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in Architecture & Planning
Periodicals

Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks

Abstract. Rainfall–runoff modelling is one of the key challenges in the field of hydrology. Various approaches exist, ranging from physically based over conceptual to fully data-driven models. In this paper, we propose a novel data-driven approach, using the Long Short-Term Memory (LSTM) network, a special type of recurrent neural network. The advantage of the LSTM is its ability to learn long-term dependencies between the provided input and output of the network, which are essential for modelling storage effects in e.g. catchments with snow influence. We use 241 catchments of the freely available CAMELS data set to test our approach and also compare the results to the well-known Sacramento Soil Moisture Accounting Model (SAC-SMA) coupled with the Snow-17 snow routine. We also show the potential of the LSTM as a regional hydrological model in which one model predicts the discharge for a variety of catchments. In our last experiment, we show the possibility to transfer process understanding, learned at regional scale, to individual catchments and thereby increasing model performance when compared to a LSTM trained only on the data of single catchments. Using this approach, we were able to achieve better model performance as the SAC-SMA + Snow-17, which underlines the potential of the LSTM for hydrological modelling applications.

Architecture & Planning• 2018• Copernicus Publications
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U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications

U-net is an image segmentation technique developed primarily for image segmentation tasks. These traits provide U-net with a high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for segmentation tasks in medical imaging. The success of U-net is evident in its widespread use in nearly all major image modalities, from CT scans and MRI to X-rays and microscopy. Furthermore, while U-net is largely a segmentation tool, there have been instances of the use of U-net in other applications. Given that U-net's potential is still increasing, this narrative literature review examines the numerous developments and breakthroughs in the U-net architecture and provides observations on recent trends. We also discuss the many innovations that have advanced in deep learning and discuss how these tools facilitate U-net. In addition, we review the different image modalities and application areas that have been enhanced by U-net.

Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
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On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial deployment, providing users with new services, improved user experiences as well as a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified to stimulate the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed.

Architecture & Planning• 2023• Institute of Electrical and Electronics Engineers
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Network Applications of Bloom Filters: A Survey

A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Bloom filters allow false positives but the space savings often outweigh this drawback when the probability of an error is controlled. Bloom filters have been used in database applications since the 1970s, but only in recent years have they become popular in the networking literature. The aim of this paper is to survey the ways in which Bloom filters have been used and modified in a variety of network problems, with the aim of providing a unified mathematical and practical framework for understanding them and stimulating their use in future applications.

Architecture & Planning• 2004• Taylor & Francis
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Q<scp>uantum</scp> ESPRESSO toward the exascale

Quantum ESPRESSO is an open-source distribution of computer codes for quantum-mechanical materials modeling, based on density-functional theory, pseudopotentials, and plane waves, and renowned for its performance on a wide range of hardware architectures, from laptops to massively parallel computers, as well as for the breadth of its applications. In this paper, we present a motivation and brief review of the ongoing effort to port Quantum ESPRESSO onto heterogeneous architectures based on hardware accelerators, which will overcome the energy constraints that are currently hindering the way toward exascale computing.

Architecture & Planning• 2020• American Institute of Physics
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CONSORT-EHEALTH: Improving and Standardizing Evaluation Reports of Web-based and Mobile Health Interventions

