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Periodicals

A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence

We define hybrid intelligence (HI) as the combination of human and machine intelligence, augmenting human intellect and capabilities instead of replacing them and achieving goals that were unreachable by either humans or machines. HI is an important new research focus for artificial intelligence, and we set a research agenda for HI by formulating four challenges.

Architecture & Planning• 2020• IEEE Computer Society
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Periodicals

Spatial atomic layer deposition: A route towards further industrialization of atomic layer deposition

Atomic layer deposition (ALD) is a technique capable of producing ultrathin conformal films with atomic level control over thickness. A major drawback of ALD is its low deposition rate, making ALD less attractive for applications that require high throughput processing. An approach to overcome this drawback is spatial ALD, i.e., an ALD mode where the half-reactions are separated spatially instead of through the use of purge steps. This allows for high deposition rate and high throughput ALD without compromising the typical ALD assets. This paper gives a perspective of past and current developments in spatial ALD. The technology is discussed and the main players are identified. Furthermore, this overview highlights current as well as new applications for spatial ALD, with a focus on photovoltaics and flexible electronics.

Architecture & Planning• 2011• American Institute of Physics
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Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples

We have recently developed analysis methods (GREML) to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP) data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (co)variation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases) in particular when the traits (diseases) are not measured on the same samples.

Architecture & Planning• 2014• Public Library of Science
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Periodicals

Against Financial Literacy Education

The dominant model of regulation in the United States for consumer credit, insurance, and investment products is disclosure and unfettered choice. As these products have become increasingly complex, consumers’ inability to understand them has become increasingly apparent, and the consequences of this inability more dire. In response, policymakers have embraced financial literacy education as a necessary corollary to the disclosure model of regulation. This education is widely believed to turn consumers into “responsible” and “empowered” market players, motivated and competent to make financial decisions that increase their own welfare. The vision is of educated consumers handling their own credit, insurance, and retirement planning matters by confidently navigating the bountiful unrestricted marketplace.\nAlthough the vision is seductive, promising both a free market and increased consumer welfare, the predicate belief in the effectiveness of financial literacy education lacks empirical support. Moreover, the belief is implausible, given the velocity of change in the financial marketplace, the gulf between current consumer skills and those needed to understand today’s complex non-standardized financial products, the persistence of biases in financial decisionmaking, and the disparity between educators and financial services firms in resources with which to reach consumers.\nHarboring this belief may be innocent, but it is not harmless; the pursuit of financial literacy poses costs that almost certainly swamp any benefits. For some consumers, financial education appears to increase confidence without improving ability, leading to worse decisions. When consumers find themselves in dire financial straits, the regulation through education model blames them for their plight, shaming them and deflecting calls for effective market regulation. Consumers generally do not serve as their own doctors and lawyers and for reasons of efficient division of labor alone, generally should not serve as their own financial experts. The search for effective financial literacy education should be replaced by a search for policies more conducive to good consumer financial outcomes.

Architecture & Planning• 2008• University of Pennsylvania
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Toward open sharing of task-based fMRI data: the OpenfMRI project

The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function.

Architecture & Planning• 2013• Frontiers Media
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Periodicals

ITK: enabling reproducible research and open science

Reproducibility verification is essential to the practice of the scientific method. Researchers report their findings, which are strengthened as other independent groups in the scientific community share similar outcomes. In the many scientific fields where software has become a fundamental tool for capturing and analyzing data, this requirement of reproducibility implies that reliable and comprehensive software platforms and tools should be made available to the scientific community. The tools will empower them and the public to verify, through practice, the reproducibility of observations that are reported in the scientific literature. Medical image analysis is one of the fields in which the use of computational resources, both software and hardware, are an essential platform for performing experimental work. In this arena, the introduction of the Insight Toolkit (ITK) in 1999 has transformed the field and facilitates its progress by accelerating the rate at which algorithmic implementations are developed, tested, disseminated and improved. By building on the efficiency and quality of open source methodologies, ITK has provided the medical image community with an effective platform on which to build a daily workflow that incorporates the true scientific practices of reproducibility verification. This article describes the multiple tools, methodologies, and practices that the ITK community has adopted, refined, and followed during the past decade, in order to become one of the research communities with the most modern reproducibility verification infrastructure. For example, 207 contributors have created over 2400 unit tests that provide over 84% code line test coverage. The Insight Journal, an open publication journal associated with the toolkit, has seen over 360,000 publication downloads. The median normalized closeness centrality, a measure of knowledge flow, resulting from the distributed peer code review system was high, 0.46.

