Toward an integrative understanding of social behavior: new models and new opportunities.

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur

Gunrock: A High-Performance Graph Processing Library on the GPU

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We evaluate Gunrock on five key graph primitives and show that Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives, and better performance than any other GPU high-level graph library.Comment: 14 pages, accepted by PPoPP'16 (removed the text repetition in the previous version v5

ISO and Social Standardisation: Uncomfortable compromises in Global Policy-Making

This paper intends to explore the involvement of ISO, the world’s most iconic standard-setting institution, in the field of social responsibility, leading to the publication of the ISO26000 standard in November, 2010. Through several aspects of this experience, an almost decade-long process, I will show how ISO developed a new political structure aimed specifically at creating global policy, originating one the most sophisticated frameworks in existence to consensualise "universal" sociopolitical principles and infuse them with the legitimacy of a "global" technocracy and liberal institutions. Moreover, I will use the latest ISO26000 experience to argue that conceptual and institutional minimalism, which favours "soft" approaches towards global policy-making, paradoxically results from combining a technocratic aim for global compatibility with more participatory decision-making arrangements involving previously excluded socio-political actors. In that sense, ISO’s upgraded participatory mechanisms solved certain deadlocks suffered by previous initiatives only to affront and spark a new round of contradictions and consequences. Thus, I will conclude commenting on the intrinsic relationship between global standards, governance and complexity, and the difficulties of politically articulating programmes with dissimilar functional differentiation

Transferring and creating technological knowledge in interfirm R&D relationships: The initiation and evolution of interfirm learning.

In this study, we examine the initiation and evolution of interfirm learning in interfirm R&D relationships. Based on in-depth case studies, we suggest that the process of learning in interfirm R&D relationships consists of different challenges: 1) initiating technological knowledge transfer, 2) continuing technological knowledge transfer, and 3) moving towards the joint creation of new technological knowledge. Our findings identify conditions needed to initiate knowledge transfer: the presence of legal knowledge transfer clauses, overlapping skills and equipment, fragile trust and organizational similarity. The continuance of knowledge exchange implies complementary modes of collaborating characterized by sharing technologies which are oriented towards different applications. Joint knowledge creation implies convergence on the level of applications which only becomes feasible when prior knowledge exchange processes have generated resilient levels of trust. These observations point to the relevance of conceiving and organizing interfirm R&D relationships in a timephased, differentiated manner.Applications; Case studies; Convergence; Exchange; Interfirm learning; Interfirm R&D; Knowledge; Knowledge creation; Knowledge transfer; Learning; Processes; R&D; Similarity; Studies; Technology; Trust;

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie