Race (human categorization) | EPFL Graph Search

Race is a categorization of humans based on shared physical or social qualities into groups generally viewed as distinct within a given society. The term came into common usage during the 16th century, when it was used to refer to groups of various kinds, including those characterized by close kinship relations. By the 17th century, the term began to refer to physical (phenotypical) traits, and then later to national affiliations. Modern science regards race as a social construct, an identity which is assigned based on rules made by society. While partly based on physical similarities within groups, race does not have an inherent physical or biological meaning. The concept of race is foundational to racism, the belief that humans can be divided based on the superiority of one race over another. Social conceptions and groupings of races have varied over time, often involving folk taxonomies that define essential types of individuals based on perceived traits. Moder

Aligning actions with objectives in endangered species recovery plans

Alex Tunas Corzon

To achieve conservation objectives for threatened and endangered species, managers must choose among potential recovery actions based on their efficacy. Yet, a lack of standardization in defining how conservation actions support recovery objectives can impede action efficacy and inhibit the efficient allocation of resources across species and projects. It is especially difficult to evaluate the effectiveness of actions in U.S. Endangered Species Act (ESA) recovery plans due to variation in how actions are described across different plans. To address this issue, we examined our ability to apply the internationally supported Conservation Measures Partnership (CMP) taxonomy to categorize existing ESA recovery plan action descriptions. Using ESA listed species in Arizona as a case study, we tested the feasibility of assigning CMP taxonomy categories to actions detailed in current recovery plans, and then used our assigned categories to assess the distribution of action categories. Pairs of researchers categorized and then compared levels of agreement between categories of recovery actions for 840 actions across 31 active recovery plans. Paired categorizations diverged for many of these actions, though confidence in action description assignments among pairs was highest in categorizing Research and Monitoring actions, which represented, on average, 53% (SD 0.9%) of actions with researcher agreement, and, on average, 42% (SD 0.08%) of classification among individual researchers. These results suggests that categorizable action descriptions most often correspond with Research and Monitoring objectives, and that other categories of actions required to delist species may be underrepresented in ESA recovery plans. We provide recommendations to support the application of the CMP taxonomy to current and future ESA recovery action descriptions using existing processes within the U.S. Fish and Wildlife Service. Our recommendations provide a roadmap for standardizing the description of recovery actions to improve decision-support for ESA-listed species.

WILEY2021

Dynamic Perception after Visually Guided Grasping by a Human-Like Autonomous Robot

Kuniaki Noda, Mototaka Suzuki

We will explore dynamic perception following the visually guided grasping of several objects by a human-like autonomous robot. This competency serves for object categorization. Physical interaction with the hand-held object gives the neural network of the robot the rich, coherent and multi-modal sensory input. Multi-layered self-organizing maps are designed and examined in static and dynamic conditions. The results of the tests in the former condition show its capability of robust categorization against noise. The network also shows better performance than a single-layered map does. In the latter condition we focus on shaking behavior by moving only the forearm of the robot. In some combinations of grasping style and shaking radius the network is capable of categorizing two objects robustly. The results show that the network capability to achieve the task largely depends on how to grasp and how to move the objects. These results together with a preliminary simulation are promising toward the self-organization of a high degree of autonomous dynamic object categorization.

2006

The interplay between human genetic variation, chronic inflammation and persistent infection: relevance for cardiovascular morbidity

Flavia Aurelia Shoko Hodel

Contemporary genomic approaches allow us to seek answers to biological questions that were previously out of reach. Genome-wide association studies (GWAS) have identified numerous genetic polymorphisms associated with human diseases, providing new insight into the genes and pathways involved in pathogenesis. The work presented in this thesis aimed to harness the power of large-scale genomics, statistical methods and bioinformatic tools to explore the interactions between persistent infections, chronic low-grade inflammation, and coronary heart disease (CHD). To achieve this, we used data collected from large population-based studies of individuals of European ancestry.To identify human genetic determinants of the humoral immune response against persistent or frequently recurring infections, with a special focus on human polyomaviruses, we performed GWAS and meta-analyses of serostatus and quantitative immunoglobulin G responses. We identified NFKB1 as a common locus associated with antibody response to multiple pathogens. For polyomaviruses, we found strong associations of HLA class II, FUT2, STING1, and MUC1 genetic variants with the intensity of the humoral response. Together, these results demonstrate the modulating contribution of host genetic variation to the individual response against some of the most prevalent human viruses.Even when they are latent, chronic infections can trigger some degree of local or systemic immune response, resulting in low-grade inflammation. In an effort to better understand the variability of humoral immune response and inflammation patterns in response to pathogen exposure, we found evidence for an association between Chlamydia trachomatis and Helicobacter pylori seropositivity, and higher plasma levels of C-reactive protein (CRP), a sensitive indicator of inflammation. High polygenic risk was also significantly associated with CRP levels, confirming that human genetic variation plays a modulating role in systemic inflammation. These results improve our understanding of the relationship between persistent infections and chronic inflammation, an important determinant of long-term morbidity in humans.Finally, we developed statistical models to explore the influences of genetic variation, persistent infections and low-grade inflammation on incident CHD. We identified high polygenic risk and Fusobacterium nucleatum infection as associated with an increased risk of developing CHD, in addition to conventional risk factors. These results confirm that CHD is a multicomponent disease that is caused by demographic, genetic and environmental factors. Moreover, they might allow for better identification of individuals at high risk for CHD and provide a rationale for future anti-infective prevention trials.Together, this research demonstrates that current genomic and serological technology, bioinformatic analysis and functional follow-up studies have the potential to provide new insight into the molecular basis of host-pathogen interactions, and their role in chronic diseases. From a translational perspective, the results of this project include new targets for diagnosis and therapeutic development, new disease biomarkers, and better predictive models. Every advance in the understanding of complex disease has the potential to improve genomic and clinical medicine, and I am pleased to have had the opportunity to act at different levels to participate in this much needed transition to precision medicine.