Architecture & Planning• 2014• Frontiers Media
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Periodicals

Hand in Motion Reveals Mind in Motion

Recently, researchers have measured hand movements en route to choices on a screen to understand the dynamics of a broad range of psychological processes. We review this growing body of research and explain how manual action exposes the real-time unfolding of underlying cognitive processing. We describe how simple hand motions may be used to continuously index participants' tentative commitments to different choice alternatives during the evolution of a behavioral response. As such, hand-tracking can provide unusually high-fidelity, real-time motor traces of the mind. These motor traces cast novel theoretical and empirical light onto a wide range of phenomena and serve as a potential bridge between far-reaching areas of psychological science - from language, to high-level cognition and learning, to social cognitive processes.

Architecture & Planning• 2011• Frontiers Media
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Periodicals

Transformers in Remote Sensing: A Survey

Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformer-based architectures, originally introduced in natural language processing, have pervaded computer vision field where the self-attention mechanism has been utilized as a replacement to the popular convolution operator for capturing long-range dependencies. Inspired by recent advances in computer vision, the remote sensing community has also witnessed an increased exploration of vision transformers for a diverse set of tasks. Although a number of surveys have focused on transformers in computer vision in general, to the best of our knowledge we are the first to present a systematic review of recent advances based on transformers in remote sensing. Our survey covers more than 60 recent transformer-based methods for different remote sensing problems in sub-areas of remote sensing: very high-resolution (VHR), hyperspectral (HSI) and synthetic aperture radar (SAR) imagery. We conclude the survey by discussing different challenges and open issues of transformers in remote sensing.

Architecture & Planning• 2023• Multidisciplinary Digital Publishing Institute
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Challenges with Verifying Microbial Degradation of Polyethylene

Polyethylene (PE) is the most abundant synthetic, petroleum-based plastic materials produced globally, and one of the most resistant to biodegradation, resulting in massive accumulation in the environment. Although the microbial degradation of polyethylene has been reported, complete biodegradation of polyethylene has not been achieved, and rapid degradation of polyethylene under ambient conditions in the environment is still not feasible. Experiments reported in the literature suffer from a number of limitations, and conclusive evidence for the complete biodegradation of polyethylene by microorganisms has been elusive. These limitations include the lack of a working definition for the biodegradation of polyethylene that can lead to testable hypotheses, a non-uniform description of experimental conditions used, and variations in the type(s) of polyethylene used, leading to a profound limitation in our understanding of the processes and mechanisms involved in the microbial degradation of polyethylene. The objective of this review is to outline the challenges in polyethylene degradation experiments and clarify the parameters required to achieve polyethylene biodegradation. This review emphasizes the necessity of developing a biochemically-based definition for the biodegradation of polyethylene (and other synthetic plastics) to simplify the comparison of results of experiments focused for the microbial degradation of polyethylene.

Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
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Periodicals

The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data

Abstract. The Orbiting Carbon Observatory-3 (OCO-3) is NASA's next instrument dedicated to extending the record of the dry-air mole fraction of column carbon dioxide (XCO2) and solar-induced fluorescence (SIF) measurements from space. The current schedule calls for a launch from the Kennedy Space Center no earlier than April 2019 via a Space-X Falcon 9 and Dragon capsule. The instrument will be installed as an external payload on the Japanese Experimental Module Exposed Facility (JEM-EF) of the International Space Station (ISS) with a nominal mission lifetime of 3 years. The precessing orbit of the ISS will allow for viewing of the Earth at all latitudes less than approximately 52∘, with a ground repeat cycle that is much more complicated than the polar-orbiting satellites that so far have carried all of the instruments capable of measuring carbon dioxide from space. The grating spectrometer at the core of OCO-3 is a direct copy of the OCO-2 spectrometer, which was launched into a polar orbit in July 2014. As such, OCO-3 is expected to have similar instrument sensitivity and performance characteristics to OCO-2, which provides measurements of XCO2 with precision better than 1 ppm at 3 Hz, with each viewing frame containing eight footprints approximately 1.6 km by 2.2 km in size. However, the physical configuration of the instrument aboard the ISS, as well as the use of a new pointing mirror assembly (PMA), will alter some of the characteristics of the OCO-3 data compared to OCO-2. Specifically, there will be significant differences from day to day in the sampling locations and time of day. In addition, the flexible PMA system allows for a much more dynamic observation-mode schedule. This paper outlines the science objectives of the OCO-3 mission and, using a simulation of 1 year of global observations, characterizes the spatial sampling, time-of-day coverage, and anticipated data quality of the simulated L1b. After application of cloud and aerosol prescreening, the L1b radiances are run through the operational L2 full physics retrieval algorithm, as well as post-retrieval filtering and bias correction, to examine the expected coverage and quality of the retrieved XCO2 and to show how the measurement objectives are met. In addition, results of the SIF from the IMAP–DOAS algorithm are analyzed. This paper focuses only on the nominal nadir–land and glint–water observation modes, although on-orbit measurements will also be made in transition and target modes, similar to OCO-2, as well as the new snapshot area mapping (SAM) mode.

Architecture & Planning• 2019• Copernicus Publications
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Periodicals

Cloud Computing: Today and Tomorrow.

During the past few years, cloud computing has become a key IT buzzword. Although the definition of cloud computing is still "cloudy", the trade press and bloggers label many vendors as cloud computing vendors, and report on their services and issues. Cloud computing is in its infancy in terms of market adoption. However, it is a key IT megatrend that will take root. This article reviews its definition and status, adoption issues, and provides a glimpse of its future and discusses technical issues that are expected to be addressed.

Architecture & Planning• 2009• EtH Zurich
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Closing the Achievement Gap through Modification of Neurocognitive and Neuroendocrine Function: Results from a Cluster Randomized Controlled Trial of an Innovative Approach to the Education of Children in Kindergarten

Effective early education is essential for academic achievement and positive life outcomes, particularly for children in poverty. Advances in neuroscience suggest that a focus on self-regulation in education can enhance children's engagement in learning and establish beneficial academic trajectories in the early elementary grades. Here, we experimentally evaluate an innovative approach to the education of children in kindergarten that embeds support for self-regulation, particularly executive functions, into literacy, mathematics, and science learning activities. Results from a cluster randomized controlled trial involving 29 schools, 79 classrooms, and 759 children indicated positive effects on executive functions, reasoning ability, the control of attention, and levels of salivary cortisol and alpha amylase. Results also demonstrated improvements in reading, vocabulary, and mathematics at the end of kindergarten that increased into the first grade. A number of effects were specific to high-poverty schools, suggesting that a focus on executive functions and associated aspects of self-regulation in early elementary education holds promise for closing the achievement gap.

