Writing biology with mutant mice: the monstrous potential of post genomic life

Social scientific accounts identified in the biological grammars of early genomics a monstrous reductionism, ‘an example of brute life, the minimalist essence of things’ (Rabinow, 1996, p. 89). Concern about this reductionism focused particularly on its links to modernist notions of control; the possibility of calculating, predicting and intervening in the biological futures of individuals and populations. Yet, the trajectories of the post genomic sciences have not unfolded in this way, challenging scientists involved in the production and integration of complex biological data and the interpretative strategies of social scientists honed in critiquing this reductionism. The post genomic sciences are now proliferating points from which to understand relations in biology, between genes and environments, as well as between species and spaces, opening up future possibilities and different ways of thinking about life. This paper explores the emerging topologies and temporalities of one form of post genomic research, drawing upon ethnographic research on international efforts in functional genomics, which are using mutant mice to understand mammalian gene function. Using vocabularies on the monstrous from Derrida and Haraway, I suggest an alternative conceptualisation of monstrosity within biology, in which the ascendancy of mice in functional genomics acts as a constant supplement to the reductionist grammars of genomics. Rather than searching for the minimalist essence of things, this form of functional genomics has become an exercise in the production and organization of biological surplus and excess, which is experimental, corporeal and affective. The uncertain functioning of monsters in this contexts acts as a generative catalyst for scientists and social scientists, proliferating perspectives from which to listen to and engage with the mutating landscapes, forms of life, and languages of a post genomic biology

A Collaborative Process for Developing Map Symbol Standards

AbstractGeographic information is commonly disseminated and consumed via visual representations of features and their environmental context on maps. Map design inherently involves generalizing reality, and one method by which mapmakers do so is through the use of symbols to represent features. Here we focus on the challenges associated with supporting mapmakers who need to work together to reach consensus on standardizing their map symbols. Based on a needs assessment study with mapmakers at the U.S. Department of Homeland Security, we designed a new, mixed-method symbol standardization process that takes place through a web-based, asynchronous platform. A study to test this new standardization process with mapmakers at DHS revealed that our process allowed participants to identify many issues related to symbol design, meaning, and categorization. The approach elicited sustained, iterative engagement and critical thinking from participants, and results from a post-study survey indicate that participants found it to be useful and usable. Results from our study and user feedback allow us to suggest multiple ways in which our approach and platform can be improved for future applications

Frameworks for Component-based Simulation

AbstractThe need to reduce development costs of simulation models has led to recent efforts for setting simulation standards that foster model reuse and interoperability. Specifically, the High Level Architecture (HLA) is a new simulation standard supported by the US Defense Modeling and Simulation Office (DMSO). It has been adopted as the standard technical architecture for all US Department of Defense simulations. In the meantime, the commercial sector has had successful efforts in developing enabling technologies for distributed computing; namely, the Common Object Request Broker Architecture (CORBA) by the Object Management Group (OMG). CORBA is a large and complex set of specifications and protocols that utilizes the objectoriented paradigm to achieve distributed object-oriented computing environments that allow object interoperability and reuse. When used as an infrastructure for simulation model reuse and interoperability, both HLA and CORBA exhibit merits and limitations. Since HLA and CORBA were developed independently, need exists for a comparative evaluation of the two architectures as a basis for component-based simulation. In this paper, both HLA and CORBA are presented in the context of component-based simulation model development and interoperability. The two architectures are compared against four comparison criteria that are related to their conceptual foundation and design

Algorithms for advance bandwidth reservation in media production networks

Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results

AI-based analysis of super-resolution microscopy: Biological discovery in the absence of ground truth

The nanoscale resolution of super-resolution microscopy has now enabled the use of fluorescent based molecular localization tools to study whole cell structural biology. Machine learning based analysis of super-resolution data offers tremendous potential for discovery of new biology, that by definition is not known and lacks ground truth. Herein, we describe the application of weakly supervised learning paradigms to super-resolution microscopy and its potential to enable the accelerated exploration of the molecular architecture of subcellular macromolecules and organelles.Comment: 14 pages, 3 figure

Using Cyber-enabled Transaction Data to Study Productivity and Innovation in Organizations

This paper draws on recent research in a wide variety of disciplines to identify the key elements necessary to build an empirical infrastructure that will advance research on one of the key building blocks of science and innovation policy: organizations. We argue that cyber-tools and new data will permit researchers to examine the innovation process |both successes and failures| and explore business performance and business dynamics at the level of the appropriate economic entity. We develop a roadmap that outlines how the new data can be developed, from harvesting the web to direct observation from deep within companies. The paper identifies a set of research questions and an approach whose pursuit could be used to develop a national research data infrastructure for the study of innovation and organizational performance. One key element of the approach is to identify and study innovation processes within organizations by collecting data on inputs and outcomes of innovation projects (or initiatives) within organizations. Another is the collection of representative data by business function/processes across firms, a proven statistical and economic approach (Sturgeon et al. 2006, Brown 2008, Lewin et al 2008). Finally, we argue that the work to develop new data from deep within firms should involve the participation of computer and information scientists. Opportunities for quasi experimental approaches to data collection, and noninvasive techniques to harvest data from within firms (i.e., auto-populating of researcher databases) need to be explored. More generally, the bringing together of scientists to consider business microdata privacy/access and data collection from organizations is itself significant, with potential for creating opportunities in a broad range of applications.

