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Periodicals

Genetic Architecture of Complex Traits and Accuracy of Genomic Prediction: Coat Colour, Milk-Fat Percentage, and Type in Holstein Cattle as Contrasting Model Traits

Prediction of genetic merit using dense SNP genotypes can be used for estimation of breeding values for selection of livestock, crops, and forage species; for prediction of disease risk; and for forensics. The accuracy of these genomic predictions depends in part on the genetic architecture of the trait, in particular number of loci affecting the trait and distribution of their effects. Here we investigate the difference among three traits in distribution of effects and the consequences for the accuracy of genomic predictions. Proportion of black coat colour in Holstein cattle was used as one model complex trait. Three loci, KIT, MITF, and a locus on chromosome 8, together explain 24% of the variation of proportion of black. However, a surprisingly large number of loci of small effect are necessary to capture the remaining variation. A second trait, fat concentration in milk, had one locus of large effect and a host of loci with very small effects. Both these distributions of effects were in contrast to that for a third trait, an index of scores for a number of aspects of cow confirmation ("overall type"), which had only loci of small effect. The differences in distribution of effects among the three traits were quantified by estimating the distribution of variance explained by chromosome segments containing 50 SNPs. This approach was taken to account for the imperfect linkage disequilibrium between the SNPs and the QTL affecting the traits. We also show that the accuracy of predicting genetic values is higher for traits with a proportion of large effects (proportion black and fat percentage) than for a trait with no loci of large effect (overall type), provided the method of analysis takes advantage of the distribution of loci effects.

Architecture & Planning• 2010• Public Library of Science
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Jointly Learning Heterogeneous Features for RGB-D Activity Recognition

In this paper, we focus on heterogeneous features learning for RGB-D activity recognition. We find that features from different channels (RGB, depth) could share some similar hidden structures, and then propose a joint learning model to simultaneously explore the shared and feature-specific components as an instance of heterogeneous multi-task learning. The proposed model formed in a unified framework is capable of: 1) jointly mining a set of subspaces with the same dimensionality to exploit latent shared features across different feature channels, 2) meanwhile, quantifying the shared and feature-specific components of features in the subspaces, and 3) transferring feature-specific intermediate transforms (i-transforms) for learning fusion of heterogeneous features across datasets. To efficiently train the joint model, a three-step iterative optimization algorithm is proposed, followed by a simple inference model. Extensive experimental results on four activity datasets have demonstrated the efficacy of the proposed method. A new RGB-D activity dataset focusing on human-object interaction is further contributed, which presents more challenges for RGB-D activity benchmarking.

Architecture & Planning• 2016• IEEE Computer Society
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Fruit recognition from images using deep learning

In this paper we introduce a new, high-quality, dataset of images containing fruits. We also present the results of some numerical experiment for training a neural network to detect fruits. We discuss the reason why we chose to use fruits in this project by proposing a few applications that could use such classifier.

Architecture & Planning• 2018
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Periodicals

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level precision. This progress has been accompanied by an exponential increase in the size and quality of data sets produced by microscopic and spectroscopic experimental techniques. These developments necessitate adequate methods for extracting relevant physical and chemical information from the large data sets, for which a priori information on the structures of various atomic configurations and lattice defects is limited or absent. Here we demonstrate an application of deep neural networks to extract information from atomically resolved images including location of the atomic species and type of defects. We develop a "weakly supervised" approach that uses information on the coordinates of all atomic species in the image, extracted via a deep neural network, to identify a rich variety of defects that are not part of an initial training set. We further apply our approach to interpret complex atomic and defect transformation, including switching between different coordination of silicon dopants in graphene as a function of time, formation of peculiar silicon dimer with mixed 3-fold and 4-fold coordination, and the motion of molecular "rotor". This deep learning-based approach resembles logic of a human operator, but can be scaled leading to significant shift in the way of extracting and analyzing information from raw experimental data.

