Periodicals
Genome-wide association analysis identifies 13 new risk loci for schizophrenia
[no abstract]
Architecture & Planning• 2013• Nature Portfolio
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Periodicals
Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors
Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear systems is the focus of investigations, it is of equal importance to create goal-directed behavior (e.g., stable locomotion from a system of coupled oscillators under perceptual guidance). Modeling goal-directed behavior with nonlinear systems is, however, rather difficult due to the parameter sensitivity of these systems, their complex phase transitions in response to subtle parameter changes, and the difficulty of analyzing and predicting their long-term behavior; intuition and time-consuming parameter tuning play a major role. This letter presents and reviews dynamical movement primitives, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques. The essence of our approach is to start with a simple dynamical system, such as a set of linear differential equations, and transform those into a weakly nonlinear system with prescribed attractor dynamics by means of a learnable autonomous forcing term. Both point attractors and limit cycle attractors of almost arbitrary complexity can be generated. We explain the design principle of our approach and evaluate its properties in several example applications in motor control and robotics.
Architecture & Planning• 2012• The MIT Press
Periodicals
A User's Guide to the Encyclopedia of DNA Elements (ENCODE)
The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.
Architecture & Planning• 2011• Public Library of Science
Periodicals
Is It Time to Start Transitioning From 2D to 3D Cell Culture?
Cell culture is an important and necessary process in drug discovery, cancer research, as well as stem cell research. Most cells are currently cultured using two-dimensional (2D) methods, but new and improved methods that implement three-dimensional (3D) cell culture techniques suggest compelling evidence that much more advanced experiments can be performed. When performing 3D cell culture experiments, the cell environment can be manipulated to mimic that of a cell in vivo and provide more accurate data about cell-to-cell interactions, tumor characteristics, drug discovery, metabolic profiling, stem cell research, and other types of diseases. Scaffold based techniques such as hydrogel-based support, polymeric hard material-based support, hydrophilic glass fiber, and organoids are employed, and each provides its own advantages and applications. Likewise, there are also scaffold-free techniques used such as hanging drop microplates, magnetic levitation, and spheroid microplates with ultra-low attachment coating. 3D cell culture has the potential to provide alternative ways to study organ behavior via the use of organoids and is expected to eventually bridge the gap between 2D cell culture and animal models. The present review compares 2D cell culture to 3D cell culture, provides the details surrounding the different 3D culture techniques, as well as focuses on the present and future applications of 3D cell culture.
Architecture & Planning• 2020• Frontiers Media
Periodicals
A Survey of Augmented Reality Technologies, Applications and Limitations
A Survey of Augmented Reality Technologies, Applications and Limitations
Architecture & Planning• 2010
Periodicals
Power and Predictive Accuracy of Polygenic Risk Scores
Polygenic scores have recently been used to summarise genetic effects among an ensemble of markers that do not individually achieve significance in a large-scale association study. Markers are selected using an initial training sample and used to construct a score in an independent replication sample by forming the weighted sum of associated alleles within each subject. Association between a trait and this composite score implies that a genetic signal is present among the selected markers, and the score can then be used for prediction of individual trait values. This approach has been used to obtain evidence of a genetic effect when no single markers are significant, to establish a common genetic basis for related disorders, and to construct risk prediction models. In some cases, however, the desired association or prediction has not been achieved. Here, the power and predictive accuracy of a polygenic score are derived from a quantitative genetics model as a function of the sizes of the two samples, explained genetic variance, selection thresholds for including a marker in the score, and methods for weighting effect sizes in the score. Expressions are derived for quantitative and discrete traits, the latter allowing for case/control sampling. A novel approach to estimating the variance explained by a marker panel is also proposed. It is shown that published studies with significant association of polygenic scores have been well powered, whereas those with negative results can be explained by low sample size. It is also shown that useful levels of prediction may only be approached when predictors are estimated from very large samples, up to an order of magnitude greater than currently available. Therefore, polygenic scores currently have more utility for association testing than predicting complex traits, but prediction will become more feasible as sample sizes continue to grow.
Architecture & Planning• 2013• Public Library of Science
Periodicals
Business Model Design and the Performance of Entrepreneurial Firms
We focus on the design of an organization’s set of boundary-spanning transactions—business model design—and ask how business model design affects the performance of entrepreneurial firms. By extending and integrating theoretical perspectives that inform the study of boundary-spanning organization design, we propose hypotheses about the impact of efficiency-centered and novelty-centered business model design on the performance of entrepreneurial firms. To test these hypotheses, we developed and analyzed a unique data set of 190 entrepreneurial firms that were publicly listed on U.S. and European stock exchanges. The empirical results show that novelty-centered business model design matters to the performance of entrepreneurial firms. Our analysis also shows that this positive relationship is remarkably stable across time, even under varying environmental regimes. Additionally, we find indications of potential diseconomies of scope in design; that is, entrepreneurs’ attempts to incorporate both efficiency- and novelty-centered design elements into their business models may be counterproductive.
