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in Architecture & Planning
Periodicals

Mathematical Modeling of Release Kinetics from Supramolecular Drug Delivery Systems

Embedding of active substances in supramolecular systems has as the main goal to ensure the controlled release of the active ingredients. Whatever the final architecture or entrapment mechanism, modeling of release is challenging due to the moving boundary conditions and complex initial conditions. Despite huge diversity of formulations, diffusion phenomena are involved in practically all release processes. The approach in this paper starts, therefore, from mathematical methods for solving the diffusion equation in initial and boundary conditions, which are further connected with phenomenological conditions, simplified and idealized in order to lead to problems which can be analytically solved. Consequently, the release models are classified starting from the geometry of diffusion domain, initial conditions, and conditions on frontiers. Taking into account that practically all solutions of the models use the separation of variables method and integral transformation method, two specific applications of these methods are included. This paper suggests that "good modeling practice" of release kinetics consists essentially of identifying the most appropriate mathematical conditions corresponding to implied physicochemical phenomena. However, in most of the cases, models can be written but analytical solutions for these models cannot be obtained. Consequently, empiric models remain the first choice, and they receive an important place in the review.

Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
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The relationship between obesity and cognitive health and decline

The relationship between obesity and cognitive impairment is important given the globally ageing population in whom cognitive decline and neurodegenerative disorders will carry grave individual, societal and financial burdens. This review examines the evidence for the link between obesity and cognitive function in terms of both the immediate effects on cognitive performance, and effects on the trajectory of cognitive ageing and likelihood of dementia. In mid-life, there is a strong association between obesity and impaired cognitive function. Anthropometric measures of obesity are also associated with reduced neural integrity (e.g. grey and white matter atrophy). Increasing age coupled with the negative metabolic consequences of obesity (e.g. type 2 diabetes mellitus) are likely to significantly contribute to cognitive decline and incidence of dementia. Stress is identified as a potential risk factor promoting abdominal obesity and contributing to impaired cognitive function. However, the potentially protective effects of obesity against cognitive decline in older age require further examination. Finally, surgical and whole diet interventions, which address obesity may improve cognitive capacity and confer some protection against later cognitive decline. In conclusion, obesity and its comorbidities are associated with impaired cognitive performance, accelerated cognitive decline and neurodegenerative pathologies such as dementia in later life. Interventions targeting mid-life obesity may prove beneficial in reducing the cognitive risks associated with obesity.

Architecture & Planning• 2017• Cambridge University Press
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Benchmarks for models of short-term and working memory.

Any mature field of research in psychology-such as short-term/working memory-is characterized by a wealth of empirical findings. It is currently unrealistic to expect a theory to explain them all; theorists must satisfice with explaining a subset of findings. The aim of the present article is to make the choice of that subset less arbitrary and idiosyncratic than is current practice. We propose criteria for identifying benchmark findings that every theory in a field should be able to explain: Benchmarks should be reproducible, generalize across materials and methodological variations, and be theoretically informative. We propose a set of benchmarks for theories and computational models of short-term and working memory. The benchmarks are described in as theory-neutral a way as possible, so that they can serve as empirical common ground for competing theoretical approaches. Benchmarks are rated on three levels according to their priority for explanation. Selection and ratings of the benchmarks is based on consensus among the authors, who jointly represent a broad range of theoretical perspectives on working memory, and they are supported by a survey among other experts on working memory. The article is accompanied by a web page providing an open forum for discussion and for submitting proposals for new benchmarks; and a repository for reference data sets for each benchmark. (PsycINFO Database Record

Architecture & Planning• 2018• American Psychological Association
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Periodicals

Digital Business Model, Digital Transformation, Digital Entrepreneurship: Is There A Sustainable “Digital”?

