Periodicals
Functional traits as indicators of biodiversity response to land use changes across ecosystems and organisms
[no abstract]
Architecture & Planning• 2010• Springer Science+Business Media
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Periodicals
Recurrent Neural Networks: A Comprehensive Review of Architectures, Variants, and Applications
Recurrent neural networks (RNNs) have significantly advanced the field of machine learning (ML) by enabling the effective processing of sequential data. This paper provides a comprehensive review of RNNs and their applications, highlighting advancements in architectures, such as long short-term memory (LSTM) networks, gated recurrent units (GRUs), bidirectional LSTM (BiLSTM), echo state networks (ESNs), peephole LSTM, and stacked LSTM. The study examines the application of RNNs to different domains, including natural language processing (NLP), speech recognition, time series forecasting, autonomous vehicles, and anomaly detection. Additionally, the study discusses recent innovations, such as the integration of attention mechanisms and the development of hybrid models that combine RNNs with convolutional neural networks (CNNs) and transformer architectures. This review aims to provide ML researchers and practitioners with a comprehensive overview of the current state and future directions of RNN research.
Architecture & Planning• 2024• Multidisciplinary Digital Publishing Institute
Periodicals
Why Are Some Population Interventions for Diet and Obesity More Equitable and Effective Than Others? The Role of Individual Agency
We now find ourselves in a world in which one in three adults is overweight or obese Unhealthy diets are an important determinant of overweight and obesity and also contribute directly to a variety of other causes of disability and death. In fact, together with physical inactivity, dietary risk factors are responsible for 10% of disability-adjusted life years lost globally Like many risk factors, unhealthy diets are not evenly distributed in the population. In most developed countries, and increasingly in developing countries too, obesity and unhealthy diets are more common in more socioeconomically disadvantaged groups Socioeconomic inequalities in health and disease are at least partly due to these inequalities in diet and obesity.
Architecture & Planning• 2016• Public Library of Science
Periodicals
Artificial General Intelligence: Concept, State of the Art, and Future Prospects
Abstract In recent years broad community of researchers has emerged, focusing on the original ambitious goals of the AI field - the creation and study of software or hardware systems with general intelligence comparable to, and ultimately perhaps greater than, that of human beings. This paper surveys this diverse community and its progress. Approaches to defining the concept of Artificial General Intelligence (AGI) are reviewed including mathematical formalisms, engineering, and biology inspired perspectives. The spectrum of designs for AGI systems includes systems with symbolic, emergentist, hybrid and universalist characteristics. Metrics for general intelligence are evaluated, with a conclusion that, although metrics for assessing the achievement of human-level AGI may be relatively straightforward (e.g. the Turing Test, or a robot that can graduate from elementary school or university), metrics for assessing partial progress remain more controversial and problematic.
Architecture & Planning• 2014• De Gruyter
Periodicals
Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges
Vehicles are currently being developed and sold with increasing levels of connectivity and automation. As with all networked computing devices, increased connectivity often results in a heightened risk of a cyber security attack. Furthermore, increased automation exacerbates any risk by increasing the opportunities for the adversary to implement a successful attack. In this paper, a large volume of publicly accessible literature is reviewed and compartmentalized based on the vulnerabilities identified and mitigation techniques developed. This review highlighted that the majority of studies are reactive and vulnerabilities are often discovered by friendly adversaries (white-hat hackers). Many gaps in the knowledge base were identified. Priority should be given to address these knowledge gaps to minimize future cyber security risks in the connected and autonomous vehicle sector.