Architecture & Planning• 2007• Institute for Operations Research and the Management Sciences
Periodicals
Attachment and reflective function: Their role in self-organization
The paper traces the relationship between attachment processes and the development of the capacity to envision mental states in self and others. We suggest that the ability to mentalize, to represent behavior in terms of mental states, or to have "a theory of mind" is a key determinant of self-organization which is acquired in the context of the child's early social relationships. Evidence for an association between the quality of attachment relationship and reflective function in the parent and the child is reviewed and interpreted in the context of current models of theory of mind development. A model of the development of self-organization is proposed which has at its core the caregiver's ability to communicate understanding of the child's intentional stance. The implications of the model for pathological self-development are explored, with specific reference to the consequences of maltreatment.
Architecture & Planning• 1997• Cambridge University Press
Periodicals
Overview of the Versatile Video Coding (VVC) Standard and its Applications
Versatile Video Coding (VVC) was finalized in July 2020 as the most recent international video coding standard. It was developed by the Joint Video Experts Team (JVET) of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) to serve an ever-growing need for improved video compression as well as to support a wider variety of today’s media content and emerging applications. This paper provides an overview of the novel technical features for new applications and the core compression technologies for achieving significant bit rate reductions in the neighborhood of 50% over its predecessor for equal video quality, the High Efficiency Video Coding (HEVC) standard, and 75% over the currently most-used format, the Advanced Video Coding (AVC) standard. It is explained how these new features in VVC provide greater versatility for applications. Highlighted applications include video with resolutions beyond standard- and high-definition, video with high dynamic range and wide color gamut, adaptive streaming with resolution changes, computer-generated and screen-captured video, ultralow-delay streaming, 360° immersive video, and multilayer coding e.g., for scalability. Furthermore, early implementations are presented to show that the new VVC standard is implementable and ready for real-world deployment.
Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
Periodicals
MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP
Abstract. The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO2. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.1 % for SO2, +19.2 % for NOx, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH3, −3.4 % for PM10, −1.6 % for PM2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO2. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.
Architecture & Planning• 2017• Copernicus Publications
Periodicals
Chronic pain: a review of its epidemiology and associated factors in population-based studies
[no abstract]
Architecture & Planning• 2019• Elsevier BV
Periodicals
The fit between product market strategy and business model: implications for firm performance
Abstract We examine the fit between a firm's product market strategy and its business model. We develop a formal model in order to analyze the contingent effects of product market strategy and business model choices on firm performance. We investigate a unique, manually collected dataset, and find that novelty‐centered business models—coupled with product market strategies that emphasize differentiation, cost leadership, or early market entry—can enhance firm performance. Our data suggest that business model and product market strategy are complements, not substitutes. Copyright © 2007 John Wiley & Sons, Ltd.
Architecture & Planning• 2007• Wiley
Periodicals
The acute respiratory distress syndrome
The acute respiratory distress syndrome (ARDS) is an important cause of acute respiratory failure that is often associated with multiple organ failure. Several clinical disorders can precipitate ARDS, including pneumonia, sepsis, aspiration of gastric contents, and major trauma. Physiologically, ARDS is characterized by increased permeability pulmonary edema, severe arterial hypoxemia, and impaired carbon dioxide excretion. Based on both experimental and clinical studies, progress has been made in understanding the mechanisms responsible for the pathogenesis and the resolution of lung injury, including the contribution of environmental and genetic factors. Improved survival has been achieved with the use of lung-protective ventilation. Future progress will depend on developing novel therapeutics that can facilitate and enhance lung repair.
Architecture & Planning• 2012• American Society for Clinical Investigation
Periodicals
Strategic talent management: A review and research agenda
[no abstract]
Architecture & Planning• 2009• Elsevier BV
Periodicals
A Survey of Autonomous Driving: <i>Common Practices and Emerging Technologies</i>
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of state-of-the-art is improved further. This paper discusses unsolved problems and surveys the technical aspect of automated driving. Studies regarding present challenges, high-level system architectures, emerging methodologies and core functions including localization, mapping, perception, planning, and human machine interfaces, were thoroughly reviewed. Furthermore, many state-of-the-art algorithms were implemented and compared on our own platform in a real-world driving setting. The paper concludes with an overview of available datasets and tools for ADS development.
Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
Periodicals
A survey of deep learning techniques for autonomous driving
Abstract The last decade witnessed increasingly rapid progress in self‐driving vehicle technology, mainly backed up by advances in the area of deep learning and artificial intelligence (AI). The objective of this paper is to survey the current state‐of‐the‐art on deep learning technologies used in autonomous driving. We start by presenting AI‐based self‐driving architectures, convolutional and recurrent neural networks, as well as the deep reinforcement learning paradigm. These methodologies form a base for the surveyed driving scene perception, path planning, behavior arbitration, and motion control algorithms. We investigate both the modular perception‐planning‐action pipeline, where each module is built using deep learning methods, as well as End2End systems, which directly map sensory information to steering commands. Additionally, we tackle current challenges encountered in designing AI architectures for autonomous driving, such as their safety, training data sources, and computational hardware. The comparison presented in this survey helps gain insight into the strengths and limitations of deep learning and AI approaches for autonomous driving and assist with design choices.