Digitalization plays a major role in contributing towards the United Nations Sustainable Development Goals. Without transformation of existing businesses, both economic and environmental challenges of the future cannot be solved sustainably. However, there is much confusion on interrelationships and terms dealing with digitization or digitalization: Digital business model, digital transformation, digital entrepreneurship. How do these terms interrelate with and to digitalization, and how do they support firms to grow sustainably? To answer this question, we identified seven core digital-related terms based on a structured literature search within the management and economics domain, namely: Digital, Business Model, Digital Business Model, Digital Technology, Digital Innovation, Digital Transformation, and Digital Entrepreneurship. Thereafter, we analyzed prior literature for deriving a common understanding and definition as a basis for interrelations within a conceptual framework. Definitions were presented in a case study setup with twelve innovation and research and development (R&D) managers from various business units of a German high-tech company. Based on these insights, we propose a conceptual framework on how Digital Readiness, Digital Technology, and Digital Business Models might sustainably relate to Innovation, moderated by a Digital Transformation Process. With this approach, we aim to equip practitioners and researchers alike in handling and addressing change through digitalization sustainably.

Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
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Periodicals

Sustainable Manufacturing and Design: Concepts, Practices and Needs

An investigation is reported on the importance of integrating sustainability with manufacturing and design, along with other objectives such as function, competitiveness, profitability and productivity. The need of utilizing appropriate tools like design for environment, life cycle assessment and other environmentally sound practices that are cognizant of the entire life cycle of a process or product is highlighted. It is likely that sustainability and environmental stewardship will be increasingly important considerations in manufacturing and design in the future and are likely to influence the main priorities for advancing manufacturing operations and technologies. Designers and manufacturing decision makers who adopt a sustainability focus and establish a sustainability culture within companies are more likely to be successful in enhancing design and manufacturing. It is concluded that more extensive research and collaboration is needed to improve understanding of sustainability in manufacturing and design, and to enhance technology transfer and applications of sustainability.

Architecture & Planning• 2012• Multidisciplinary Digital Publishing Institute
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A Deep Learning Model Based on Concatenation Approach for the Diagnosis of Brain Tumor

Brain tumor is a deadly disease and its classification is a challenging task for radiologists because of the heterogeneous nature of the tumor cells. Recently, computer-aided diagnosis-based systems have promised, as an assistive technology, to diagnose the brain tumor, through magnetic resonance imaging (MRI). In recent applications of pre-trained models, normally features are extracted from bottom layers which are different from natural images to medical images. To overcome this problem, this study proposes a method of multi-level features extraction and concatenation for early diagnosis of brain tumor. Two pre-trained deep learning models i.e. Inception-v3 and DensNet201 make this model valid. With the help of these two models, two different scenarios of brain tumor detection and its classification were evaluated. First, the features from different Inception modules were extracted from pre-trained Inception-v3 model and concatenated these features for brain tumor classification. Then, these features were passed to softmax classifier to classify the brain tumor. Second, pre-trained DensNet201 was used to extract features from various DensNet blocks. Then, these features were concatenated and passed to softmax classifier to classify the brain tumor. Both scenarios were evaluated with the help of three-class brain tumor dataset that is available publicly. The proposed method produced 99.34 %, and 99.51% testing accuracies respectively with Inception-v3 and DensNet201 on testing samples and achieved highest performance in the detection of brain tumor. As results indicated, the proposed method based on features concatenation using pre-trained models outperformed as compared to existing state-of-the-art deep learning and machine learning based methods for brain tumor classification.

Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
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Artificial Intelligence and Marketing: Pitfalls and Opportunities

This article discusses the pitfalls and opportunities of AI in marketing through the lenses of knowledge creation and knowledge transfer. First, we discuss the notion of “higher-order learning” that distinguishes AI applications from traditional modeling approaches, and while focusing on recent advances in deep neural networks, we cover its underlying methodologies (multilayer perceptron, convolutional, and recurrent neural networks) and learning paradigms (supervised, unsupervised, and reinforcement learning). Second, we discuss the technological pitfalls and dangers marketing managers need to be aware of when implementing AI in their organizations, including the concepts of badly defined objective functions, unsafe or unrealistic learning environments, biased AI, explainable AI, and controllable AI. Third, AI will have a deep impact on predictive tasks that can be automated and require little explainability, we predict that AI will fall short of its promises in many marketing domains if we do not solve the challenges of tacit knowledge transfer between AI models and marketing organizations.

