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Allowing structures to rock during an earthquake can effectively provide base isolation at a relatively small cost. Rocking limits the base shear demand and provides self-centering, but the rocking response depends on energy dissipation caused by interaction with the soil and impacts during re-centering. This paper addresses the computational modeling of buildings that have either been designed to rock on the soil beneath their foundation (foundation rocking) or at the foundation–structure interface (structural rocking). Within OpenSees, foundation and structural rocking were modeled using a beam-on-a-nonlinear-Winkler-foundation model (BNWF) combined with flat-slider elements for footing–soil and superstructure–footing interactions, respectively. The modified with flat-slider elements BNWF model (mBNWF) involves an uplift-dependent stiffness and viscous damping for both vertical and horizontal directions, and a friction–vertical force coupling. The proposed computational model was used to simulate an extensive set of centrifuge tests involving both structural rocking and foundation rocking with sequential excitations. Generally, the proposed modeling approach, without calibration of built-in parameters, adequately captured the response observed in centrifuge experiments. More specifically, the modeling captured the response amplitude and waveform of story accelerations and building rocking angle in most cases, but including potential nonlinear behavior caused by previous ground excitations was in some cases critical to obtain reasonable predictions. This was more profound for foundation rocking due to its inherent dependency on the soil strength and energy dissipation; for structural rocking previous nonlinear response primarily affected the transition time between full contact and rocking, but had a smaller effect on the prediction of maximum response.

IntroductionThe ability to perform optimally under pressure is critical across many occupations, including the military, first responders, and competitive sport. Despite recognition that such performance depends on a range of cognitive factors, how common these factors are across performance domains remains unclear. The current study sought to integrate existing knowledge in the performance field in the form of a transdisciplinary expert consensus on the cognitive mechanisms that underlie performance under pressure.MethodsInternational experts were recruited from four performance domains [(i) Defense; (ii) Competitive Sport; (iii) Civilian High-stakes; and (iv) Performance Neuroscience]. Experts rated constructs from the Research Domain Criteria (RDoC) framework (and several expert-suggested constructs) across successive rounds, until all constructs reached consensus for inclusion or were eliminated. Finally, included constructs were ranked for their relative importance.ResultsSixty-eight experts completed the first Delphi round, with 94% of experts retained by the end of the Delphi process. The following 10 constructs reached consensus across all four panels (in order of overall ranking): (1) Attention; (2) Cognitive Control—Performance Monitoring; (3) Arousal and Regulatory Systems—Arousal; (4) Cognitive Control—Goal Selection, Updating, Representation, and Maintenance; (5) Cognitive Control—Response Selection and Inhibition/Suppression; (6) Working memory—Flexible Updating; (7) Working memory—Active Maintenance; (8) Perception and Understanding of Self—Self-knowledge; (9) Working memory—Interference Control, and (10) Expert-suggested—Shifting.DiscussionOur results identify a set of transdisciplinary neuroscience-informed constructs, validated through expert consensus. This expert consensus is critical to standardizing cognitive assessment and informing mechanism-targeted interventions in the broader field of human performance optimization.

Rapid and accurate identification of potential structural deficiencies is a crucial task in evaluating seismic vulnerability of large building inventories in a region. In the case of multi-story structures, abrupt vertical variations of story stiffness are known to significantly increase the likelihood of collapse during moderate or severe earthquakes. Identifying and retrofitting buildings with such irregularities—generally termed as soft-story buildings—is, therefore, vital in earthquake preparedness and loss mitigation efforts. Soft-story building identification through conventional means is a labor-intensive and time-consuming process. In this study, an automated procedure was devised based on deep learning techniques for identifying soft-story buildings from street-view images at a regional scale. A database containing a large number of building images and a semi-automated image labeling approach that effectively annotates new database entries was developed for developing the deep learning model. Extensive computational experiments were carried out to examine the effectiveness of the proposed procedure, and to gain insights into automated soft-story building identification.

Regional seismic damage simulation of buildings provides decision-makers with important information for earthquake disaster prevention and mitigation. Utilizing nonlinear time history analysis using multiple-degree-of-freedom (MDOF) models for buildings, and the next-generation performance-based earthquake engineering, an open-source general-purpose scientific workflow for seismic damage simulation and loss prediction of urban buildings (referred to as SimCenter Workflow) is presented in this study. To introduce the SimCenter Workflow process in detail and demonstrate its advantages, a seismic damage simulation and loss prediction for 1.8 million buildings in the San Francisco Bay Area were performed using the SimCenter Workflow. The open nature and modularization of the SimCenter Workflow facilitate its extensibility and make it practical for researchers to apply to seismic damage simulations in other regions.

ObjectivesTo investigate whether delirium motor subtypes differ in terms of phenomenology and contributory aetiology.DesignCross-sectional study.SettingInternational study incorporating data from Ireland and India across palliative care, old age liaison psychiatry and general adult liaison psychiatry settings.Participants1757 patients diagnosed with delirium using criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fourth edition (DSM IV).Primary and secondary outcome measuresHyperactive, mixed and hypoactive delirium subtypes were identified using the abbreviated version of the Delirium Motor Subtype Scale. Phenomenology was assessed using the Delirium Rating Scale Revised. Contributory aetiologies were assessed using the Delirium Aetiology Checklist (DEC), with a score >2 indicating that the aetiology was likely or definitely contributory.ResultsHypoactive delirium was associated with dementia, cerebrovascular and systemic infection aetiologies (pConclusionsThis study indicates a pattern of aetiology and symptomatology of delirium motor subtypes across a large international sample that had previously been lacking. It serves to improve our understanding of this complex condition and has implications in terms of early detection and management of delirium.

With the goal to facilitate research to evaluate the risks from natural hazards and alternate risk mitigation strategies, the Natural Hazards Engineering Research Infrastructure’s Computational Modeling and Simulation Center (NHERI SimCenter) is developing computational workflows for regional hazard simulations. These simulations enable research to integrate detailed assessments of individual facilities with comprehensive regional-scale simulations of natural hazard effects. This approach enables fine (parcel level) granularity on assessing natural hazard impacts on buildings, infrastructures systems and other constructed facilities, which can enable engineering informed assessment of policy considerations and socio-economic impacts. Effective development of research platforms for high-resolution regional simulations requires modular workflows that can integrate state-of-the-art models with information technologies and high-performance computing resources. In this paper, the modular architecture of the computational workflow models is described and illustrated through testbed applications to evaluate regional building damage under an earthquake and a hurricane scenario. Developed and disseminated as open-source software on the NHERI Design Safe Cyberinfrastructure, the computational models and workflows are enabling multi-disciplinary collaboration on research to mitigate the effects of natural hazard disasters.

Reinforced concrete (RC) walls are extensively used to resist lateral forces in tall buildings as well as in the majority of medium to low-rise structures designed for protective purposes. In the framework of seismic performance-based design, where an adequate modeling of the lateral load versus lateral displacement relationship and a full understanding of the damage evolution are required, numerical models represent an effective tool to conduct nonlinear response analyses of such systems. For practical applications and for performing extensive nonlinear analyses, it would be desirable to have a robust yet simple numerical model that is capable of capturing the global and local characteristics of the response for different levels of damage. To this end, this paper presents a finite element-based model implemented in OpenSees [1] capable of simulating the in-plane nonlinear static and dynamic response of RC walls across a broad range of aspect ratios. The proposed model includes (i) the element technology, in which the state-of-the-art isoparametric elements are coupled with layered sections, and (ii) a novel plane-stress plastic-damage concrete material. A simple simulation-based method for determining the concrete material parameters is proposed. Model validation is conducted through a comprehensive comparison against experimental tests collected from the literature. Results show that the proposed numerical tool can be reliably used to simulate the nonlinear global and local response of RC walls spanning a broad range of aspect ratios (from 0.4 to 2.3). Moreover, model hysteresis damping is analytically analyzed to provide modelers with insight into the equivalent damping to employ when nonlinear and equivalent linear dynamic analyses are performed with the proposed model. Finally, an extensive parametric study comprising a total of 12,288 nonlinear simulations is developed to investigate the sensitivity of the numerically predicted response to changes in the concrete model parameters and gain insight into the factors that most affect the walls peak shear and dissipated energy.