Architecture & Planning• 2017• Institute of Electrical and Electronics Engineers
Periodicals
A paradigm shift: relationships in trauma-informed mental health services
Trauma-informed approaches emerged partly in response to research demonstrating that trauma is widespread across society, that it is highly correlated with mental health and that this is a costly public health issue. The fundamental shift in providing support using a trauma-informed approach is to move from thinking 'What is wrong with you?' to considering 'What happened to you?'. This article, authored by trauma survivors and service providers, describes trauma-informed approaches to mental healthcare, why they are needed and how barriers can be overcome so that they can be implemented as an organisational change process. It also describes how past trauma can be understood as the cause of mental distress for many service users, how service users can be retraumatised by 'trauma-uninformed' staff and how staff can experience vicariously the service user's trauma and can themselves be traumatised by practices such as restraint and seclusion. Trauma-informed mental healthcare offers opportunities to improve service users' experiences, improve working environments for staff, increase job satisfaction and reduce stress levels by improving the relationships between staff and patients through greater understanding, respect and trust. LEARNING OBJECTIVES: •Appreciate broad-based definitions of trauma•Gain an understanding of what trauma-informed approaches are and why they have emerged, including the potential for (re)traumatisation in the mental health system•Consider how to practise trauma-informed approaches, including in 'trauma-uninformed' organisations, and the potential barriers to and opportunities from doing so. DECLARATION OF INTEREST: A. S. is funded by a National Institute for Health Research (NIHR) Post-Doctoral Fellowship. This article presents independent research partially funded by the NIHR. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR or the Department of Health.
Architecture & Planning• 2018• Cambridge University Press
Periodicals
New Games, New Rules: Big Data and the Changing Context of Strategy
Big data and the mechanisms by which it is produced and disseminated introduce important changes in the ways information is generated and made relevant for organizations. Big data often represents miscellaneous records of the whereabouts of large and shifting online crowds. It is frequently agnostic, in the sense of being produced for generic purposes or purposes different from those sought by big data crunching. It is based on varying formats and modes of communication (e.g., texts, image and sound), raising severe problems of semiotic translation and meaning compatibility. Crucially, the usefulness of big data rests on their steady updatability, a condition that reduces the time span within which this data is useful or relevant. Jointly, these attributes challenge established rules of strategy making as these are manifested in the canons of procuring structured information of lasting value that addresses specific and long-term organizational objectives. The developments underlying big data thus seem to carry important implications for strategy making, and the data and information practices with which strategy has been associated. We conclude by placing the understanding of these changes within the wider social and institutional context of longstanding data practices and the significance they carry for management and organizations.
Architecture & Planning• 2014• SAGE Publishing
Periodicals
Role of Digital Transformation for Achieving Sustainability: Mediated Role of Stakeholders, Key Capabilities, and Technology
Sustainability through digital transformation is essential for contemporary businesses. Embracing sustainability, micro-, small-, and medium-sized enterprises (MSMEs) can gain a competitive advantage, attracting customers and investors who share these values. Moreover, incorporating sustainable practices empowers MSMEs to drive innovation, reduce costs, and enhance their reputation. This study aims to identify how owners or senior managers of MSMEs can initiate a sustainable digital transformation project. A systematic literature review was carried out, including 59 publications from 2019 to 2023. As a result, this research identifies the first steps owners of MSMEs can take to begin the transition by identifying critical organizational capabilities necessary for successful transformation, explores the technologies that can support MSMEs in their sustainability goals, and emphasizes the significance of stakeholders in achieving a successful digital transformation journey. Firstly, owners or senior managers should change the organizational culture to support decisions and strategies focus on sustainability. Secondly, the leading role of stakeholders is in the innovation process that allows businesses to be more competitive locally and globally. Finally, big data is the technology that can provide the most significant benefit to MSMEs because it will enable analyzing data of all kinds and contributes disruptively to decision-making.
Architecture & Planning• 2023• Multidisciplinary Digital Publishing Institute
Periodicals
Multi-Sensor Fusion in Automated Driving: A Survey
With the significant development of practicability in deep learning and the ultra-high-speed information transmission rate of 5G communication technology will overcome the barrier of data transmission on the Internet of Vehicles, automated driving is becoming a pivotal technology affecting the future industry. Sensors are the key to the perception of the outside world in the automated driving system and whose cooperation performance directly determines the safety of automated driving vehicles. In this survey, we mainly discuss the different strategies of multi-sensor fusion in automated driving in recent years. The performance of conventional sensors and the necessity of multi-sensor fusion are analyzed, including radar, LiDAR, camera, ultrasonic, GPS, IMU, and V2X. According to the differences in the latest studies, we divide the fusion strategies into four categories and point out some shortcomings. Sensor fusion is mainly applied for multi-target tracking and environment reconstruction. We discuss the method of establishing a motion model and data association in multi-target tracking. At the end of the paper, we analyzed the deficiencies in the current studies and put forward some suggestions for further improvement in the future. Through this investigation, we hope to analyze the current situation of multi-sensor fusion in the automated driving process and provide more efficient and reliable fusion strategies.
Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
Periodicals
OVERSTORY-IMPOSED HETEROGENEITY IN SOLAR RADIATION AND SOIL MOISTURE IN A SEMIARID WOODLAND
Degradation of semiarid ecosystems is a major environmental problem worldwide, characterized by a reduction in the ratio of herbaceous to woody plant biomass. These ecosystems can be described as a set of canopy patches comprising woody plants and the intercanopy patches that separate them, yielding an overstory with intermediate closure. Field measurements of microclimate at the scale of canopy patches, particularly for near-ground solar radiation and soil moisture, are largely lacking from both nondegraded and degraded ecosystems. We tested for relationships among spatial patterns of the overstory, near-ground solar radiation, and soil moisture in a semiarid piñon–juniper woodland in northern New Mexico that had a highly heterogeneous overstory (≈50% canopy cover) and was not degraded with respect to ground cover and erosion rates. We used measurements taken every 1 m along a 102-m transect—solar radiation indices were estimated monthly and annually using hemispherical photographs, and soil moisture was measured over 4 yr using time-domain reflectometry (TDR)—and analyzed the data using general least squares linear models that accounted for spatial autocorrelation and temporal heteroscedasticity. Time-averages of solar radiation and of soil moisture both were spatially autocorrelated at scales of up to 4 m (P < 0.05), corresponding approximately to the average lengths of both canopy and intercanopy patches and to the scale of spatial autocorrelation in the canopy/intercanopy pattern of the overstory (3 m; P < 0.05). For near-ground solar radiation, we found expected spatial variation between patches (canopy < intercanopy; P < 0.0001) and within patches for centers vs. edges (canopy center < canopy edge and intercanopy center > intercanopy edge; P < 0.0001) and for north vs. south edges (canopy north edge < canopy south edge and intercanopy south edge < intercanopy north edge; P < 0.0001). For soil moisture, canopy locations were significantly drier than intercanopy locations (P < 0.0001), and edge locations were significantly wetter than center locations both overall and within both patch types (P < 0.0001). Spatial heterogeneity in soil mositure was attributed primarily to canopy interception and drip on the basis of large differences in snow cover between canopy and intercanopy locations. Spatial autocorrelation in the residuals for soil moisture of up to 7 m was attributed to transpiration by woody plants at scales corresponding to belowground root distributions. The spatial heterogeneities in near-ground solar radiation and soil moisture are of sufficient magnitude to affect biotic processes of woody and herbaceous plants, such as growth and seedling establishment. Because land degradation problems in semiarid shrublands and woodlands appear to result from differential impacts to intercanopy vs. canopy patches, our results can be used to help design effective mitigation and remediation strategies. More generally, our results demonstrate how the physical presence of woody canopies reinforces spatial heterogeneity in microclimate and, because our site has intermediate closure of the overstory, bridge the gap along a grassland–forest continuum between related studies in relatively open savannas and in forests with nearly closed canopies.
Architecture & Planning• 1997• Wiley
Periodicals
Virtual and augmented reality: Advancing research in consumer marketing
[no abstract]
Architecture & Planning• 2020• Elsevier BV
Periodicals
Phenotyping common beans for adaptation to drought
Common beans (Phaseolus vulgaris L.) originated in the New World and are the grain legume of greatest production for direct human consumption. Common bean production is subject to frequent droughts in highland Mexico, in the Pacific coast of Central America, in northeast Brazil, and in eastern and southern Africa from Ethiopia to South Africa. This article reviews efforts to improve common bean for drought tolerance, referring to genetic diversity for drought response, the physiology of drought tolerance mechanisms, and breeding strategies. Different races of common bean respond differently to drought, with race Durango of highland Mexico being a major source of genes. Sister species of P. vulgaris likewise have unique traits, especially P. acutifolius which is well adapted to dryland conditions. Diverse sources of tolerance may have different mechanisms of plant response, implying the need for different methods of phenotyping to recognize the relevant traits. Practical considerations of field management are discussed including: trial planning; water management; and field preparation.
