Dramatic Increase In Complexity Research Articles

Health Intelligence Atlas: A Core Tool for Public Health Intelligence.

Background The dramatic increase in complexity and volume of health data has challenged traditional health systems to deliver useful information to their users. The novel coronavirus disease 2019 (COVID-19) pandemic has further exacerbated this problem and demonstrated the critical need for the 21st century approach. This approach needs to ingest relevant, diverse data sources, analyze them, and generate appropriate health intelligence products that enable users to take more effective and efficient actions for their specific challenges. Objectives This article characterizes the Health Intelligence Atlas (HI-Atlas) development and implementation to produce Public Health Intelligence (PHI) that supports identifying and prioritizing high-risk communities by public health authorities. The HI-Atlas moves from post hoc observations to a proactive model-based approach for preplanning COVID-19 vaccine preparedness, distribution, and assessing the effectiveness of those plans. Results Details are presented on how the HI-Atlas merged traditional surveillance data with social intelligence multidimensional data streams to produce the next level of health intelligence. Two-model use cases in a large county demonstrate how the HI-Atlas produced relevant PHI to inform public health decision makers to (1) support identification and prioritization of vulnerable communities at risk for COVID-19 spread and vaccine hesitancy, and (2) support the implementation of a generic model for planning equitable COVID-19 vaccine preparedness and distribution. Conclusion The scalable models of data sources, analyses, and smart hybrid data layer visualizations implemented in the HI-Atlas are the Health Intelligence tools designed to support real-time proactive planning and monitoring for COVID-19 vaccine preparedness and distribution in counties and states.

MEMS-Enabled Silicon Photonic Integrated Devices and Circuits

Photonic integrated circuits have seen a dramatic increase in complexity over the past decades. This development has been spurred by recent applications in datacenter communications and enabled by the availability of standardized mature technology platforms. Mechanical movement of wave-guiding structures at the micro- and nanoscale provides unique opportunities to further enhance functionality and to reduce power consumption in photonic integrated circuits. We here demonstrate integration of MEMS-enabled components in a simplified silicon photonics process based on IMEC's Standard iSiPP50G Silicon Photonics Platform and a custom release process.

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity.

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function.

Relaxation of concentration variance: A new tool to measure chemical element mobility during mixing of magmas

The ability of chemical elements to diffuse in silicate melts is central to igneous processes. It controls the rates of phase transitions such as crystal growth and dissolution kinetics, the rate of homogenization of compositional gradients generated by fractional crystallization and assimilation of country rocks as well as one of the most intriguing processes of all, magma mixing.A very useful measure, commonly used to quantify the rate of homogenization of chemical elements in silicate melts, is the diffusion coefficient. It is widely approximated to be of a constant value (at a fixed pressure and temperature) for a melt with a given composition and rheology. When dealing with magma mixing processes, melts with different initial compositions and rheological properties (e.g. basalt and rhyolite) coexist in the same system. Under such circumstances, the compositional and rheological dependence of diffusion coefficients must be considered, leading to a considerable increase of complexity in the modeling of magma mixing. Yet, an additional and even more dramatic increase in complexity is due to the fact that the mixing of magmas is undoubtedly a very dynamic process. Scale-invariant distributions of filaments of different melts are generated by stretching and folding dynamics. This has a dual effect on the mobility of chemical elements. On the one hand their mobility increases because of an exponential increase of contact area. On the other hand, mobility can be buffered by the different diffusivities in the melts (larger in the low-viscosity than in the high-viscosity melt). Uphill diffusion of chemical elements is likely to develop at the interface between interacting magmas, further increasing the complexity of the process.Here we aim to understand chemical element mobility during melt homogenization in a magma mixing event under dynamic conditions. We have performed experiments by mixing phonolitic and alkali-basaltic melts. The mixing process was induced using a high-temperature centrifuge apparatus. The rotating speed and acceleration during all experiments were 1850rpm and 1000g, respectively. Experiments were performed for 5, 20 and 120min. Samples were arranged in a buoyantly unstable geometry, with the denser material placed at the inner side of the rotating circle, resulting in injection of the mafic melt into the felsic melt during rotation. The temperature during experimental runs was 1200 (±1)°C.From the resultant glasses, vortex-like structures generated by repeated stretching and folding dynamics were observed at the interface between the two melts. The concentrations of major and trace elements were then measured along interfaces by electron microprobe and LA-ICP-MS. The mobility of each element was next quantified by calculating the decrease (or relaxation) of concentration variance with time. The first notable result is that for major and trace elements, concentrations variance decays exponentially. The exponent of the exponential function is then chosen as a measure of element mobility. Our results show clearly that different chemical elements homogenize in the melt at differing rates. Amongst the major elements Na is the fastest element followed by Al, Mg, Ca, K and Si. The trace elements, Ba, Rb, Sr, Nb and Zr exhibit similar mobilities. The REE display the lowest mobility and they show a systematic decrease from light to heavy.The results from this study indicate that the decay of concentration variance is a robust tool for obtaining new insights into chemical exchanges during the mixing of silicate melts. Concentration variance includes in a single measure an expression of the influence of all possible factors (e.g. viscosity, composition, fluid-dynamic regime) controlling the mobility of chemical elements during the mixing of two liquids. A new parameter, the Relaxation of Concentration Variance (RCV), is proposed as an effective tool for quantifying the homogenization of chemical elements during the mixing of silicate melts.