Architecture & Planning• 2020• SAGE Publishing
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Periodicals

Review of Battery Management Systems (BMS) Development and Industrial Standards

The evolving global landscape for electrical distribution and use created a need area for energy storage systems (ESS), making them among the fastest growing electrical power system products. A key element in any energy storage system is the capability to monitor, control, and optimize performance of an individual or multiple battery modules in an energy storage system and the ability to control the disconnection of the module(s) from the system in the event of abnormal conditions. This management scheme is known as “battery management system (BMS)”, which is one of the essential units in electrical equipment. BMS reacts with external events, as well with as an internal event. It is used to improve the battery performance with proper safety measures within a system. Therefore, a safe BMS is the prerequisite for operating an electrical system. This report analyzes the details of BMS for electric transportation and large-scale (stationary) energy storage. The analysis includes different aspects of BMS covering testing, component, functionalities, topology, operation, architecture, and BMS safety aspects. Additionally, current related standards and codes related to BMS are also reviewed. The report investigates BMS safety aspects, battery technology, regulation needs, and offer recommendations. It further studies current gaps in respect to the safety requirements and performance requirements of BMS by focusing mainly on the electric transportation and stationary application. The report further provides a framework for developing a new standard on BMS, especially on BMS safety and operational risk. In conclusion, four main areas of (1) BMS construction, (2) Operation Parameters, (3) BMS Integration, and (4) Installation for improvement of BMS safety and performance are identified, and detailed recommendations were provided for each area. It is recommended that a technical review of the BMS be performed for transportation electrification and large-scale (stationary) applications. A comprehensive evaluation of the components, architectures, and safety risks applicable to BMS operation is also presented.

Architecture & Planning• 2021• Multidisciplinary Digital Publishing Institute
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Periodicals

Sii-Mobility: An IoT/IoE Architecture to Enhance Smart City Mobility and Transportation Services

The new Internet of Things/Everything (IoT/IoE) paradigm and architecture allows one to rethink the way Smart City infrastructures are designed and managed, but on the other hand, a number of problems have to be solved. In terms of mobility the cities that embrace the sensoring era can take advantage of this disruptive technology to improve the quality of life of their citizens, also thanks to the rationalization in the use of their resources. In Sii-Mobility, a national smart city project on mobility and transportation, a flexible platform has been designed and here, in this paper, is presented. It permits one to set up heterogeneous and complex scenarios that integrate sensors/actuators as IoT/IoE in an overall Big Data, Machine Learning and Data Analytics scenario. A detailed and complex case-study has been presented to validate the solution in the context of a system that dynamically reverse the traveling direction of a road segment, with all the safety conditions in place. This case study composes several building blocks of the IoT platform, which demonstrate that a flexible and dynamic set-up is possible, supporting security, safety, local, cloud and mixed solutions.

Architecture & Planning• 2018• Multidisciplinary Digital Publishing Institute
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Periodicals

After Liberal Hegemony: The Advent of a Multiplex World Order

While the West woke up to the threat to the liberal international order when Donald Trump was elected U.S. president, its decline was apparent even at the height of the Obama-Clinton era. What follows the end of the U.S.-dominated world order is not a return to multipolarity as many pundits assume. The twenty-first-century world—politically and culturally diverse but economically and institutionally interlinked—is vastly different from the multipolar world that existed prior to World War II. China and India are major powers now; and globalization will not end, but will take on a new form, driven more by the East than the West and more by South-South linkages than North-North ones. The system of global governance will fragment, with new actors and institutions chipping away at the old UN-based system. Liberal values and institutions will not disappear, but will have to coexist and enmesh with the ideas and institutions of others, especially those initiated by China. This “multiplex world” carries both risks and opportunities for managing international stability. Instead of bemoaning the passing of the old liberal order, the West should accept the new realities and search for new ways to ensure peace and stability in partnership with the rising powers.

Architecture & Planning• 2017• Cambridge University Press
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Periodicals

What, If Anything, Is Rodent Prefrontal Cortex?

Prefrontal cortex (PFC) means different things to different people. In recent years, there has been a major increase in publications on the PFC, especially using mice. However, inconsistencies in the nomenclature and anatomical boundaries of PFC areas has made it difficult for researchers to compare data and interpret findings across species. We conducted a meta-analysis of publications on the PFC of humans and rodents and found dramatic differences in the focus of research on these species. In addition, we compared anatomical terms and criteria across several common rodent brain atlases and found inconsistencies among, and even within, leading atlases. To assess the impact of these issues on the research community, we conducted a survey of established PFC researchers on their use of anatomical terms and found little consensus. We report on the results of the survey and propose an alternative scheme for interpreting data from rodent studies, based on structural analysis of the corpus callosum and nomenclature used in research on the anterior cingulate cortex (ACC) of primates.