Architecture & Planning• 2013• Frontiers Media
Periodicals
The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data
The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns.
Architecture & Planning• 2015• Frontiers Media
Periodicals
Altering the course of schizophrenia: progress and perspectives
[no abstract]
Architecture & Planning• 2016• Nature Portfolio
Periodicals
Recent Advances in the Remediation of Textile-Dye-Containing Wastewater: Prioritizing Human Health and Sustainable Wastewater Treatment
Water makes up most of the Earth, although just 0.3% is usable for people and animals. The huge oceans, icecaps, and other non-potable water resources make up the remaining 99.7%. Water quality has declined in recent decades due to pollution from population growth, industry, unplanned urbanization, and poor water management. The textile industry has significant global importance, although it also stands as a major contributor to wastewater generation, leading to water depletion and ecotoxicity. This issue arises from the extensive utilization of harmful chemicals, notably dyes. The main aim of this review article is to combine and assess the impacts of textile wastewater that contains dyes and chemicals, and to examine their potential consequences on human health, aquatic health, and the environment. Moreover, the dedicated section presents an in-depth review of various environmentally sustainable approaches for the management and treatment of wastewater in the textile industry. These approaches encompass bio adsorbents, biological methods, membrane technology, ion exchange, advanced oxidation processes, as well as physicochemical and biochemical processes. Furthermore, this study also evaluates the contemporary progressions in this particular domain, taking into account the corresponding advantages and disadvantages. Finally, this article highlights the significance of recovering and reusing dyes, alkalis, and electrolytes in wastewater treatment. Additionally, it emphasizes the necessity of performing technoeconomic analyses and life cycle assessments (LCA) on wastewater treatment plants.
Architecture & Planning• 2024• Multidisciplinary Digital Publishing Institute
Periodicals
On Interpretability of Artificial Neural Networks: A Survey
Deep learning as represented by the artificial deep neural networks (DNNs) has achieved great success recently in many important areas that deal with text, images, videos, graphs, and so on. However, the black-box nature of DNNs has become one of the primary obstacles for their wide adoption in mission-critical applications such as medical diagnosis and therapy. Because of the huge potentials of deep learning, increasing the interpretability of deep neural networks has recently attracted much research attention. In this paper, we propose a simple but comprehensive taxonomy for interpretability, systematically review recent studies in improving interpretability of neural networks, describe applications of interpretability in medicine, and discuss possible future research directions of interpretability, such as in relation to fuzzy logic and brain science.
Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
Periodicals
Blockchain and Smart Contracts for Insurance: Is the Technology Mature Enough?
Blockchain is receiving increasing attention from academy and industry, since it is considered a breakthrough technology that could bring huge benefits to many different sectors. In 2017, Gartner positioned blockchain close to the peak of inflated expectations, acknowledging the enthusiasm for this technology that is now largely discussed by media. In this scenario, the risk to adopt it in the wake of enthusiasm, without objectively judging its actual added value is rather high. Insurance is one the sectors that, among others, started to carefully investigate the possibilities of blockchain. For this specific sector, however, the hype cycle shows that the technology is still in the innovation trigger phase, meaning that the spectrum of possible applications has not been fully explored yet. Insurers, as with many other companies not necessarily active only in the financial sector, are currently requested to make a hard decision, that is, whether to adopt blockchain or not, and they will only know if they were right in 3–5 years. The objective of this paper is to support actors involved in this decision process by illustrating what a blockchain is, analyzing its advantages and disadvantages, as well as discussing several use cases taken from the insurance sector, which could easily be extended to other domains.
