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1. Probabilistic Modeling of Information Dynamics in Networked Cyber-Physical-Social Systems

   https://doi.org/10.1109/JIOT.2021.3072893  

   Wang, Yan ( April 2021 , IEEE Internet of Things Journal)

   null (Ed.)

   Cyber-physical-social systems (CPSS) are physical devices with highly integrated functions of sensing, computing, communication and control, and are seamlessly embedded in human society. The levels of intelligence and functions that CPSS can perform rely on their extensive collaboration and information sharing through networks. In this paper, information diffusion within CPSS networks is studied. Information dynamics models are proposed to characterize the evolution of information processing and decision making capabilities of individual CPSS nodes. The data-driven statistical models are based on a mesoscale probabilistic graph model, where the individual nodes' sensing and computing functions are represented as the probabilities of correct predictions, whereas the communication functions are represented as the probabilities of mutual influences between nodes. A copula dynamics model is proposed to explicitly capture the information dependency among individuals with joint prediction probabilities and estimated from extremal probabilities. A topology-informed vector autoregression model is proposed to represent the mutual influence of prediction capabilities. A spatial-temporal hybrid Gaussian process regression model is also proposed to simultaneously capture correlations between nodes and temporal correlation in the time series. 

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2. Extending Coverage of Stationary Sensing Systems with Mobile Sensing Systems for Human Mobility Modeling

   https://doi.org/10.1145/3411827  

   Yang, Yu ; Fang, Zhihan ; Xie, Xiaoyang ; Zhang, Fan ; Liu, Yunhuai ; Zhang, Desheng ( September 2020 , Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies)

   Human mobility modeling has many applications in location-based services, mobile networking, city management, and epidemiology. Previous sensing approaches for human mobility are mainly categorized into two types: stationary sensing systems (e.g., surveillance cameras and toll booths) and mobile sensing systems (e.g., smartphone apps and vehicle tracking devices). However, stationary sensing systems only provide mobility information of human in limited coverage (e.g., camera-equipped roads) and mobile sensing systems only capture a limited number of people (e.g., people using a particular smartphone app). In this work, we design a novel system Mohen to model human mobility with a heterogeneous sensing system. The key novelty of Mohen is to fundamentally extend the sensing coverage of a large-scale stationary sensing system with a small-scale sensing system. Based on the evaluation on data from real-world urban sensing systems, our system outperforms them by 35% and achieves a competitive result to an Oracle method.

    

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3. Distributed Constraint Optimization Problem for Coordinated Response of Unmanned Aerial Vehicles and Ground Vehicles

   https://doi.org/10.1109/CISS50987.2021.9400249  

   Darko, Justice ; Folsom, Larkin ; Deshpande, Niharika ; Park, Hyoshin ( March 2021 , The 55th Annual Conference on Information Sciences and Systems)

   While there has been significant progress on statistical theories in the information community, there is a lack of studies in information-theoretic distributed resource allocation to maximize information gain. With advanced technologies of unmanned aerial vehicles (UAVs) in response to corresponding revised FAA regulations, this study focuses on developing a new framework for utilizing UAVs in incident management. As a result of new computing technologies, predictive decision-making studies have recently improved ERV allocations for a sequence of incidents; however, these ground-based operations do not simultaneously capture network-wide information. This study incorporates a real-time aerial view using UAVs with three key improvements. First, aerial observations update the status of the freeway shoulder, allowing an ERV to safely travel at full speed. Second, observing parameters of the congestion shockwave provides accurate measurements of the true impact of an incident. Third, real-time information can be gathered on the clearance progress of an incident scene. We automate UAV and ERV allocation while satisfying constraints between these vehicles using a distributed constraint optimization problem (DCOP) framework. To find the optimal assignment of vehicles, the proposed model is formulated and solved using the Max-Sum approach. The system utility convergence is presented for different scenarios of grid size, number of incidents, and number of vehicles. We also present the solution of our model using the Distributed Stochastic Algorithm (DSA). DSA with exploration heuristics outperformed the Max-Sum algorithm when probability threshold p=0.5 but degrades for higher values of p. 

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4. Building-level wastewater surveillance using tampon swabs and RT-LAMP for rapid SARS-CoV-2 RNA detection

   https://doi.org/10.1039/D1EW00496D  

   Bivins, Aaron ; Lott, Megan ; Shaffer, Marlee ; Wu, Zhenyu ; North, Devin ; Lipp, Erin K. ; Bibby, Kyle ( December 2021 , Environmental Science: Water Research & Technology)

   Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA has demonstrated useful correlation with both coronavirus disease 2019 (COVID-19) cases and clinical testing positivity at the community level. Wastewater surveillance on college campuses has also demonstrated promising predictive capacity for the presence and absence of COVID-19 cases. However, to date, such monitoring has most frequently relied upon composite samplers and reverse transcription quantitative PCR (RT-qPCR) techniques, which limits the accessibility and scalability of wastewater surveillance, particularly in low-resource settings. In this study, we trialed the use of tampons as passive swabs for sample collection and reverse transcription loop-mediated isothermal amplification (RT-LAMP), which does not require sophisticated thermal cycling equipment, to detect SARS-CoV-2 RNA in wastewater. Results for the workflow were available within three hours of sample collection. The RT-LAMP assay is approximately 20 times less analytically sensitive than RT-droplet digital PCR. Nonetheless, during a building-level wastewater surveillance campaign concurrent with independent weekly clinical testing of all students, the method demonstrated a three-day positive predictive value (PPV) of 75% (excluding convalescent cases) and same-day negative predictive value (NPV) of 80% for incident COVID-19 cases. These predictive values are comparable to that reported by wastewater monitoring using RT-qPCR. These observations suggest that even with lower analytical sensitivity the tampon swab and RT-LAMP workflow offers a cost-effective and rapid approach that could be leveraged for scalable building-level wastewater surveillance for COVID-19 potentially even in low-resource settings. 

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5. Bioinspired Hard-Soft Matter Interfaces for Applications in Electrocatalysis and Photoelectrosynthesis

   Moore, G. F. ; Wadsworth, B. L. ; Khusnutdinova, D. ; Beiler, A. M ; Reyes Cruz, E. A. ( April 2019 , Abstract of Papers, Materials and Research Society Spring Meeting and Exhibit)

   Human-engineered systems capable of generating fuels from sustainable energy sources provide an approach to satiating modern societies' energy demands, with minimal environmental impact. Strategies to address this challenge for science and the imagination often draw inspiration from the biological process of photosynthesis that powers our biosphere and supplied the fossil fuels global economies rely on. In this context, the active sites of enzymes have inspired researchers to develop molecular complexes that capture key structural and functional principles of nature's catalysts. However, not all aspects of biological energy transducing systems are or should be targets of chemical mimicry in designing an artificial photosynthesis, and some of the more favorable properties associated with solid-state heterogeneous catalysts have motivated molecular based surface-modification strategies. In this presentation, I will discuss efforts from our research group to develop heterogeneous–homogeneous architectures that combine the form factors of their underpinning solid-state supports with molecular coatings, enabling cooperative control and tunability of physical properties. 

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