Architecture & Planning• 2014• Public Library of Science
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Applications of Multi-Omics Technologies for Crop Improvement

Multiple “omics” approaches have emerged as successful technologies for plant systems over the last few decades. Advances in next-generation sequencing (NGS) have paved a way for a new generation of different omics, such as genomics, transcriptomics, and proteomics. However, metabolomics, ionomics, and phenomics have also been well-documented in crop science. Multi-omics approaches with high throughput techniques have played an important role in elucidating growth, senescence, yield, and the responses to biotic and abiotic stress in numerous crops. These omics approaches have been implemented in some important crops including wheat ( Triticum aestivum L.), soybean ( Glycine max ), tomato ( Solanum lycopersicum ), barley ( Hordeum vulgare L.), maize ( Zea mays L.), millet ( Setaria italica L.), cotton ( Gossypium hirsutum L.), Medicago truncatula , and rice ( Oryza sativa L.). The integration of functional genomics with other omics highlights the relationships between crop genomes and phenotypes under specific physiological and environmental conditions. The purpose of this review is to dissect the role and integration of multi-omics technologies for crop breeding science. We highlight the applications of various omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, and ionomics, and the implementation of robust methods to improve crop genetics and breeding science. Potential challenges that confront the integration of multi-omics with regard to the functional analysis of genes and their networks as well as the development of potential traits for crop improvement are discussed. The panomics platform allows for the integration of complex omics to construct models that can be used to predict complex traits. Systems biology integration with multi-omics datasets can enhance our understanding of molecular regulator networks for crop improvement. In this context, we suggest the integration of entire omics by employing the “phenotype to genotype” and “genotype to phenotype” concept. Hence, top-down (phenotype to genotype) and bottom-up (genotype to phenotype) model through integration of multi-omics with systems biology may be beneficial for crop breeding improvement under conditions of environmental stresses.

Architecture & Planning• 2021• Frontiers Media
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Periodicals

A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses

Unmanned aerial vehicles (UAVs) are becoming a valuable tool to collect data in a variety of contexts. Their use in agriculture is particularly suitable, as those areas are often vast, making ground scouting difficult, and sparsely populated, which means that injury and privacy risks are not as important as in urban settings. Indeed, the use of UAVs for monitoring and assessing crops, orchards, and forests has been growing steadily during the last decade, especially for the management of stresses such as water, diseases, nutrition deficiencies, and pests. This article presents a critical overview of the main advancements on the subject, focusing on the strategies that have been used to extract the information contained in the images captured during the flights. Based on the information found in more than 100 published articles and on our own research, a discussion is provided regarding the challenges that have already been overcome and the main research gaps that still remain, together with some suggestions for future research.

Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
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Initial Genomics of the Human Nucleolus

We report for the first time the genomics of a nuclear compartment of the eukaryotic cell. 454 sequencing and microarray analysis revealed the pattern of nucleolus-associated chromatin domains (NADs) in the linear human genome and identified different gene families and certain satellite repeats as the major building blocks of NADs, which constitute about 4% of the genome. Bioinformatic evaluation showed that NAD-localized genes take part in specific biological processes, like the response to other organisms, odor perception, and tissue development. 3D FISH and immunofluorescence experiments illustrated the spatial distribution of NAD-specific chromatin within interphase nuclei and its alteration upon transcriptional changes. Altogether, our findings describe the nature of DNA sequences associated with the human nucleolus and provide insights into the function of the nucleolus in genome organization and establishment of nuclear architecture.

Architecture & Planning• 2010• Public Library of Science
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Citizenship Rights for Immigrants: National Political Processes and Cross-National Convergence in Western Europe, 1980–2008

Immigrant citizenship rights in the nation-state reference both theories of cross-national convergence and the resilience of national political processes. This article investigates European countries' attribution of rights to immigrants: Have these rights become more inclusive and more similar across countries? Are they affected by EU membership, the role of the judiciary, the party in power, the size of the immigrant electorate, or pressure exerted by anti-immigrant parties? Original data on 10 European countries, 1980-2008, reveal no evidence for cross-national convergence. Rights tended to become more inclusive until 2002, but stagnated afterward. Electoral changes drive these trends: growth of the immigrant electorate led to expansion, but countermobilization by right-wing parties slowed or reversed liberalizations. These electoral mechanisms are in turn shaped by long-standing policy traditions, leading to strong path dependence and the reproduction of preexisting cross-national differences.