Architecture & Planning• 2018• Multidisciplinary Digital Publishing Institute
Periodicals
A Simple Genetic Architecture Underlies Morphological Variation in Dogs
Domestic dogs exhibit tremendous phenotypic diversity, including a greater variation in body size than any other terrestrial mammal. Here, we generate a high density map of canine genetic variation by genotyping 915 dogs from 80 domestic dog breeds, 83 wild canids, and 10 outbred African shelter dogs across 60,968 single-nucleotide polymorphisms (SNPs). Coupling this genomic resource with external measurements from breed standards and individuals as well as skeletal measurements from museum specimens, we identify 51 regions of the dog genome associated with phenotypic variation among breeds in 57 traits. The complex traits include average breed body size and external body dimensions and cranial, dental, and long bone shape and size with and without allometric scaling. In contrast to the results from association mapping of quantitative traits in humans and domesticated plants, we find that across dog breeds, a small number of quantitative trait loci (< or = 3) explain the majority of phenotypic variation for most of the traits we studied. In addition, many genomic regions show signatures of recent selection, with most of the highly differentiated regions being associated with breed-defining traits such as body size, coat characteristics, and ear floppiness. Our results demonstrate the efficacy of mapping multiple traits in the domestic dog using a database of genotyped individuals and highlight the important role human-directed selection has played in altering the genetic architecture of key traits in this important species.
Architecture & Planning• 2010• Public Library of Science
Periodicals
RNAi Efficiency, Systemic Properties, and Novel Delivery Methods for Pest Insect Control: What We Know So Far
In recent years, the research on the potential of using RNA interference (RNAi) to suppress crop pests has made an outstanding growth. However, given the variability of RNAi efficiency that is observed in many insects, the development of novel approaches toward insect pest management using RNAi requires first to unravel factors behind the efficiency of dsRNA-mediated gene silencing. In this review, we explore essential implications and possibilities to increase RNAi efficiency by delivery of dsRNA through non-transformative methods. We discuss factors influencing the RNAi mechanism in insects and systemic properties of dsRNA. Finally, novel strategies to deliver dsRNA are discussed, including delivery by symbionts, plant viruses, trunk injections, root soaking, and transplastomic plants.
Architecture & Planning• 2016• Frontiers Media
Periodicals
Three-Dimensional Architecture and Biogenesis of Membrane Structures Associated with Hepatitis C Virus Replication
All positive strand RNA viruses are known to replicate their genomes in close association with intracellular membranes. In case of the hepatitis C virus (HCV), a member of the family Flaviviridae, infected cells contain accumulations of vesicles forming a membranous web (MW) that is thought to be the site of viral RNA replication. However, little is known about the biogenesis and three-dimensional structure of the MW. In this study we used a combination of immunofluorescence- and electron microscopy (EM)-based methods to analyze the membranous structures induced by HCV in infected cells. We found that the MW is derived primarily from the endoplasmic reticulum (ER) and contains markers of rough ER as well as markers of early and late endosomes, COP vesicles, mitochondria and lipid droplets (LDs). The main constituents of the MW are single and double membrane vesicles (DMVs). The latter predominate and the kinetic of their appearance correlates with kinetics of viral RNA replication. DMVs are induced primarily by NS5A whereas NS4B induces single membrane vesicles arguing that MW formation requires the concerted action of several HCV replicase proteins. Three-dimensional reconstructions identify DMVs as protrusions from the ER membrane into the cytosol, frequently connected to the ER membrane via a neck-like structure. In addition, late in infection multi-membrane vesicles become evident, presumably as a result of a stress-induced reaction. Thus, the morphology of the membranous rearrangements induced in HCV-infected cells resemble those of the unrelated picorna-, corona- and arteriviruses, but are clearly distinct from those of the closely related flaviviruses. These results reveal unexpected similarities between HCV and distantly related positive-strand RNA viruses presumably reflecting similarities in cellular pathways exploited by these viruses to establish their membranous replication factories.
