Influence of seismic effect of bridge piles on a subway station

As separated platform subway station structures are close to bridge piles, their analysis under static and seismic loading is required. An artificial earthquake record, generated by using Kanai-Tajimi model and trigonometric series superposition method, is used to analyze the seismic performance of the subway station structure. Different construction sequences of bridge piles and subway stations are considered in the analysis of structural seismic performance. Irrespective of the type of analysis, most of the horizontal and the vertical stresses of the subway station with existing bridge piles show a decreasing trend as compared to those without bridge piles. The stresses associated with post-constructed bridge piles increase significantly as compared to those without piles, especially in areas of stress concentrations. A parametric analysis of the distance between the subway station and the bridge pile is also conducted. The percentage increase in horizontal and vertical stress of the subway station, with post-construction pile, gradually decreases with increasing distance. However, in case of existing piles the percentage increase in stress, as a function of distance, has an inflection point

Oscillation-specific nodal alterations in early to middle stages Parkinsons disease.

Background: Different oscillations of brain networks could carry different dimensions of brain integration. We aimed to investigate oscillation-specific nodal alterations in patients with Parkinsons disease (PD) across early stage to middle stage by using graph theory-based analysis. Methods: Eighty-eight PD patients including 39 PD patients in the early stage (EPD) and 49 patients in the middle stage (MPD) and 36 controls were recruited in the present study. Graph theory-based network analyses from three oscillation frequencies (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; slow-3: 0.073-0.198 Hz) were analyzed. Nodal metrics (e.g. nodal degree centrality, betweenness centrality and nodal efficiency) were calculated. Results: Our results showed that (1) a divergent effect of oscillation frequencies on nodal metrics, especially on nodal degree centrality and nodal efficiency, that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed, which visually showed that network was perturbed in PD; (2) PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities, which was consistently detected within all three oscillation frequencies; (3) the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients; (4) logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level; (5) occipital disruption within high frequency (slow-3) made a significant influence on motor impairment which was dominated by akinesia and rigidity. Conclusions: Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages

Effect of remelting processes on the microstructure and mechanical behaviours of 18Ni-300 maraging steel manufactured by selective laser melting

Selective laser melting (SLM) is an established metal additive manufacturing technology extensively used in the automotive domain to manufacture metallic components with complex structures from 18Ni-300 maraging steel. However, achieving high-performance 18Ni-300 maraging steel using SLM still presents a challenge in terms of formulation of the processing parameters. The remelting process has the potential to address this challenge during SLM before post-treatments. This paper systematically investigated the effect of remelting on the microstructure and mechanical behaviours of the SLM-built 18Ni-300 maraging steel. The experimental results suggest that increases in the relative density of the as-built samples from 99.12% to 99.93% are achieved by a specific combination of remelting parameters (laser power 200 W, scan speed 750 mm/s, remelting rotation 90° and hatch spacing 0.11 mm) that eliminate large-sized pores. Compared with the as-built condition, remelting can slightly coarsen the average grain sizes and increased the fraction of low-angle grain boundaries (2°–15°). The tensile strength showed no remelting dependence, whereas both the ductility and microhardness increased. Elongation of the as-built sample increased from 10.5 ± 0.8% to 13 ± 3.5% after remelting under the #28 condition. These findings provide a fundamentally new understanding of how a combination of SLM and remelting can aid in the manufacture of high-performing 18Ni-300 maraging steel

Dopamine depletion and subcortical dysfunction disrupt cortical synchronization and metastability affecting cognitive function in Parkinson's disease