BACKGROUND: Web-based and mobile health interventions (also called "Internet interventions" or "ehealth/mhealth interventions") are tools or treatments, typically behaviorally based, that are operationalized and transformed for delivery via the Internet or mobile platforms. These include electronic tools for patients, informal caregivers, healthy consumers, and health care providers. The "Consolidated Standards of Reporting Trials" (CONSORT) was developed to improve the suboptimal reporting of randomized controlled trials (RCTs). While broadly the CONSORT statement can be applied to provide guidance on how ehealth and mhealth trials should be reported, RCTs of web-based interventions pose very specific issues and challenges, in particular related to reporting sufficient details of the intervention to allow replication and theory-building. OBJECTIVE: To develop a checklist, dubbed CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile HEalth Applications and onLine TeleHealth), as an extension of the CONSORT statement that provides guidance for authors of ehealth and mhealth interventions. METHODS: A literature review was conducted, followed by a survey among ehealth experts and a workshop. RESULTS: An instrument and checklist was constructed as an extension of the CONSORT statement. The instrument has been adopted by the Journal of Medical Internet Research (JMIR) and authors of ehealth RCTs are required to submit an electronic checklist explaining how they addressed each subitem. CONCLUSIONS: CONSORT-EHEALTH has the potential to improve reporting and provides a basis for evaluating the validity and applicability of ehealth trials. Subitems describing how the intervention should be reported can also be used for non-RCT evaluation reports. As part of the development process, an evaluation component is essential, therefore feedback from authors will be solicited, and a before-after study will evaluate whether reporting has been improved.

Architecture & Planning• 2011• JMIR Publications
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From Monocytes to M1/M2 Macrophages: Phenotypical vs. Functional Differentiation

Studies on monocyte and macrophage biology and differentiation have revealed the pleiotropic activities of these cells. Macrophages are tissue sentinels that maintain tissue integrity by eliminating/repairing damaged cells and matrices. In this M2-like mode, they can also promote tumor growth. Conversely, M1-like macrophages are key effector cells for the elimination of pathogens, virally infected, and cancer cells. Macrophage differentiation from monocytes occurs in the tissue in concomitance with the acquisition of a functional phenotype that depends on microenvironmental signals, thereby accounting for the many and apparently opposed macrophage functions. Many questions arise. When monocytes differentiate into macrophages in a tissue (concomitantly adopting a specific functional program, M1 or M2), do they all die during the inflammatory reaction, or do some of them survive? Do those that survive become quiescent tissue macrophages, able to react as naïve cells to a new challenge? Or, do monocyte-derived tissue macrophages conserve a "memory" of their past inflammatory activation? This review will address some of these important questions under the general framework of the role of monocytes and macrophages in the initiation, development, resolution, and chronicization of inflammation.

Architecture & Planning• 2014• Frontiers Media
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The Biodiversity of the Mediterranean Sea: Estimates, Patterns, and Threats

The Mediterranean Sea is a marine biodiversity hot spot. Here we combined an extensive literature analysis with expert opinions to update publicly available estimates of major taxa in this marine ecosystem and to revise and update several species lists. We also assessed overall spatial and temporal patterns of species diversity and identified major changes and threats. Our results listed approximately 17,000 marine species occurring in the Mediterranean Sea. However, our estimates of marine diversity are still incomplete as yet-undescribed species will be added in the future. Diversity for microbes is substantially underestimated, and the deep-sea areas and portions of the southern and eastern region are still poorly known. In addition, the invasion of alien species is a crucial factor that will continue to change the biodiversity of the Mediterranean, mainly in its eastern basin that can spread rapidly northwards and westwards due to the warming of the Mediterranean Sea. Spatial patterns showed a general decrease in biodiversity from northwestern to southeastern regions following a gradient of production, with some exceptions and caution due to gaps in our knowledge of the biota along the southern and eastern rims. Biodiversity was also generally higher in coastal areas and continental shelves, and decreases with depth. Temporal trends indicated that overexploitation and habitat loss have been the main human drivers of historical changes in biodiversity. At present, habitat loss and degradation, followed by fishing impacts, pollution, climate change, eutrophication, and the establishment of alien species are the most important threats and affect the greatest number of taxonomic groups. All these impacts are expected to grow in importance in the future, especially climate change and habitat degradation. The spatial identification of hot spots highlighted the ecological importance of most of the western Mediterranean shelves (and in particular, the Strait of Gibraltar and the adjacent Alboran Sea), western African coast, the Adriatic, and the Aegean Sea, which show high concentrations of endangered, threatened, or vulnerable species. The Levantine Basin, severely impacted by the invasion of species, is endangered as well. This abstract has been translated to other languages (File S1).