Architecture & Planning• 2018• Society for Neuroscience
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Periodicals

Wood modification technologies - a review

The market for new durable products of modified wood has increased substantially during the last few years, especially in Europe. This increased interest depends partly on the restricted use of toxic preservatives due to increased environmental concern, as well as the need for reduced maintenance for wood products that are mainly for exterior use. Furthermore, as sustainability becomes a greater concern, the environmental impact of construction and interior materials should be included in planning by considering the entire life cycle and embodied energy of the materials used. As a result, wood modification has been implemented to improve the intrinsic properties of wood, widen the range of sawn timber applications, and acquire the form and functionality desired by engineers, without bringing environmental friendliness into question. The different wood modification processes are at various stages of development, and the challenges that must be overcome to expand to industrial applications differ amongst them. In this paper, three groups of wood modification processes are discussed and exemplified with modified wood products that have been newly introduced to the market: (i) chemical processing (acetylation, furfurylation, resin impregnation etc.); (ii) thermo-hydro processing (thermal treatment); and (iii) thermo-hydro-mechanical processing (surface densification). Building on these examples, the paper will discuss the environmental impact assessment of modification processes and further development needs.

Architecture & Planning• 2017
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Report on the development of the Advanced Encryption Standard (AES)

In 1997, the National Institute of Standards and Technology (NIST) initiated a process to select a symmetric-key encryption algorithm to be used to protect sensitive (unclassified) Federal information in furtherance of NIST's statutory responsibilities. In 1998, NIST announced the acceptance of 15 candidate algorithms and requested the assistance of the cryptographic research community in analyzing the candidates. This analysis included an initial examination of the security and efficiency characteristics for each algorithm. NIST reviewed the results of this preliminary research and selected MARS, RC™, Rijndael, Serpent and Twofish as finalists. Having reviewed further public analysis of the finalists, NIST has decided to propose Rijndael as the Advanced Encryption Standard (AES). The research results and rationale for this selection are documented in this report.

Architecture & Planning• 2001• The National Institute of Standards and Technology
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The default mode network and social understanding of others: what do brain connectivity studies tell us

The Default Mode Network (DMN) has been found to be involved in various domains of cognitive and social processing. The present article will review brain connectivity results related to the DMN in the fields of social understanding of others: emotion perception, empathy, theory of mind, and morality. Most of the reviewed studies focused on healthy subjects with no neurological and psychiatric disease, but some studies on patients with autism and psychopathy will also be discussed. Common results show that the medial prefrontal cortex (MPFC) plays a key role in the social understanding of others, and the subregions of the MPFC contribute differently to this function according to their roles in different subsystems of the DMN. At the bottom, the ventral MPFC in the medial temporal lobe (MTL) subsystem and its connections with emotion regions are mainly associated with emotion engagement during social interactions. Above, the anterior MPFC (aMPFC) in the cortical midline structures (CMS) and its connections with posterior and anterior cingulate cortex contribute mostly to making self-other distinctions. At the top, the dorsal MPFC (dMPFC) in the dMPFC subsystem and its connection with the temporo-parietal junction (TPJ) are primarily related to the understanding of other's mental states. As behaviors become more complex, the related regions in frontal cortex are located higher. This reflects the transfer of information processing from automatic to cognitive processes with the increase of the complexity of social interaction. Besides the MPFC and TPJ, the connectivities of posterior cingulate cortex (PCC) also show some changes during tasks from the four social fields. These results indicate that the DMN is indispensable in the social understanding of others.

Architecture & Planning• 2014• Frontiers Media
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A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification

Brain cancer classification is an important step that depends on the physician's knowledge and experience. An automated tumor classification system is very essential to support radiologists and physicians to identify brain tumors. However, the accuracy of current systems needs to be improved for suitable treatments. In this paper, we propose a hybrid feature extraction method with a regularized extreme learning machine (RELM) for developing an accurate brain tumor classification approach. The approach starts by preprocessing the brain images by using a min-max normalization rule to enhance the contrast of brain edges and regions. Then, the brain tumor features are extracted based on a hybrid method of feature extraction. Finally, a RELM is used for classifying the type of brain tumor. To evaluate and compare the proposed approach, a set of experiments is conducted on a new public dataset of brain images. The experimental results proved that the approach is more effective compared with the existing state-of-the-art approaches, and the performance in terms of classification accuracy improved from 91.51% to 94.233% for the experiment of the random holdout technique.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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Integrated genomics, physiology and breeding approaches for improving drought tolerance in crops

Drought is one of the most serious production constraint for world agriculture and is projected to worsen with anticipated climate change. Inter-disciplinary scientists have been trying to understand and dissect the mechanisms of plant tolerance to drought stress using a variety of approaches; however, success has been limited. Modern genomics and genetic approaches coupled with advances in precise phenotyping and breeding methodologies are expected to more effectively unravel the genes and metabolic pathways that confer drought tolerance in crops. This article discusses the most recent advances in plant physiology for precision phenotyping of drought response, a vital step before implementing the genetic and molecular-physiological strategies to unravel the complex multilayered drought tolerance mechanism and further exploration using molecular breeding approaches for crop improvement. Emphasis has been given to molecular dissection of drought tolerance by QTL or gene discovery through linkage and association mapping, QTL cloning, candidate gene identification, transcriptomics and functional genomics. Molecular breeding approaches such as marker-assisted backcrossing, marker-assisted recurrent selection and genome-wide selection have been suggested to be integrated in crop improvement strategies to develop drought-tolerant cultivars that will enhance food security in the context of a changing and more variable climate.

Architecture & Planning• 2012• Springer Science+Business Media
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Operational High Resolution Land Cover Map Production at the Country Scale Using Satellite Image Time Series

A detailed and accurate knowledge of land cover is crucial for many scientific and operational applications, and as such, it has been identified as an Essential Climate Variable. This accurate knowledge needs frequent updates. This paper presents a methodology for the fully automatic production of land cover maps at country scale using high resolution optical image time series which is based on supervised classification and uses existing databases as reference data for training and validation. The originality of the approach resides in the use of all available image data, a simple pre-processing step leading to a homogeneous set of acquisition dates over the whole area and the use of a supervised classifier which is robust to errors in the reference data. The produced maps have a kappa coefficient of 0.86 with 17 land cover classes. The processing is efficient, allowing a fast delivery of the maps after the acquisition of the image data, does not need expensive field surveys for model calibration and validation, nor human operators for decision making, and uses open and freely available imagery. The land cover maps are provided with a confidence map which gives information at the pixel level about the expected quality of the result.

Architecture & Planning• 2017• Multidisciplinary Digital Publishing Institute
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Sarcoidosis: A Clinical Overview from Symptoms to Diagnosis

Sarcoidosis is a multi-system disease of unknown etiology characterized by the formation of granulomas in various organs. It affects people of all ethnic backgrounds and occurs at any time of life but is more frequent in African Americans and Scandinavians and in adults between 30 and 50 years of age. Sarcoidosis can affect any organ with a frequency varying according to ethnicity, sex and age. Intrathoracic involvement occurs in 90% of patients with symmetrical bilateral hilar adenopathy and/or diffuse lung micronodules, mainly along the lymphatic structures which are the most affected system. Among extrapulmonary manifestations, skin lesions, uveitis, liver or splenic involvement, peripheral and abdominal lymphadenopathy and peripheral arthritis are the most frequent with a prevalence of 25-50%. Finally, cardiac and neurological manifestations which can be the initial manifestation of sarcoidosis, as can be bilateral parotitis, nasosinusal or laryngeal signs, hypercalcemia and renal dysfunction, affect less than 10% of patients. The diagnosis is not standardized but is based on three major criteria: a compatible clinical and/or radiological presentation, the histological evidence of non-necrotizing granulomatous inflammation in one or more tissues and the exclusion of alternative causes of granulomatous disease. Certain clinical features are considered to be highly specific of the disease (e.g., Löfgren's syndrome, lupus pernio, Heerfordt's syndrome) and do not require histological confirmation. New diagnostic guidelines were recently published. Specific clinical criteria have been developed for the diagnosis of cardiac, neurological and ocular sarcoidosis. This article focuses on the clinical presentation and the common differentials that need to be considered when appropriate.

Architecture & Planning• 2021• Multidisciplinary Digital Publishing Institute
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Taking Drones to the Next Level: Cooperative Distributed Unmanned-Aerial-Vehicular Networks for Small and Mini Drones

Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications. However, the cooperation of small and mini drones in a network is capable of further improving the performance and the coverage area of UAVs. There are numerous new challenges to be solved before the widespread introduction of multi-UAV-based heterogeneous flying ad hoc networks (FANET), including the formulation of a stable network structure. Meanwhile, an efficient gateway-selection algorithm and management mechanism is required. However, the stability control of the hierarchical UAV network guarantees the efficient collaboration of the drones. In this article, we begin by surveying the FANET structure and its protocol architecture. Then, a variety of distributed gateway-selection algorithms and cloud-based stability-control mechanisms are addressed, complemented by a range of open challenges.

Architecture & Planning• 2017• Institute of Electrical and Electronics Engineers
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Behavioural nudges increase COVID-19 vaccinations

Abstract Enhancing vaccine uptake is a critical public health challenge 1 . Overcoming vaccine hesitancy 2,3 and failure to follow through on vaccination intentions 3 requires effective communication strategies 3,4 . Here we present two sequential randomized controlled trials to test the effect of behavioural interventions on the uptake of COVID-19 vaccines. We designed text-based reminders that make vaccination salient and easy, and delivered them to participants drawn from a healthcare system one day (first randomized controlled trial) ( n = 93,354 participants; clinicaltrials number NCT04800965) and eight days (second randomized controlled trial) ( n = 67,092 individuals; clinicaltrials number NCT04801524) after they received a notification of vaccine eligibility. The first reminder boosted appointment and vaccination rates within the healthcare system by 6.07 (84%) and 3.57 (26%) percentage points, respectively; the second reminder increased those outcomes by 1.65 and 1.06 percentage points, respectively. The first reminder had a greater effect when it was designed to make participants feel ownership of the vaccine dose. However, we found no evidence that combining the first reminder with a video-based information intervention designed to address vaccine hesitancy heightened its effect. We performed online studies ( n = 3,181 participants) to examine vaccination intentions, which revealed patterns that diverged from those of the first randomized controlled trial; this underscores the importance of pilot-testing interventions in the field. Our findings inform the design of behavioural nudges for promoting health decisions 5 , and highlight the value of making vaccination easy and inducing feelings of ownership over vaccines.

Architecture & Planning• 2021• Nature Portfolio
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Components of expertise

This article discusses frameworks for studying expertise at the knowledge level and knowledge-use level. It reviews existing approaches such as inference structures, the distinction between deep and surface knowledge, problem-solving methods, and generic tasks. A new synthesis is put forward in the form of a componential framework that stresses modularity and an analysis of the pragmatic constraints on the task. The analysis of a rule from an existing expert system (the Dipmeter Advisor) is used to illustrate the framework.

Architecture & Planning• 1990• Consejo Superior de Investigaciones Científicas
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The Simoa HD-1 Analyzer: A Novel Fully Automated Digital Immunoassay Analyzer with Single-Molecule Sensitivity and Multiplexing

Disease detection at the molecular level is driving the emerging revolution of early diagnosis and treatment. A challenge facing the field is that protein biomarkers for early diagnosis can be present in very low abundance. The lower limit of detection with conventional immunoassay technology is the upper femtomolar range (10(-13) M). Digital immunoassay technology has improved detection sensitivity three logs, to the attomolar range (10(-16) M). This capability has the potential to open new advances in diagnostics and therapeutics, but such technologies have been relegated to manual procedures that are not well suited for efficient routine use. We describe a new laboratory instrument that provides full automation of single-molecule array (Simoa) technology for digital immunoassays. The instrument is capable of single-molecule sensitivity and multiplexing with short turnaround times and a throughput of 66 samples/h. Singleplex and multiplexed digital immunoassays were developed for 16 proteins of interest in cardiovascular, cancer, infectious disease, neurology, and inflammation research. The average sensitivity improvement of the Simoa immunoassays versus conventional ELISA was >1200-fold, with coefficients of variation of <10%. The potential of digital immunoassays to advance human diagnostics was illustrated in two clinical areas: traumatic brain injury and early detection of infectious disease.

Architecture & Planning• 2015• Elsevier BV
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