Parkinson's disease (PD) is primarily characterized by the loss of dopaminergic cells and atrophy in subcortical regions. However, the impact of these pathological changes on large‐scale dynamic integration and segregation of the cortex are not well understood. In this study, we investigated the effect of subcortical dysfunction on cortical dynamics and cognition in PD. Spatiotemporal dynamics of the phase interactions of resting‐state blood‐oxygen‐level‐dependent signals in 159 PD patients and 152 normal control (NC) individuals were estimated. The relationships between subcortical atrophy, subcortical–cortical fiber connectivity impairment, cortical synchronization/metastability, and cognitive performance were then assessed. We found that cortical synchronization and metastability in PD patients were significantly decreased. To examine whether this is an effect of dopamine depletion, we investigated 45 PD patients both ON and OFF dopamine replacement therapy, and found that cortical synchronization and metastability are significantly increased in the ON state. The extent of cortical synchronization and metastability in the OFF state reflected cognitive performance and mediates the difference in cognitive performance between the PD and NC groups. Furthermore, both the thalamic volume and thalamocortical fiber connectivity had positive relationships with cortical synchronization and metastability in the dopaminergic OFF state, and mediate the difference in cortical synchronization between the PD and NC groups. In addition, thalamic volume also reflected cognitive performance, and cortical synchronization/metastability mediated the relationship between thalamic volume and cognitive performance in PD patients. Together, these results highlight that subcortical dysfunction and reduced dopamine levels are responsible for decreased cortical synchronization and metastability, further affecting cognitive performance in PD. This might lead to biomarkers being identified that can predict if a patient is at risk of developing dementia

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Recent Advances in Electronic Skins with Multiple-Stimuli-Responsive and Self-Healing Abilities

Wearable electronic skin (e-skin) has provided a revolutionized way to intelligently sense environmental stimuli, which shows prospective applications in health monitoring, artificial intelligence and prosthetics fields. Drawn inspiration from biological skins, developing e-skin with multiple stimuli perception and self-healing abilities not only enrich their bionic multifunctionality, but also greatly improve their sensory performance and functional stability. In this review, we highlight recent important developments in the material structure design strategy to imitate the fascinating functionalities of biological skins, including molecular synthesis, physical structure design, and special biomimicry engineering. Moreover, their specific structure-property relationships, multifunctional application, and existing challenges are also critically analyzed with representative examples. Furthermore, a summary and perspective on future directions and challenges of biomimetic electronic skins regarding function construction will be briefly discussed. We believe that this review will provide valuable guidance for readers to fabricate superior e-skin materials or devices with skin-like multifunctionalities and disparate characteristics

Recent Advances in Electronic Skins with Multiple-Stimuli-Responsive and Self-Healing Abilities

Wearable electronic skin (e-skin) has provided a revolutionized way to intelligently sense environmental stimuli, which shows prospective applications in health monitoring, artificial intelligence and prosthetics fields. Drawn inspiration from biological skins, developing e-skin with multiple stimuli perception and self-healing abilities not only enrich their bionic multifunctionality, but also greatly improve their sensory performance and functional stability. In this review, we highlight recent important developments in the material structure design strategy to imitate the fascinating functionalities of biological skins, including molecular synthesis, physical structure design, and special biomimicry engineering. Moreover, their specific structure-property relationships, multifunctional application, and existing challenges are also critically analyzed with representative examples. Furthermore, a summary and perspective on future directions and challenges of biomimetic electronic skins regarding function construction will be briefly discussed. We believe that this review will provide valuable guidance for readers to fabricate superior e-skin materials or devices with skin-like multifunctionalities and disparate characteristics

Parametric Study on Mixed Torsional Behavior of U-Shaped Thin-Walled RC Girders

Nowadays, U-shaped thin-walled concrete girders have been widely applied in the urban construction of rail viaducts in China as well as worldwide. However, the mixed torsional behaviors of these structures are not well understood. In this paper, the mixed torsional behaviors of the U-shaped thin-walled RC girders are theoretically analyzed, and a method predicting failure modes and ultimate torques is proposed. Nonlinear FE models based on ABAQUS to simulate the mixed torsional behaviors are built and calibrated with the test results. Parametric studies considering three crucial parameters (boundary condition, span length-section height ratio, and ratio of longitudinal bars to stirrups) are conducted based on both the above suggested calculating method and the FE modeling. The calculated and the simulated results agree well with each other and with the test results. It is found that the failure modes of the U-shaped thin-walled RC girders under torsion are influenced by all the three parameters. Three kinds of failure modes are observed: flexural failures dominated by warping moment, shear failures caused by warping torque and circulatory torque, and flexural-shear failures in the cases where flexural failure and shear failure appear almost at the same time