Architecture & Planning• 2010• Public Library of Science
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Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology

Metadata and data have become a regular currency for citizens to pay for their communication services and security—a trade-off that has nestled into the comfort zone of most people. This article deconstructs the ideological grounds of datafication. Datafication is rooted in problematic ontological and epistemological claims. As part of a larger social media logic, it shows characteristics of a widespread secular belief. Dataism, as this conviction is called, is so successful because masses of people — naively or unwittingly — trust their personal information to corporate platforms. The notion of trust becomes more problematic because people’s faith is extended to other public institutions (e.g. academic research and law enforcement) that handle their (meta)data. The interlocking of government, business, and academia in the adaptation of this ideology makes us want to look more critically at the entire ecosystem of connective media.

Architecture & Planning• 2014• Surveillance Studies Network
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The Politics, Power, and Pathologies of International Organizations

International Relations scholars have vigorous theories to explain why international organizations (IOs) are created, but they have paid little attention to IO behavior and whether IOs actually do what their creators intend. This blind spot flows logically from the economic theories of organization that have dominated the study of international institutions and regimes. To recover the agency and autonomy of IOs, we offer a constructivist approach. Building on Max Weber's well-known analysis of bureaucracy, we argue that IOs are much more powerful than even neoliberals have argued, and that the same characteristics of bureaucracy that make IOs powerful can also make them prone to dysfunctional behavior. IOs are powerful because, like all bureaucracies, they make rules, and, in so doing, they create social knowledge. IOs deploy this knowledge in ways that define shared international tasks, create new categories of actors, form new interests for actors, and transfer new models of political organization around the world. However, the same normative valuation on impersonal rules that defines bureaucracies and makes them powerful in modern life can also make them unresponsive to their environments, obsessed with their own rules at the expense of primary missions, and ultimately produce inefficient and self-defeating behavior. Sociological and constructivist approaches thus allow us to expand the research agenda beyond IO creation and to ask important questions about the consequences of global bureaucratization and the effects of IOs in world politics.

Architecture & Planning• 1999• University of Cambridge
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The Sorcerer II Global Ocean Sampling Expedition: Northwest Atlantic through Eastern Tropical Pacific

The world's oceans contain a complex mixture of micro-organisms that are for the most part, uncharacterized both genetically and biochemically. We report here a metagenomic study of the marine planktonic microbiota in which surface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition. These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal and ending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp). Though a few major microbial clades dominate the planktonic marine niche, the dataset contains great diversity with 85% of the assembled sequence and 57% of the unassembled data being unique at a 98% sequence identity cutoff. Using the metadata associated with each sample and sequencing library, we developed new comparative genomic and assembly methods. One comparative genomic method, termed "fragment recruitment," addressed questions of genome structure, evolution, and taxonomic or phylogenetic diversity, as well as the biochemical diversity of genes and gene families. A second method, termed "extreme assembly," made possible the assembly and reconstruction of large segments of abundant but clearly nonclonal organisms. Within all abundant populations analyzed, we found extensive intra-ribotype diversity in several forms: (1) extensive sequence variation within orthologous regions throughout a given genome; despite coverage of individual ribotypes approaching 500-fold, most individual sequencing reads are unique; (2) numerous changes in gene content some with direct adaptive implications; and (3) hypervariable genomic islands that are too variable to assemble. The intra-ribotype diversity is organized into genetically isolated populations that have overlapping but independent distributions, implying distinct environmental preference. We present novel methods for measuring the genomic similarity between metagenomic samples and show how they may be grouped into several community types. Specific functional adaptations can be identified both within individual ribotypes and across the entire community, including proteorhodopsin spectral tuning and the presence or absence of the phosphate-binding gene PstS.

Architecture & Planning• 2007• Public Library of Science
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Event-Based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of μs), very high dynamic range (140 dB versus 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world.

Architecture & Planning• 2020• IEEE Computer Society
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CellProfiler 3.0: Next-generation image processing for biology

CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProfiler's infrastructure is greatly improved, and we provide a protocol for cloud-based, large-scale image processing. New plugins enable running pretrained deep learning models on images. Designed by and for biologists, CellProfiler equips researchers with powerful computational tools via a well-documented user interface, empowering biologists in all fields to create quantitative, reproducible image analysis workflows.