Hardware architecture design of video compression for multimedia communication systems

VLSI realization of video compression is the key to many real-time multimedia communications systems. Among the video compression algorithms, the newly established MPEG-4 and, in particular, H.264 standards have become increasingly popular. However, the high coding efficiency of such video coding algorithms comes at the cost of a dramatic increase in complexity. Effective and efficient hardware solutions to this problem are necessary. In this article we present an overview of the hardware design issues of MPEG-4 and H.264. Both module and system architectures of these two coding standards are discussed. Based on these architectures, the design of a single-chip encoder complying with the H.264 baseline profile and capable of encoding the D1 resolution (720 x 480) video at 30 Hz is presented as an example. In addition, the system integration issues of video compression engines with multimedia communication systems and a general hardware platform for various applications are discussed.

The new paradigm for wireless network optimization: a synergy of automated processes and human intervention

With the evolution of wireless technologies, the optimization process for the radio access network has undergone a dramatic increase in complexity. This trend is driven by the introduction of multiple objectives for packet data services, the increasing network heterogeneity resulting from technology overlays, and the growing demand for nondisruptive optimization of operating networks. In a multidisciplinary effort, Bell Laboratories has developed a new optimization methodology that tackles these challenges using automated processes. We show that the paradigm shift toward automation requires the development of several interdependent algorithms each designed to cope with a particular optimization task. In the application described, human intervention proves indispensable; it demands a new kind of expertise that combines understanding of the automated processes with knowledge of network operation. Through examples we illustrate the variety of tasks that have to be automated and where guidance is needed through human control. The development of these automated processes is an important step toward dynamic optimization routines that are integrated into the network and adjust the network in a real-time manner.

Bifurcations of a particular forced Van der Pol Oscillator

The averaged equations of a forced non-linear oscillator, with both non-linear frictional and restoring forces, are considered as a two parameter system. The local and global bifurcations of the averaged two-parameter system are investigated. The local bifurcations are of Hopf and saddle-node type and are located in the parameter plane. The exceptional parameter points on the local bifurcation curves are investigated and the resulting global bifurcations are catalogued. Saddle connections, coalescence of limit cycles and saddle node creations on limit cycles are shown to occur using normal forms for vector fields and cycles without contact techniques. The behaviour shows the dramatic increase in complexity obtained by adding a nonlinear restoring force to the standard forced Van der Pol Oscillator.