Architecture & Planning• 2017• American Chemical Society
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Periodicals

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

Architecture & Planning• 2018• Public Library of Science
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Implementation of a MIMO OFDM-Based Wireless LAN System

The combination of multiple-input multiple-output (MIMO) signal processing with orthogonal frequency division multiplexing (OFDM) is regarded as a promising solution for enhancing the data rates of next-generation wireless communication systems operating in frequency-selective fading environments. To realize this extension of OFDM with MIMO, a number of changes are required in the baseband signal processing. An overview is given of the necessary changes, including time and frequency synchronization, channel estimation, synchronization tracking, and MIMO detection. As a test case, the OFDM-based wireless local area network (WLAN) standard IEEE 802.11a is considered, but the results are applicable more generally. The complete MIMO OFDM processing is implemented in a system with three transmit and three receive antennas, and its performance is evaluated with both simulations and experimental test results. Results from measurements with this MIMO OFDM system in a typical office environment show, on average, a doubling of the system throughput, compared with a single antenna OFDM system. An average expected tripling of the throughput was most likely not achieved due to coupling between the transmitter and receiver branches.

Architecture & Planning• 2004• Institute of Electrical and Electronics Engineers
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A Survey on Technologies, Standards and Open Challenges in Satellite IoT

The Internet of Things (IoT) is expected to bring new opportunities for improving several services for the Society, from transportation to agriculture, from smart cities to fleet management. In this framework, massive connectivity represents one of the key issues. This is especially relevant when IoT systems are expected to cover a large geographical area or a region not reached by terrestrial network connections. In such scenarios, the usage of satellites might represent a viable solution for providing wide area coverage and connectivity in a flexible and affordable manner. Our paper presents a survey on current solutions for the deployment of IoT services in remote/rural areas by exploiting satellites. Several architectures and technical solutions are analyzed, underlining their features and limitations, and real test cases are presented. It has been highlighted that low-orbit satellites offer an efficient solution to support long-range IoT services, with a good trade-off in terms of coverage and latency. Moreover, open issues, new challenges, and innovative technologies have been focused, carefully considering the perimeter that current IoT standardization framework will impose to the practical implementation of future satellite based IoT systems.

Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
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Periodicals

The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise

Respiratory rate is a fundamental vital sign that is sensitive to different pathological conditions (e.g., adverse cardiac events, pneumonia, and clinical deterioration) and stressors, including emotional stress, cognitive load, heat, cold, physical effort, and exercise-induced fatigue. The sensitivity of respiratory rate to these conditions is superior compared to that of most of the other vital signs, and the abundance of suitable technological solutions measuring respiratory rate has important implications for healthcare, occupational settings, and sport. However, respiratory rate is still too often not routinely monitored in these fields of use. This review presents a multidisciplinary approach to respiratory monitoring, with the aim to improve the development and efficacy of respiratory monitoring services. We have identified thirteen monitoring goals where the use of the respiratory rate is invaluable, and for each of them we have described suitable sensors and techniques to monitor respiratory rate in specific measurement scenarios. We have also provided a physiological rationale corroborating the importance of respiratory rate monitoring and an original multidisciplinary framework for the development of respiratory monitoring services. This review is expected to advance the field of respiratory monitoring and favor synergies between different disciplines to accomplish this goal.

Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
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Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities

Smart cities contain intelligent things which can intelligently automatically and collaboratively enhance life quality, save people's lives, and act a sustainable resource ecosystem. To achieve these advanced collaborative technologies such as drones, robotics, artificial intelligence, and Internet of Things (IoT) are required to increase the smartness of smart cities by improving the connectivity, energy efficiency, and quality of services (QoS). Therefore, collaborative drones and IoT play a vital role in supporting a lot of smart-city applications such as those involved in communication, transportation, agriculture,safety and security, disaster mitigation, environmental protection, service delivery, energy saving, e-waste reduction, weather monitoring, healthcare, etc. This paper presents a survey of the potential techniques and applications of collaborative drones and IoT which have recently been proposed in order to increase the smartness of smart cities. It provides a comprehensive overview highlighting the recent and ongoing research on collaborative drone and IoT in improving the real-time application of smart cities. This survey is different from previous ones in term of breadth, scope, and focus. In particular, we focus on the new concept of collaborative drones and IoT for improving smart-city applications. This survey attempts to show how collaborative drones and IoT improve the smartness of smart cities based on data collection, privacy and security, public safety, disaster management, energy consumption and quality of life in smart cities. It mainly focuses on the measurement of the smartness of smart cities, i.e., environmental aspects, life quality, public safety, and disaster management.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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Soil “Ecosystem” Services and Natural Capital: Critical Appraisal of Research on Uncertain Ground