Architecture & Planning• 2012• Public Library of Science
Periodicals
Utility of ChatGPT in Clinical Practice
ChatGPT is receiving increasing attention and has a variety of application scenarios in clinical practice. In clinical decision support, ChatGPT has been used to generate accurate differential diagnosis lists, support clinical decision-making, optimize clinical decision support, and provide insights for cancer screening decisions. In addition, ChatGPT has been used for intelligent question-answering to provide reliable information about diseases and medical queries. In terms of medical documentation, ChatGPT has proven effective in generating patient clinical letters, radiology reports, medical notes, and discharge summaries, improving efficiency and accuracy for health care providers. Future research directions include real-time monitoring and predictive analytics, precision medicine and personalized treatment, the role of ChatGPT in telemedicine and remote health care, and integration with existing health care systems. Overall, ChatGPT is a valuable tool that complements the expertise of health care providers and improves clinical decision-making and patient care. However, ChatGPT is a double-edged sword. We need to carefully consider and study the benefits and potential dangers of ChatGPT. In this viewpoint, we discuss recent advances in ChatGPT research in clinical practice and suggest possible risks and challenges of using ChatGPT in clinical practice. It will help guide and support future artificial intelligence research similar to ChatGPT in health.
Architecture & Planning• 2023• JMIR Publications
Periodicals
The OASIS3 coupler: a European climate modelling community software
Abstract. This paper presents the OASIS3 coupling software used in five of the seven European Earth System Models (ESMs) participating to the Fifth Coupled Model Intercomparison Project (CMIP5). A short history of the coupler development is followed by a technical description of OASIS3. The performances of a few relatively high resolution models coupled with OASIS3 are then described. It is shown that, although its limited field-per-field parallelism will eventually become a bottleneck in the simulation, OASIS3 can still be considered an appropriate tool for most of these relatively demanding coupled configurations. Its successful use in different CMIP5 ESMs is then detailed. A discussion of the benefits and drawbacks of the OASIS3's approach and a presentation of planned developments conclude the paper.
Architecture & Planning• 2013• Copernicus Publications
Periodicals
Deep learning in ophthalmology: The technical and clinical considerations
[no abstract]
Architecture & Planning• 2019• Elsevier BV
Periodicals
ESPRESSO at VLT
Context. ESPRESSO is the new high-resolution spectrograph of ESO’s Very Large Telescope (VLT). It was designed for ultra-high radial-velocity (RV) precision and extreme spectral fidelity with the aim of performing exoplanet research and fundamental astrophysical experiments with unprecedented precision and accuracy. It is able to observe with any of the four Unit Telescopes (UTs) of the VLT at a spectral resolving power of 140 000 or 190 000 over the 378.2 to 788.7 nm wavelength range; it can also observe with all four UTs together, turning the VLT into a 16 m diameter equivalent telescope in terms of collecting area while still providing a resolving power of 70 000. Aims. We provide a general description of the ESPRESSO instrument, report on its on-sky performance, and present our Guaranteed Time Observation (GTO) program along with its first results. Methods. ESPRESSO was installed on the Paranal Observatory in fall 2017. Commissioning (on-sky testing) was conducted between December 2017 and September 2018. The instrument saw its official start of operations on October 1, 2018, but improvements to the instrument and recommissioning runs were conducted until July 2019. Results. The measured overall optical throughput of ESPRESSO at 550 nm and a seeing of 0.65″ exceeds the 10% mark under nominal astroclimatic conditions. We demonstrate an RV precision of better than 25 cm s −1 during a single night and 50 cm s −1 over several months. These values being limited by photon noise and stellar jitter shows that the performance is compatible with an instrumental precision of 10 cm s −1 . No difference has been measured across the UTs, neither in throughput nor RV precision. Conclusions. The combination of the large collecting telescope area with the efficiency and the exquisite spectral fidelity of ESPRESSO opens a new parameter space in RV measurements, the study of planetary atmospheres, fundamental constants, stellar characterization, and many other fields.
Architecture & Planning• 2020• EDP Sciences