Architecture & Planning• 2018• Public Library of Science
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Epithelial-mesenchymal transition and its implications for fibrosis

Epithelial to mesenchymal transition (EMT) is a central mechanism for diversifying the cells found in complex tissues. This dynamic process helps organize the formation of the body plan, and while EMT is well studied in the context of embryonic development, it also plays a role in the genesis of fibroblasts during organ fibrosis in adult tissues. Emerging evidence from studies of renal fibrosis suggests that more than a third of all disease-related fibroblasts originate from tubular epithelia at the site of injury. This review highlights recent advances in the process of EMT signaling in health and disease and how it may be attenuated or reversed by selective cytokines and growth factors.

Architecture & Planning• 2003• American Society for Clinical Investigation
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Pymoo: Multi-Objective Optimization in Python

Python has become the programming language of choice for research and industry projects related to data science, machine learning, and deep learning. Since optimization is an inherent part of these research fields, more optimization related frameworks have arisen in the past few years. Only a few of them support optimization of multiple conflicting objectives at a time, but do not provide comprehensive tools for a complete multi-objective optimization task. To address this issue, we have developed pymoo, a multi-objective optimization framework in Python. We provide a guide to getting started with our framework by demonstrating the implementation of an exemplary constrained multi-objective optimization scenario. Moreover, we give a high-level overview of the architecture of pymoo to show its capabilities followed by an explanation of each module and its corresponding sub-modules. The implementations in our framework are customizable and algorithms can be modified/extended by supplying custom operators. Moreover, a variety of single, multi- and many-objective test problems are provided and gradients can be retrieved by automatic differentiation out of the box. Also, pymoo addresses practical needs, such as the parallelization of function evaluations, methods to visualize low and high-dimensional spaces, and tools for multi-criteria decision making. For more information about pymoo, readers are encouraged to visit: https://pymoo.org.

Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
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FREQUENCY EFFECTS IN LANGUAGE PROCESSING

This article shows how language processing is intimately tuned to input frequency. Examples are given of frequency effects in the processing of phonology, phonotactics, reading, spelling, lexis, morphosyntax, formulaic language, language comprehension, grammaticality, sentence production, and syntax. The implications of these effects for the representations and developmental sequence of SLA are discussed. Usage-based theories hold that the acquisition of language is exemplar based. It is the piecemeal learning of many thousands of constructions and the frequency-biased abstraction of regularities within them. Determinants of pattern productivity include the power law of practice, cue competition and constraint satisfaction, connectionist learning, and effects of type and token frequency. The regularities of language emerge from experience as categories and prototypical patterns. The typical route of emergence of constructions is from formula, through low-scope pattern, to construction. Frequency plays a large part in explaining sociolinguistic variation and language change. Learners' sensitivity to frequency in all these domains has implications for theories of implicit and explicit learning and their interactions. The review concludes by considering the history of frequency as an explanatory concept in theoretical and applied linguistics, its 40 years of exile, and its necessary reinstatement as a bridging variable that binds the different schools of language acquisition research.

Architecture & Planning• 2002• Cambridge University Press
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Cellular architecture and key technologies for 5G wireless communication networks

The fourth generation wireless communication systems have been deployed or are soon to be deployed in many countries. However, with an explosion of wireless mobile devices and services, there are still some challenges that cannot be accommodated even by 4G, such as the spectrum crisis and high energy consumption. Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications and therefore have started research on fifth generation wireless systems that are expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications. Future challenges facing these potential technologies are also discussed.