The intensity of many natural hazards, such as hurricanes, floods, tornadoes, etc., are increasing as a consequence of climate change. This increase in intensity coupled with the increase in population density, particularly along the coasts, is only magnifying the impact of such events. In order to quantify and mitigate the risk due to the hazards and to prepare for the potential impacts in a region, it is necessary to collect the information of existing buildings that are pertinent to natural hazard analysis and risk management. Gathering the building information in a region- or city-scale is a laborious and expensive undertaking. This paper presents a framework for regional scale building information generation/gathering to support regional hazard analysis. In this framework, different types of data are acquired from multiple sources (satellite and street view images, property tax assessment data, etc.) and are fused to semantically profile each building in a city. Specifically, deep learning technique is employed to extract building information from street or satellite images. A novel data mining tool is developed to overcome the data scarcity issue, quantify the uncertainty and enrich the data repository. With this framework, building inventories of cities are created to provide the data needed for disaster and risk management planning and simulations.

This paper presents an investigation on the seismic behavior of steel moment frames with mechanical hinge beam-to-column connections. The connection uses a mechanical hinge to carry shear force and a pair of buckling-restrained steel plates bolted to the beam flange to transfer bending moment. The moment-rotation behavior of the connection was theoretically studied. A nonlinear numerical model for steel moment frames under strong earthquakes was developed and validated using a shaking table test of an 18-story steel moment frame at the E-Defense facility. Then, nonlinear static and time-history analyses were conducted to compare the seismic behavior of a conventional steel moment frame and three innovative steel frames equipped mechanical hinge connections in terms of roof displacement, base shear, inter-story drift ratio, and plastic hinge rotation.

What you need to know Rheumatoid arthritis is a chronic, disabling autoimmune disease characterised by synovitis of small and large joints causing swelling, stiffness, pain, and progressive joint destruction. About 1% of the UK population have rheumatoid arthritis, and approximately 15% of these people have severe disease. It affects roughly three times as many women as men. People tend to develop rheumatoid arthritis between 40 and 60 years of age, although it can arise at any age. The early signs of rheumatoid arthritis are often encountered in primary care, where people present with joint pain and swelling. Fast and accurate referral to rheumatology services is important to achieve early remission and prevent or reduce disability.1 This article summarises the update of the National Institute for Health and Care Excellence (NICE) guideline for the diagnosis and management of rheumatoid arthritis in adults.2 The management of rheumatoid arthritis has evolved in the nine years since the previous NICE guideline on rheumatoid arthritis was published, with greater emphasis on a treat-to-target strategy rather than specific drug regimens,3 and debate about the merit of initiating treatment with combination drug therapy.4 Technologies such as ultrasound have been increasingly used for diagnosis and monitoring of synovitis where it is unclear from clinical examination.5 These aspects of management were investigated by the Guideline Committee, and …

The recognition of the primacy of enthesitis in animal models of spondyloarthritis and the prevalence of clinically occult enthesopathy in psoriatic subjects and of persistent joint pain in PsA subjects who have ostensibly good reduction of joint swelling under biological therapy has highlighted the potential impact of polyenthesitis in psoriatic disease. In daily practice, the formal demonstration of enthesitis is challenging for the following reasons: the relatively avascular nature of enthesis, often leading to the absence of overt clinical inflammatory signs; the frequent lack of elevation of inflammatory markers; and finally, the limitations of current imaging techniques to provide supportive evidence for inflammation in these areas. Consequently, enthesitis may present as widespread pain indistinguishable from FM or may emerge as the dominant feature after successful biological therapy for suppression of synovitis. The unmet needs in the differentiation between FM and enthesitis in psoriatic disease patients are highlighted and critically evaluated in this article.

Summary The Rayleigh damping model, which is pervasive in nonlinear response history analysis (RHA) of buildings, is shown to develop ‘spurious’ damping forces and lead to inaccurate response results. We prove that a viscous damping matrix constructed by superposition of modal damping matrices—irrespective of the number of modes included or values assigned to modal damping ratios—completely eliminates the ‘spurious’ damping forces. This is the damping model recommended for nonlinear RHA. Replacing the stiffness-proportional part of Rayleigh damping by the tangent stiffness matrix is shown to improve response results. However, this model is not recommended because it lacks a physical basis and has conceptual implications that are troubling: hysteresis in damping force–velocity relationship and negative damping at large displacements. Furthermore, the model conflicts with the constant-damping model that has been the basis for fundamental concepts and accumulated experience about the inelastic response of structures. With a distributed plasticity model, the structural response is not sensitive to the damping model; even the Rayleigh damping model leads to acceptable results. This perspective on damping provides yet another reason to employ the superior distributed plasticity models in nonlinear RHA. OpenSees software has been extended to include a damping matrix defined as the superposition of modal damping matrices. Although this model leads to a full populated damping matrix, the additional computational demands are demonstrated to be minimal. Copyright © 2015 John Wiley & Sons, Ltd.

Summary In this paper, we described the benefits and the challenges of integrating existing scientific workflow technologies into science gateways. Scientific workflow managers are powerful tools for handling large computational tasks. Domain scientists find it difficult to create new workflows, so many tasks that could benefit from workflow automation are often avoided or performed by hand. Two technologies have come together to bring the benefits of workflow to the masses. The Pegasus Workflow Management System can manage workflows comprised of millions of tasks, all the while recording data about the execution and intermediate results so that the provenance of the final result is clear. The HUBzero platform for scientific collaboration provides a venue for building and delivering tools to researchers and educators. With the press of a button, these tools can launch Pegasus workflows on national computing infrastructures and bring results back for plotting and visualization. As a result, the combination of Pegasus and HUBzero is bringing high-throughput computing to a much wider audience. Copyright © 2014 John Wiley & Sons, Ltd.

The automation and systemisation of the next generation of cognitive assessment approaches have the potential to change how clinicians assess and interact with patients. This may be especially pertinent in the case of delirium, as current methods often rely on the subjective opinion of clinicians and specialists, with potential for the condition to be overlooked or misdiagnosed. Currently, one of the most commonly used tests, is the clock-drawing test, which has relatively wide appeal as a cognitive screening instrument due to its clinical utility and psychometric properties. However, there are a number of inconsistencies associated with its use and interpretation. In this paper, we describe a new assessment methodology that we have developed, facilitated by the advances in tablet technology. In trials, our "Letter and Shape Drawing (LSD)" tool, involving both an automated scoring capability and a simpler user interaction, has demonstrated correlation with other conventional cognitive test methods although some optimisation requirements remain.

© 2017 European Sleep Research Society While research indicates that both the macro- and microstructure of sleep may be altered in fibromyalgia syndrome, few studies have controlled for symptom duration or included pain-control participants (i.e. patients with chronic pain and sleep disturbance not associated with fibromyalgia syndrome). A frequently reported alteration found in the sleep microstructure of patients with fibromyalgia syndrome is the alpha-delta sleep anomaly. Although alpha waves have been observed during N3 sleep in healthy individuals, it has been proposed that there is an increase in alpha wave activity during slow-wave sleep in fibromyalgia syndrome. Originally considered a possible neurological contribution to fibromyalgia syndrome, whether the alpha-delta sleep anomaly is fundamental to the development of fibromyalgia syndrome, or results mainly from the pain experience remains unknown. The present study was designed to compare sleep macro- and microstructure, and psychometric profiles, in three broadly age-matched groups of female participants: patients with fibromyalgia syndrome (n = 19); patients with osteoar thritis with sleep disturbance (n = 17); and healthy adults (n = 10). Patients with fibromyalgia syndrome met the American College of Rheumatology diagnostic criteria and were recruited within 6 months of diagnosis. Subjective sleep quality was significantly lowest, and levels of anxiety and depressive symptoms were significantly highest for patients with fibromyalgia syndrome. However, the groups showed no significant differences in polysomnographic measures of total sleep time, sleep latency and total wake after sleep onset. Levels of alpha-delta sleep were statistically similar in both clinical (fibromyalgia syndrome and osteoarthritis) groups, indicating that it is not a specific abnormality of fibromyalgia syndrome. Overall, subjective measurements of anxiety, depression, fatigue and sleep quality better discriminated between the three groups than did objective measurements of sleep variables.