Over the last few years, considerable attention has been devoted in the scientific literature and in the media to the concept of "ecosystem" services of soils. The monetary valuation of these services, demanded by many governments and international agencies, is often depicted as a necessary condition for the preservation of the natural capital that soils represent. This focus on soil services is framed in the context of a general interest in ecosystem services that allegedly started in 1997, and took off in earnest after 2005. The careful analysis of the literature proposed in this article shows that, in fact, interest in the multifunctionality of soils emerged already in the mid-60s, at a time when hundreds of researchers worldwide were trying, and largely failing, to figure out how to put price tags meaningfully on "nature's services." Soil scientists, since, have tried to better understand various functions/services of soils, as well as their possible relation with key soil characteristics, like biodiversity. They have also tried to make progress on the challenging quantification of soil functions/services. However, researchers have shown very little interest in monetary valuation, undoubtedly in part because it is not clear what economic and financial markets might do with prices of soil functions/services, even if we could somehow come up with such numbers, and because there is no assurance at all, based on neoclassical economic theory, that markets would manage soil resources optimally. Instead of monetary valuation, focus in the literature has been put on decision-making methods, like Multi-Criteria Decision Analysis (MCDA) and Bayesian Belief Networks (BBN), which do not require the systematic monetization of soil functions/services and easily accommodate deliberative approaches involving a variety of stakeholders. A prerequisite to progress in such public deliberations is that participants be very cognizant of the extreme relevance of soils to many aspects of their daily life. We argue that, as long as this prerequisite is satisfied, the combination of deliberative decision-making methods and of a sound scientific approach to the quantification of soil functions/services is a very promising avenue to manage effectively and ethically the priceless heritage that soils constitute.

Architecture & Planning• 2016• Frontiers Media
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What Kind of Local and Regional Development and for Whom?

Pike A., Rodríguez-Pose A. and Tomaney J. (2007) What kind of local and regional development and for whom?, Regional Studies 41, 1253–1269. This paper asks the question, what kind of local and regional development and for whom? It examines what is meant by local and regional development, its historical context, its geographies in space, territory, place and scale and its different varieties, principles and values. The socially uneven and geographically differentiated distribution of who and where benefits and loses from particular forms of local and regional development is analysed. A holistic, progressive and sustainable version of local and regional development is outlined with reflections upon its limits and political renewal. Locally and regionally determined development models should not be developed independently of more foundational principles and values such as democracy, equity, internationalism and justice. Specific local and regional articulations are normative questions and subject to social determination and political choices in particular national and international contexts. Local Regional Development Pike A., Rodríguez-Pose A. et Tomaney J. (2007) Quelle sorte d'aménagement du territoire et pour qui?, Regional Studies 41, 1253–1269. Cet article pose la question suivante: quelle sorte d'aménagement du territoire et pour qui? Il cherche à examiner ce que l'on veut dire par aménagement du territoire, son historique, ses orientations quant à l'espace, au territoire, à l'endroit et à l'échelle, et ses différentes formes, principes et valeurs. On examine la distribution socialement irrégulière et géographiquement distincte des gens et des emplacements qui profitent ou perdent des formes particulières d'aménagement du territoire. On esquisse ici une version de l'aménagement du territoire à la fois holistique, progressive et durable, tout en réfléchissant sur ses limites et sur le regain politique. Des modèles de développement, déterminés sur les plans local ou régional, ne devraient pas être développés indépendamment des principes et des valeurs de base, tels la démocratie, l'équité, l'internationalisme et la justice. Des articulations locales et régionales spécifiques sont des questions normatives et dépendent de la détermination sociale et des choix politiques dans des contextes nationaux et internationaux particuliers. Local Régional Développement Pike A., Rodríguez-Pose A. und Tomaney J. (2007) Welche Art von lokaler und regionaler Entwicklung und für wen? Regional Studies 41, 1253–1269. In diesem Beitrag wird die Frage gestellt: welche Art von lokaler und regionaler Entwicklung und für wen? Untersucht werden der Begriff der lokalen und regionalen Entwicklung sowie ihr historischer Kontext, ihre Geografien in Raum, Gebiet, Ort und Maßstab sowie ihre verschiedenen Varietäten, Prinzipien und Werte. Analysiert wird die gesellschaftlich ungleichmäßige und geografisch differenzierte Verteilung hinsichtlich der Frage, wer von bestimmten Formen der lokalen und regionalen Entwicklung wo profitiert oder verliert. Es wird eine ganzheitliche, progressive und nachhaltige Version der lokalen und regionalen Entwicklung beschrieben, und es werden Überlegungen hinsichtlich ihrer Grenzen und politischen Erneuerung angestellt. Lokal und regional bestimmte Entwicklungsmodelle sollten nicht unabhängig von grundlegenderen Prinzipien und Werten wie Demokratie, Gleichheit, Internationalismus und Gerechtigkeit entwickelt werden. Spezifische lokale und regionale Äußerungen sind normative Fragen und unterliegen einer gesellschaftlichen Determination sowie einer politischen Auswahl in bestimmten nationalen und internationalen Kontexten. Lokal Regional Entwicklung Pike A., Rodríguez-Pose A. y Tomaney J. (2007) ¿Qué tipo de desarrollo regional y local es necesario y para quién?, Regional Studies 41, 1253–1269. En este ensayo planteamos la cuestión de qué tipo de desarrollo regional y local es necesario y para quién. Analizamos qué significa exactamente desarrollo local y regional, su contexto histórico, sus geografías en el espacio, territorio, lugar y escala y sus diferentes variaciones, principios y valores. Estudiamos también la distribución socialmente desigual y geográficamente diferenciada de quién se beneficia y quién sale perjudicado de los diferentes tipos de desarrollo local y regional y dónde ocurre. Describimos una versión holística, progresiva y sostenible del desarrollo local y regional con reflexiones sobre sus límites y renovación política. Los modelos de desarrollo determinados a nivel local y regional no deberían crearse sin tener en cuenta principios y valores fundamentales tales como democracia, derechos, internacionalismo y justicia. Las articulaciones específicas a nivel local y regional son cuestiones normativas y están sujetas a determinaciones sociales y opciones políticas en contextos nacionales e internacionales. Local Regional Desarrollo