Architecture & Planning• 2014• Institute of Electrical and Electronics Engineers
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Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing

With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications and services, spanning from personal assistant to recommendation systems to video/audio surveillance. More recently, with the proliferation of mobile computing and Internet of Things (IoT), billions of mobile and IoT devices are connected to the Internet, generating zillions bytes of data at the network edge. Driving by this trend, there is an urgent need to push the AI frontiers to the network edge so as to fully unleash the potential of the edge big data. To meet this demand, edge computing, an emerging paradigm that pushes computing tasks and services from the network core to the network edge, has been widely recognized as a promising solution. The resulted new interdiscipline, edge AI or edge intelligence (EI), is beginning to receive a tremendous amount of interest. However, research on EI is still in its infancy stage, and a dedicated venue for exchanging the recent advances of EI is highly desired by both the computer system and AI communities. To this end, we conduct a comprehensive survey of the recent research efforts on EI. Specifically, we first review the background and motivation for AI running at the network edge. We then provide an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning model toward training/inference at the network edge. Finally, we discuss future research opportunities on EI. We believe that this survey will elicit escalating attentions, stimulate fruitful discussions, and inspire further research ideas on EI.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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The Increasing Trend in Caesarean Section Rates: Global, Regional and National Estimates: 1990-2014

BACKGROUND: Caesarean section (CS) rates continue to evoke worldwide concern because of their steady increase, lack of consensus on the appropriate CS rate and the associated additional short- and long-term risks and costs. We present the latest CS rates and trends over the last 24 years. METHODS: We collected nationally-representative data on CS rates between 1990 to 2014 and calculated regional and subregional weighted averages. We conducted a longitudinal analysis calculating differences in CS rates as absolute change and as the average annual rate of increase (AARI). RESULTS: According to the latest data from 150 countries, currently 18.6% of all births occur by CS, ranging from 6% to 27.2% in the least and most developed regions, respectively. Latin America and the Caribbean region has the highest CS rates (40.5%), followed by Northern America (32.3%), Oceania (31.1%), Europe (25%), Asia (19.2%) and Africa (7.3%). Based on the data from 121 countries, the trend analysis showed that between 1990 and 2014, the global average CS rate increased 12.4% (from 6.7% to 19.1%) with an average annual rate of increase of 4.4%. The largest absolute increases occurred in Latin America and the Caribbean (19.4%, from 22.8% to 42.2%), followed by Asia (15.1%, from 4.4% to 19.5%), Oceania (14.1%, from 18.5% to 32.6%), Europe (13.8%, from 11.2% to 25%), Northern America (10%, from 22.3% to 32.3%) and Africa (4.5%, from 2.9% to 7.4%). Asia and Northern America were the regions with the highest and lowest average annual rate of increase (6.4% and 1.6%, respectively). CONCLUSION: The use of CS worldwide has increased to unprecedented levels although the gap between higher- and lower-resource settings remains. The information presented is essential to inform policy and global and regional strategies aimed at optimizing the use of CS.

Architecture & Planning• 2016• Public Library of Science
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The<i>Herschel</i>-SPIRE instrument and its in-flight performance

The Spectral and Photometric Imaging REceiver (SPIRE), is the <i>Herschel<i/> Space Observatory`s submillimetre camera and spectrometer. It contains a three-band imaging photometer operating at 250, 350 and 500 <i>μ<i/>m, and an imaging Fourier-transform spectrometer (FTS) which covers simultaneously its whole operating range of 194–671 <i>μ<i/>m (447–1550 GHz). The SPIRE detectors are arrays of feedhorn-coupled bolometers cooled to 0.3 K. The photometer has a field of view of 4´× 8´, observed simultaneously in the three spectral bands. Its main operating mode is scan-mapping, whereby the field of view is scanned across the sky to achieve full spatial sampling and to cover large areas if desired. The spectrometer has an approximately circular field of view with a diameter of 2.6´. The spectral resolution can be adjusted between 1.2 and 25 GHz by changing the stroke length of the FTS scan mirror. Its main operating mode involves a fixed telescope pointing with multiple scans of the FTS mirror to acquire spectral data. For extended source measurements, multiple position offsets are implemented by means of an internal beam steering mirror to achieve the desired spatial sampling and by rastering of the telescope pointing to map areas larger than the field of view. The SPIRE instrument consists of a cold focal plane unit located inside the <i>Herschel<i/> cryostat and warm electronics units, located on the spacecraft Service Module, for instrument control and data handling. Science data are transmitted to Earth with no on-board data compression, and processed by automatic pipelines to produce calibrated science products. The in-flight performance of the instrument matches or exceeds predictions based on pre-launch testing and modelling: the photometer sensitivity is comparable to or slightly better than estimated pre-launch, and the spectrometer sensitivity is also better by a factor of 1.5–2.

