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This study explicates a concept of transactive resilience for cross-sector disaster communication via integrating the transactive memory system and the network theory of social capital. The concept was validated through n=34 in-depth interviews with key disaster-responding organizations (public, private, and nonprofits sectors) of a U.S. city. Findings indicate that transactive resilience network is built on strong relational trust (interpersonal and informal relationships), perceived expertise (consensus/accuracy), and coordination and communication (two-way, flexibility, and optimal network characteristics). 

We present our latest development and experimental validation of carrier cooperative recovery for enhancing the resilience of optical packet transport networks. Experimental results prove that in case of resource crunch caused by, e.g., traffic congestion, failures, man-made/natural disasters, etc., swift and low-cost recovery can be achieved by exploiting the interconnection capability among carriers, which demonstrates a novel use case of multi-carrier interconnection technology. 

ABSTRACT:This study explores a rapid and precise method for micromechanical characterization and mapping of heterogeneous rocks, utilizing high-speed nanoindentation and mineral volume fractions. Traditional method for determination of mechanical properties of the different phases of a heterogeneous material require the combination of nanoindentation data and chemical analysis of the material. However, this results in increasing the cost, time, and complexity of the process. Hence, the proposed study explores different data mining techniques such as Uniform Manifold Approximation and Projection (UMAP) with k-means clustering, Dirichlet Process Mixture Model (DPMM) clustering, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), utilizing high speed nanoindentation data for an efficient and accurate evaluation of the micromechanical properties of heterogeneous shale rock. Comparison of the three techniques deduced that UMAP with k-means clustering technique provides appropriate micromechanical characterization and mapping results with a weighted error of about 13.40%. Even DPMM and DBSCAN performed reasonably well with slightly high weighted errors, therefore they can be adopted as a secondary clustering technique for validation of other clustering technique results. The results demonstrate the potential and efficiency of high-speed nanoindentation test in conjunction with data analytics for characterization and mapping of micromechanical properties of heterogeneous material. 

Frost heave of soil extensively exists in northern regions and poses a significant threat to infrastructure in cold regions. Despite over a century of research, challenges persist in numerically simulating frost heave. This study addresses two key issues: (1) What is the primary driving force for liquid water transfer during the freezing process? (2) How can we correctly represent unfrozen water content? Critical insights are derived from the theoretical analysis of coupled hydrothermal migration during soil freezing processes, followed by a case simulation using COMSOL Multiphysics. It concludes that of the water content gradient, suction gradient, and hydraulic gradient, only the hydraulic gradient is the fundamental driving force for liquid water flow. Moreover, unfrozen water content is an intrinsic property of frozen soil and should not be indirectly determined by assessing ice content. This study enhances our understanding of the frost heave mechanism and contributes to developing a unified model for frost heave. 

We present the development, architecture, and features of a new multi-device mHealth software platform to support near real-time remote monitoring of metabolic health and timely intervention in the treatment and survivorship of cancer patients. Our platform, mEnergy, leverages a human- centered design process, and integrates in a unified, web-based framework consumer-grade hardware—Fitbit wearable sensor devices, smartphones, and Withings smart scales. mEnergy can aid oncologists in identifying early indicators of muscle-wasting (sarcopenia) due to sleep disturbance, insufficient weight recov- ery, or reduced/limited activity. The platform aims for a smooth transition into clinical practice and increased adherence to evidence-based recommendations, in particular in underserved geographical areas. This toxicity-surveillance approach based on mHealth technologies can improve treatment outcomes, quality of life, and survivorship