A model and prototype implementation for tracking and tracing agricultural batch products along the food chain

There is an increasing demand of traceability in the food chain, statutory requirements are growing stricter and there is increasing pressure to develop standardized traceability systems. Each event in the chain, like production of transportation, packing, distribution or processing results in a different product which can have its own information associated within the tracing system. From the raw material to the sale of goods, more and more information needs to be gathered and made available. Supplementary information may also be collected at any step, in order to provide data for analysis and optimization of production practices. Using web-based systems for data processing, storage and transfer makes possible a flexible way of information access, networking and usability. In this paper an architectural proposal is presented and the proposed solution is tested by the implementation of a prototype. The software architecture presented makes use of a series of standards than offer new possibilities in traceability control and management. For testing the prototype, information from precision farming together with the information recorded during the transport and delivery was used. The system enables full traceability and it complies with all existing traceability standards

Tracing Digital Transformation Pathways from Subsistence Farming to Equitable and Sustainable Modern Society: Revisiting the eKutir ICT Platform-Enabled Ecosystem as an Interstitial Space

Digitalization has impacted how new practices emerge. In this study, we examined the genesis of new practices during the implementation of an ICT platform-enabled ecosystem in communities of subsistence farmers who were opening to modern development. The platform ecosystem, led by the eKutir social enterprise (Odisha, India), leveraged micro-entrepreneurs to establish networks of actors to support farmers. We view the eKutir model as an interstitial space, i.e., a transition space (combining physical, digital, and human components) that brings actors from different institutional fields together. Five focus groups (n=83 farmers) and semi-structured interviews (n=18 individuals) were conducted. Transcripts were analyzed using inductive methods. The study reveals a six-step institutional process: (i) forming physical and digital connections, (ii) gaining legitimacy, (iii) establishing inter-field resource dependencies, (iv) distributing power, (v) standardizing practices, and (vi) sustaining changes in practices. This study contributes to research on ICT for development and interstitial spaces

Web-enabled, Real-time, Quality Assurance for Machining Production Systems

AbstractIn order to maintain the close control of production quality, frequent measurement and process parameter adjustments are desirable. In the discrete parts industry, part inspection is intended to be a metric for the process quality but quality control is typically done long after the part has been machined. The long latency between machining and quality assessment makes it difficult to incorporate quality feedback into production. Quality assurance relies on continuous real–time quality feedback, which is not a complex concept. However, the collection and representation of the necessary process data and quality measurement data is challenging. This paper discusses Web-enabled, real-time quality data and statistics based on the integration of two manufacturing open specifications: MTConnect and Quality Measurement Results (QMResults). A pilot implementation that integrates the two technologies and produces Web-enabled, real-time quality results in a standard XML representation from Computer Numerical Control (CNC) machine tool inspections will be discussed

Integrated Research Plan to Assess the Combined Effects of Space Radiation, Altered Gravity, and Isolation and Confinement on Crew Health and Performance: Problem Statement

Future crewed exploration missions to Mars could last up to three years and will expose astronauts to unprecedented environmental challenges. Challenges to the nervous system during these missions will include factors of: space radiation that can damage sensitive neurons in the central nervous system (CNS); isolation and confinement can affect cognition and behavior; and altered gravity that will change the astronauts perception of their environment and their spatial orientation, and will affect their coordination, balance, and locomotion. In the past, effects of spaceflight stressors have been characterized individually. However, long-term, simultaneous exposure to multiple stressors will produce a range of interrelated behavioral and biological effects that have the potential to adversely affect operationally relevant crew performance. These complex environmental challenges might interact synergistically and increase the overall risk to the health and performance of the astronaut. Therefore, NASAs Human Research Program (HRP) has directed an integrated approach to characterize and mitigate the risk to the CNS from simultaneous exposure to these multiple spaceflight factors. The proposed research strategy focuses on systematically evaluating the relationships among three existing research risks associated with spaceflight: Risk of Acute (In-flight) and Late Central Nervous System Effects from Radiation (CNS), Risk of Adverse Cognitive or Behavioral Conditions and Psychiatric Disorders (BMed), and Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Spaceflight (SM). NASAs HRP approach is intended to identify the magnitude and types of interactions as they affect behavior, especially as it relates to operationally relevant performance (e.g., performance that depends on reaction time, procedural memory, etc.). In order to appropriately characterize this risk of multiple spaceflight environmental stressors, there is a recognition of the need to leverage research approaches using appropriate animal models and behavioral constructs. Very little has been documented on the combined effects of altered gravity, space radiation, and other psychological and cognitive stressors on the CNS. Preliminary evidence from rodents suggest that a combination of a minimum of exposures to even two of three stressors of: simulated space radiation, simulated microgravity, and simulated isolation and confinement, have produced different and more pronounced biological and performance effects than exposure to these same stressors individually. Structural and functional changes to the CNS of rodents exposed to transdisciplinary combined stressors indicate that important processes related to information processing are likely altered including impairment of exploratory and risk taking behaviors, as well as executive function including learning, memory, and cognitive flexibility all of which may be linked to changes in related operational relevant performance. The fully integrated research plan outlines approaches to evaluate how combined, potentially synergistic, impacts of simultaneous exposures to spaceflight hazards will affect an astronauts CNS and their operationally relevant performance during future exploration missions, including missions to the Moon and Mars. The ultimate goals are to derive risk estimates for the combined, potentially synergistic, effects of the three major spaceflight hazards that will establish acceptable maximum decrement or change in a physiological or behavioral parameters during or after spaceflight, the acceptable limit of exposure to a spaceflight factor, and to evaluate strategies to mitigate any associated decrements in operationally relevant performance