Architecture & Planning• 2019• Wiley
Periodicals
Impact of Climate Change on Crops Adaptation and Strategies to Tackle Its Outcome: A Review
Agriculture and climate change are internally correlated with each other in various aspects, as climate change is the main cause of biotic and abiotic stresses, which have adverse effects on the agriculture of a region. The land and its agriculture are being affected by climate changes in different ways, e.g., variations in annual rainfall, average temperature, heat waves, modifications in weeds, pests or microbes, global change of atmospheric CO₂ or ozone level, and fluctuations in sea level. The threat of varying global climate has greatly driven the attention of scientists, as these variations are imparting negative impact on global crop production and compromising food security worldwide. According to some predicted reports, agriculture is considered the most endangered activity adversely affected by climate changes. To date, food security and ecosystem resilience are the most concerning subjects worldwide. Climate-smart agriculture is the only way to lower the negative impact of climate variations on crop adaptation, before it might affect global crop production drastically. In this review paper, we summarize the causes of climate change, stresses produced due to climate change, impacts on crops, modern breeding technologies, and biotechnological strategies to cope with climate change, in order to develop climate resilient crops. Revolutions in genetic engineering techniques can also aid in overcoming food security issues against extreme environmental conditions, by producing transgenic plants.
Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
Periodicals
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
Periodicals
Sustainable data analysis with Snakemake
Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.
Architecture & Planning• 2021• Faculty of 1000
Periodicals
A Metaverse: Taxonomy, Components, Applications, and Open Challenges
Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is based on the social value of Generation Z that online and offline selves are not different. With the technological development of deep learning-based high-precision recognition models and natural generation models, Metaverse is being strengthened with various factors, from mobile-based always-on access to connectivity with reality using virtual currency. The integration of enhanced social activities and neural-net methods requires a new definition of Metaverse suitable for the present, different from the previous Metaverse. This paper divides the concepts and essential techniques necessary for realizing the Metaverse into three components (i.e., hardware, software, and contents) and three approaches (i.e., user interaction, implementation, and application) rather than marketing or hardware approach to conduct a comprehensive analysis. Furthermore, we describe essential methods based on three components and techniques to Metaverse’s representative Ready Player One, Roblox, and Facebook research in the domain of films, games, and studies. Finally, we summarize the limitations and directions for implementing the immersive Metaverse as social influences, constraints, and open challenges.
Architecture & Planning• 2022• Institute of Electrical and Electronics Engineers
Periodicals
Machine Learning Interpretability: A Survey on Methods and Metrics
Machine learning systems are becoming increasingly ubiquitous. These systems’s adoption has been expanding, accelerating the shift towards a more algorithmic society, meaning that algorithmically informed decisions have greater potential for significant social impact. However, most of these accurate decision support systems remain complex black boxes, meaning their internal logic and inner workings are hidden to the user and even experts cannot fully understand the rationale behind their predictions. Moreover, new regulations and highly regulated domains have made the audit and verifiability of decisions mandatory, increasing the demand for the ability to question, understand, and trust machine learning systems, for which interpretability is indispensable. The research community has recognized this interpretability problem and focused on developing both interpretable models and explanation methods over the past few years. However, the emergence of these methods shows there is no consensus on how to assess the explanation quality. Which are the most suitable metrics to assess the quality of an explanation? The aim of this article is to provide a review of the current state of the research field on machine learning interpretability while focusing on the societal impact and on the developed methods and metrics. Furthermore, a complete literature review is presented in order to identify future directions of work on this field.
Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
Periodicals
Evidence that fibroblasts derive from epithelium during tissue fibrosis
Interstitial fibroblasts are principal effector cells of organ fibrosis in kidneys, lungs, and liver. While some view fibroblasts in adult tissues as nothing more than primitive mesenchymal cells surviving embryologic development, they differ from mesenchymal cells in their unique expression of fibroblast-specific protein-1 (FSP1). This difference raises questions about their origin. Using bone marrow chimeras and transgenic reporter mice, we show here that interstitial kidney fibroblasts derive from two sources. A small number of FSP1(+), CD34(-) fibroblasts migrate to normal interstitial spaces from bone marrow. More surprisingly, however, FSP1(+) fibroblasts also arise in large numbers by local epithelial-mesenchymal transition (EMT) during renal fibrogenesis. Both populations of fibroblasts express collagen type I and expand by cell division during tissue fibrosis. Our findings suggest that a substantial number of organ fibroblasts appear through a novel reversal in the direction of epithelial cell fate. As a general mechanism, this change in fate highlights the potential plasticity of differentiated cells in adult tissues under pathologic conditions.
Architecture & Planning• 2002• American Society for Clinical Investigation