Architecture & Planning• 2012• University of Chicago Press
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Hydroponic Solutions for Soilless Production Systems: Issues and Opportunities in a Smart Agriculture Perspective

Soilless cultivation systems represent a valid opportunity for the agricultural production sector, especially in areas characterized by severe soil degradation and limited water availability. Furthermore, this agronomic practice embodies a favourable response towards an environmental-friendly agriculture and a promising tool in the vision of a general challenge in terms of food security. This review aims therefore at unravelling limitations and opportunities of hydroponic solutions used in soilless cropping systems focusing on the plant mineral nutrition process. In particular, this review provides information i) on the processes and mechanisms occurring in the hydroponic solutions that ensure an adequate nutrient concentration and thus an optimal nutrient acquisition without leading to nutritional disorders influencing ultimately also crop quality (e.g. solubilization/precipitation of nutrients/elements in the hydroponic solution, substrate specificity in the nutrient uptake process, nutrient competition/antagonism and interactions among nutrients); ii) on new emerging technologies that might improve the management of soilless cropping systems such as the use of nanoparticles and beneficial microorganism like plant growth promoting rhizobacteria (PGPRs); iii) on tools (multi-element sensors and interpretation algorithms based on machine learning logics to analyse such data) that might be exploited in a smart agriculture approach to monitor the availability of nutrients/elements in the hydroponic solution and to modify its composition in realtime. These aspects are discussed considering what has been recently demonstrated at the scientific level and applied in the industrial context.

Architecture & Planning• 2019• Frontiers Media
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Immersive VR and Education: Embodied Design Principles That Include Gesture and Hand Controls

This article explores relevant applications of educational theory for the design of immersive virtual reality (VR). Two unique attributes associated with VR position the technology to positively affect education: 1) the sensation of presence, and 2) the embodied affordances of gesture and manipulation in the 3rd dimension. These are referred to as the two profound affordances of VR. The primary focus of this article is on the embodiment afforded by gesture and 3D for learning. The new generation of hand controllers induces embodiment and agency via meaningful and congruent movements with the content to be learned. Several examples of gesture-rich lessons are presented. The final section includes an extensive set of design principles for immersive VR in education, and finishes with the Necessary Nine which are hypothesized to optimize the pedagogy within a lesson.

Architecture & Planning• 2018• Frontiers Media
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A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector

In the telecom sector, a huge volume of data is being generated on a daily basis due to a vast client base. Decision makers and business analysts emphasized that attaining new customers is costlier than retaining the existing ones. Business analysts and customer relationship management (CRM) analyzers need to know the reasons for churn customers, as well as, behavior patterns from the existing churn customers’ data. This paper proposes a churn prediction model that uses classification, as well as, clustering techniques to identify the churn customers and provides the factors behind the churning of customers in the telecom sector. Feature selection is performed by using information gain and correlation attribute ranking filter. The proposed model first classifies churn customers data using classification algorithms, in which the Random Forest (RF) algorithm performed well with 88.63% correctly classified instances. Creating effective retention policies is an essential task of the CRM to prevent churners. After classification, the proposed model segments the churning customer’s data by categorizing the churn customers in groups using cosine similarity to provide group-based retention offers. This paper also identified churn factors that are essential in determining the root causes of churn. By knowing the significant churn factors from customers’ data, CRM can improve productivity, recommend relevant promotions to the group of likely churn customers based on similar behavior patterns, and excessively improve marketing campaigns of the company. The proposed churn prediction model is evaluated using metrics, such as accuracy, precision, recall, f-measure, and receiving operating characteristics (ROC) area. The results reveal that our proposed churn prediction model produced better churn classification using the RF algorithm and customer profiling usingk-meansclustering. Furthermore, it also provides factors behind the churning of churn customers through the rules generated by using the attribute-selected classifier algorithm.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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