Architecture & Planning• 2007• Routledge
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Periodicals

Automaticity of walking: functional significance, mechanisms, measurement and rehabilitation strategies

Automaticity is a hallmark feature of walking in adults who are healthy and well-functioning. In the context of walking, "automaticity" refers to the ability of the nervous system to successfully control typical steady state walking with minimal use of attention-demanding executive control resources. Converging lines of evidence indicate that walking deficits and disorders are characterized in part by a shift in the locomotor control strategy from healthy automaticity to compensatory executive control. This is potentially detrimental to walking performance, as an executive control strategy is not optimized for locomotor control. Furthermore, it places excessive demands on a limited pool of executive reserves. The result is compromised ability to perform basic and complex walking tasks and heightened risk for adverse mobility outcomes including falls. Strategies for rehabilitation of automaticity are not well defined, which is due to both a lack of systematic research into the causes of impaired automaticity and to a lack of robust neurophysiological assessments by which to gauge automaticity. These gaps in knowledge are concerning given the serious functional implications of compromised automaticity. Therefore, the objective of this article is to advance the science of automaticity of walking by consolidating evidence and identifying gaps in knowledge regarding: (a) functional significance of automaticity; (b) neurophysiology of automaticity;

Architecture & Planning• 2015• Frontiers Media
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ProjectQ: an open source software framework for quantum computing

We introduce ProjectQ, an open source software effort for quantum computing. The first release features a compiler framework capable of targeting various types of hardware, a high-performance simulator with emulation capabilities, and compiler plug-ins for circuit drawing and resource estimation. We introduce our Python-embedded domain-specific language, present the features, and provide example implementations for quantum algorithms. The framework allows testing of quantum algorithms through simulation and enables running them on actual quantum hardware using a back-end connecting to the IBM Quantum Experience cloud service. Through extension mechanisms, users can provide back-ends to further quantum hardware, and scientists working on quantum compilation can provide plug-ins for additional compilation, optimization, gate synthesis, and layout strategies.

Architecture & Planning• 2018• Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
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Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review

With the growing integration of distributed energy resources (DERs), flexible loads, and other emerging technologies, there are increasing complexities and uncertainties for modern power and energy systems. This brings great challenges to the operation and control. Besides, with the deployment of advanced sensor and smart meters, a large number of data are generated, which brings opportunities for novel data-driven methods to deal with complicated operation and control issues. Among them, reinforcement learning (RL) is one of the most widely promoted methods for control and optimization problems. This paper provides a comprehensive literature review of RL in terms of basic ideas, various types of algorithms, and their applications in power and energy systems. The challenges and further works are also discussed.

