Abstract. We consider applications scenarios where an untrusted aggregator wishes to continually monitor the heavy-hitters across a set of distributed streams. Since each stream can contain sensitive data, such as the purchase history of customers, we wish to guarantee the privacy of each stream, while allowing the untrusted aggregator to accurately detect the heavy hitters and their approximate frequencies. Our protocols are scalable in settings where the volume of streaming data is large, since we guarantee low memory usage and processing overhead by each data source, and low communication overhead between the data sources and the aggregator.

Hyperpolarization-activated currents (Ih) mediated by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels modulate excitability of myelinated A− and Ah-type visceral ganglion neurons (VGN). Whether alterations in Ih underlie the previously reported reduction of excitability of myelinated Ah-type VGNs following ovariectomy (OVX) has remained unclear. Here we used the intact nodose ganglion preparation in conjunction with electrophysiological approaches to examine the role of Ih remodeling in altering Ah-type neuron excitability following ovariectomy in adult rats. Ah-type neurons were identified based on their afferent conduction velocity. Ah-type neurons in nodose ganglia from non-OVX rats exhibited a voltage ‘sag’ as well as ‘rebound’ action potentials immediately following hyperpolarizing current injections, which both were suppressed by the Ih blocker ZD7288. Repetitive spike activity induced afterhyperpolarizations lasting several hundreds of milliseconds (termed post-excitatory membrane hyperpolarizations, PEMHs), which were significantly reduced by ZD7288, suggesting that they resulted from transient deactivation of Ih during the preceding spike trains. Ovariectomy reduced whole-cell Ih density, caused a hyperpolarizing shift of the voltage-dependence of Ih activation, and slowed Ih activation. OVX-induced Ih remodeling was accompanied by a flattening of the stimulus frequency/response curve and loss of PEMHs. Also, HCN1 mRNA levels were reduced by ∼30% in nodose ganglia from OVX rats compared with their non-OVX counterparts. Acute exposure of nodose ganglia to 17beta-estradiol partly restored Ih density and accelerated Ih activation in Ah-type cells. In conclusion, Ih plays a significant role in modulating the excitability of myelinated Ah-type VGNs in adult female rats.

Global pandemics, such as the Coronavirus Disease 2019 (COVID-19), have serious harmful effects on people′s physical health and mental well-being. It is imperative therefore that we seek to understand community resilience and identify ways to enhance this, especially within our cities and communities. Therefore, great emphasis is now placed on how cities prepare for and recover from such disasters, and community resilience has emerged as a key consideration. Drawing upon research on the theory of resilience, this study seeks to identify the factors that influence community resilience and to analyze their causation toward helping to manage the risks associated with the COVID-19 pandemic. Seventeen factors from the five dimensions of social capital, economic capital, physical environment, demographic characteristics, and institutional factors are used to construct an index system. This is used to establish the structural level and importance of each factor. Data were collected using a questionnaire survey involving 12,000 members of key community groups in the city of Wuhan. An interpretative structural model (ISM) combining the analytic hierarchy process (AHP) method was then used to obtain the multi-level hierarchical structure composed of direct factors, indirect factors, and fundamental factors. The results show that the income level, vulnerability of the population, and the built environment are the main factors that affect the resilience of communities affected by COVID-19. These findings provide useful guidance toward the effective planning and design of urban construction and infrastructure. The results are expected to be useful to inform future decision-making and toward the long term, sustainable management of the risks posed by COVID-19.

Nodose ganglia are composed of A-, Ah- and C-type neurons. Despite their important roles in regulating visceral afferent function, including cardiovascular, pulmonary, and gastrointestinal homeostasis, information about subtype-specific expression, molecular identity, and function of individual ion transporting proteins is scarce. Although experiments utilizing the sliced ganglion preparation have provided valuable insights into the electrophysiological properties of nodose ganglion neuron subtypes, detailed characterization of their electrical phenotypes will require measurements in isolated cells. One major unresolved problem, however, is the difficulty to unambiguously identify the subtype of isolated nodose ganglion neurons without current-clamp recording, because the magnitude of conduction velocity in the corresponding afferent fiber, a reliable marker to discriminate subtypes in situ, can no longer be determined. Here, we present data supporting the notion that application of an algorithm regarding to microscopic structural characteristics, such as neuron shape evaluated by the ratio between shortest and longest axis, neuron surface characteristics, like membrane roughness, and axon attachment, enables specific and sensitive subtype identification of acutely dissociated rat nodose ganglion neurons, by which the accuracy of identification is further validated by electrophysiological markers and overall positive predictive rates is 89.26% (90.04%, 76.47%, and 98.21% for A-, Ah, and C-type, respectively). This approach should aid in gaining insight into the molecular correlates underlying phenotypic heterogeneity of nodose ganglia. Additionally, several critical points that help for neuron identification and afferent conduction calibration are also discussed.

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