, Michael Stefan Daniel Liebling, Emmanuel Pignat

Limited time-resolution in microscopy is an obstacle to many biological studies. Despite recent advances in hardware, digital cameras have limited operation modes that constrain frame-rate, integration time, and color sensing patterns. In this paper, we propose an approach to extend the temporal resolution of a conventional digital color camera by leveraging a multi-color illumination source. Our method allows imaging single-hue objects at increased frame-rate by trading spectral for temporal information (while retaining the ability to measure base hue). It also allows rapid switching to standard RGB acquisition. We evaluated the feasibility and performance of our method via experiments with mobile resolution targets. We observed a time-resolution increase by a factor 2.8 with a three-fold increase in temporal sampling rate. We further illustrate the use of our method to image the beating heart of a zebrafish larva, allowing the display of color or fast grayscale images. Our method is particularly well-suited to extend the capabilities of imaging systems where the flexibility of rapidly switching between high frame rate and color imaging are necessary.

2019

EPFL2013