Architecture & Planning• 2010• EDP Sciences
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI

Recently, artificial intelligence and machine learning in general have demonstrated remarkable performances in many tasks, from image processing to natural language processing, especially with the advent of deep learning (DL). Along with research progress, they have encroached upon many different fields and disciplines. Some of them require high level of accountability and thus transparency, for example, the medical sector. Explanations for machine decisions and predictions are thus needed to justify their reliability. This requires greater interpretability, which often means we need to understand the mechanism underlying the algorithms. Unfortunately, the blackbox nature of the DL is still unresolved, and many machine decisions are still poorly understood. We provide a review on interpretabilities suggested by different research works and categorize them. The different categories show different dimensions in interpretability research, from approaches that provide "obviously" interpretable information to the studies of complex patterns. By applying the same categorization to interpretability in medical research, it is hoped that: 1) clinicians and practitioners can subsequently approach these methods with caution; 2) insight into interpretability will be born with more considerations for medical practices; and 3) initiatives to push forward data-based, mathematically grounded, and technically grounded medical education are encouraged.

Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
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The brain basis of emotion: A meta-analytic review

Researchers have wondered how the brain creates emotions since the early days of psychological science. With a surge of studies in affective neuroscience in recent decades, scientists are poised to answer this question. In this target article, we present a meta-analytic summary of the neuroimaging literature on human emotion. We compare the locationist approach (i.e., the hypothesis that discrete emotion categories consistently and specifically correspond to distinct brain regions) with the psychological constructionist approach (i.e., the hypothesis that discrete emotion categories are constructed of more general brain networks not specific to those categories) to better understand the brain basis of emotion. We review both locationist and psychological constructionist hypotheses of brain-emotion correspondence and report meta-analytic findings bearing on these hypotheses. Overall, we found little evidence that discrete emotion categories can be consistently and specifically localized to distinct brain regions. Instead, we found evidence that is consistent with a psychological constructionist approach to the mind: A set of interacting brain regions commonly involved in basic psychological operations of both an emotional and non-emotional nature are active during emotion experience and perception across a range of discrete emotion categories.

Architecture & Planning• 2012• Cambridge University Press
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A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)

Motivated by the vast amount of information that is rapidly accumulating about the human brain in digital form, we embarked upon a program in 1992 to develop a four-dimensional probabilistic atlas and reference system for the human brain. Through an International Consortium for Brain Mapping (ICBM) a dataset is being collected that includes 7000 subjects between the ages of eighteen and ninety years and including 342 mono- and dizygotic twins. Data on each subject includes detailed demographic, clinical, behavioural and imaging information. DNA has been collected for genotyping from 5800 subjects. A component of the programme uses post-mortem tissue to determine the probabilistic distribution of microscopic cyto- and chemoarchitectural regions in the human brain. This, combined with macroscopic information about structure and function derived from subjects in vivo, provides the first large scale opportunity to gain meaningful insights into the concordance or discordance in micro- and macroscopic structure and function. The philosophy, strategy, algorithm development, data acquisition techniques and validation methods are described in this report along with database structures. Examples of results are described for the normal adult human brain as well as examples in patients with Alzheimer's disease and multiple sclerosis. The ability to quantify the variance of the human brain as a function of age in a large population of subjects for whom data is also available about their genetic composition and behaviour will allow for the first assessment of cerebral genotype-phenotype-behavioural correlations in humans to take place in a population this large. This approach and its application should provide new insights and opportunities for investigators interested in basic neuroscience, clinical diagnostics and the evaluation of neuropsychiatric disorders in patients.

Architecture & Planning• 2001• Royal Society
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