Architecture & Planning• 2020• Springer Nature
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Impact of COVID-19 on loneliness, mental health, and health service utilisation: a prospective cohort study of older adults with multimorbidity in primary care

BACKGROUND: The COVID-19 pandemic has impacted the psychological health and health service utilisation of older adults with multimorbidity, who are particularly vulnerable. AIM: To describe changes in loneliness, mental health problems, and attendance to scheduled medical care before and after the onset of the COVID-19 pandemic. DESIGN AND SETTING: Telephone survey on a pre-existing cohort of older adults with multimorbidity in primary care. METHOD: -tests, Wilcoxon's signed-rank test, and McNemar's test. Loneliness was measured by the De Jong Gierveld Loneliness Scale. The secondary outcomes (anxiety, depression, and insomnia) were measured by the 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder tool, and the Insomnia Severity Index. Appointments attendance data were extracted from a computerised medical record system. Sociodemographic factors associated with outcome changes were examined by linear regression and generalised estimating equations. RESULTS: Data were collected from 583 older (≥60 years) adults. There were significant increases in loneliness, anxiety, and insomnia, after the onset of the COVID-19 outbreak. Missed medical appointments over a 3-month period increased from 16.5% 1 year ago to 22.0% after the onset of the outbreak. In adjusted analysis, being female, living alone, and having >4 chronic conditions were independently associated with increased loneliness. Females were more likely to have increased anxiety and insomnia. CONCLUSION: Psychosocial health of older patients with multimorbidity markedly deteriorated and missed medical appointments substantially increased after the COVID-19 outbreak.

Architecture & Planning• 2020• Royal College of General Practitioners
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Digitization, Digital Twins, Blockchain, and Industry 4.0 as Elements of Management Process in Enterprises in the Energy Sector

In the 21st century, it is becoming increasingly clear that human activities and the activities of enterprises affect the environment. Therefore, it is important to learn about the methods in which companies minimize the negative effects of their activities. The article presents the steps taken and innovative actions carried out by enterprises in the energy sector. The article analyzes innovative activities undertaken and implemented by enterprises from the energy sector. The relationships between innovative strategies, including, inter alia, digitization, and Industry 4.0 solutions, in the development of companies and the achieved results concerning sustainable development and environmental impact. Digitization has far exceeded traditional productivity improvement ranges of 3–5% per year, with a clear cost improvement potential of well above 25%. Enterprises on a large scale make attempts to increase energy efficiency by implementing the state-of-the-art innovative technical and technological solutions, which increase reliability and durability (material and mechanical engineering). Digitization of energy companies allows them to reduce operating costs and increases efficiency. With digital advances, the useful life of an energy plant can be increased up to 30%. Advanced technologies, blockchain, and the use of intelligent networks enables the activation of prosumers in the electricity market. Reducing energy consumption in industry and at the same time increasing energy efficiency for which the European Union is fighting in the clean air package for all Europeans have a positive impact on environmental protection, sustainable development, and the implementation of the decarbonization program.

Architecture & Planning• 2021• Multidisciplinary Digital Publishing Institute
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Neurocognitive impairment in euthymic patients with bipolar affective disorder

BACKGROUND: Persistent impairments in neurocognitive function have been described in patients with bipolar disorder whose disease is in remission. However, methodological issues such as the effect of residual mood symptoms and hypercortisolaemia may confound such studies. AIMS: To assess neurocognitive functioning in prospectively verified euthymic patients with bipolar disorder. METHOD: Sixty-three patients with bipolar disorder and a matched control group completed a comprehensive neurocognitive test battery. Euthymia was confirmed in the patient group by prospective clinical ratings over 1 month prior to testing. Saliva samples were collected to profile basal cortisol secretion. RESULTS: Patients were significantly impaired across a broad range of cognitive domains. Across the domains tested, clinically significant impairment was observed in 3% to 42% of patients. Deficits were not causally associated with residual mood symptoms or hypercortisolaemia. CONCLUSIONS: Neurocognitive impairment persists in patients whose bipolar disorder is in remission. This may represent a trait abnormality and be a marker of underlying neurobiological dysfunction.

Architecture & Planning• 2005• Cambridge University Press
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Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system is a prominent concept, where a UAV equipped with an MEC server is deployed to serve a number of terminal devices (TDs) of Internet of Things in a finite period. In this article, each TD has a certain latency-critical computation task in each time slot to complete. Three computation strategies can be available to each TD. First, each TD can operate local computing by itself. Second, each TD can partially offload task bits to the UAV for computing. Third, each TD can choose to offload task bits to access point via UAV relaying. We propose a new optimization problem formulation that aims to minimize the total energy consumption including communication-related energy, computation-related energy and UAV's flight energy by optimizing the bits allocation, time slot scheduling, and power allocation as well as UAV trajectory design. As the formulated problem is nonconvex and difficult to find the optimal solution, we propose to solve the problem by two parts, and obtain the near optimal solution by the Lagrangian duality method and successive convex approximation technique, respectively. By analysis, the proposed algorithm can be guaranteed to converge within a dozen of iterations. Finally, numerical results are given to validate the proposed algorithm, which is verified to be efficient and superior to the other benchmark cases.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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In search of a circular supply chain archetype – a content-analysis-based literature review

This paper addresses questions of how extant research discourses concerning the sustainability of supply chains contribute to understanding about circularity in supply chain configurations that support restorative and regenerative processes, as espoused by the Circular Economy ideal. In response to these questions, we develop a content-based literature analysis to progress theoretical body of knowledge and conceptualise the notion of a circular supply chain. We derive an archetypal form from four antecedent sustainable supply chain narratives – ‘reverse logistics’, ‘green supply chains’, ‘sustainable supply chain management’ and ‘closed-loop supply chains’. This paper offers five propositions about what the circular supply chain archetype represents in terms of its scope, focus and impact. Novel insights lead to a definition of circular supply chain and a more coherent foundation for future inquiry and practice.

Architecture & Planning• 2018• Taylor & Francis
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Persistent improvement in synaptic and cognitive functions in an Alzheimer mouse model after rolipram treatment

Evidence suggests that Alzheimer disease (AD) begins as a disorder of synaptic function, caused in part by increased levels of amyloid beta-peptide 1-42 (Abeta42). Both synaptic and cognitive deficits are reproduced in mice double transgenic for amyloid precursor protein (AA substitution K670N,M671L) and presenilin-1 (AA substitution M146V). Here we demonstrate that brief treatment with the phosphodiesterase 4 inhibitor rolipram ameliorates deficits in both long-term potentiation (LTP) and contextual learning in the double-transgenic mice. Most importantly, this beneficial effect can be extended beyond the duration of the administration. One course of long-term systemic treatment with rolipram improves LTP and basal synaptic transmission as well as working, reference, and associative memory deficits for at least 2 months after the end of the treatment. This protective effect is possibly due to stabilization of synaptic circuitry via alterations in gene expression by activation of the cAMP-dependent protein kinase (PKA)/cAMP regulatory element-binding protein (CREB) signaling pathway that make the synapses more resistant to the insult inflicted by Abeta. Thus, agents that enhance the cAMP/PKA/CREB pathway have potential for the treatment of AD and other diseases associated with elevated Abeta42 levels.

Architecture & Planning• 2004• American Society for Clinical Investigation
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The internet of things for smart manufacturing: A review

The modern manufacturing industry is investing in new technologies such as the Internet of Things (IoT), big data analytics, cloud computing and cybersecurity to cope with system complexity, increase information visibility, improve production performance, and gain competitive advantages in the global market. These advances are rapidly enabling a new generation of smart manufacturing, i.e., a cyber-physical system tightly integrating manufacturing enterprises in the physical world with virtual enterprises in cyberspace. To a great extent, realizing the full potential of cyber-physical systems depends on the development of new methodologies on the Internet of Manufacturing Things (IoMT) for data-enabled engineering innovations. This article presents a review of the IoT technologies and systems that are the drivers and foundations of data-driven innovations in smart manufacturing. We discuss the evolution of internet from computer networks to human networks to the latest era of smart and connected networks of manufacturing things (e.g., materials, sensors, equipment, people, products, and supply chain). In addition, we present a new framework that leverages IoMT and cloud computing to develop a virtual machine network. We further extend our review to IoMT cybersecurity issues that are of paramount importance to businesses and operations, as well as IoT and smart manufacturing policies that are laid out by governments around the world for the future of smart factory. Finally, we present the challenges and opportunities arising from IoMT. We hope this work will help catalyze more in-depth investigations and multi-disciplinary research efforts to advance IoMT technologies.

Architecture & Planning• 2019• Taylor & Francis
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