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  1. null (Ed.)
    The relationships between crop yields and meteorology are naturally non-stationary because of spatiotemporal heterogeneity. Many studies have examined spatial heterogeneity in the regression model, but only limited research has attempted to account for both spatial autocorrelation and temporal variation. In this article, we develop a novel spatiotemporally varying coefficient (STVC) model to understand non-stationary relationships between crop yields and meteorological variables. We compare the proposed model with variant models specialized for time or spatial, namely spatial varying coefficient (SVC) model and temporal varying coefficient (TVC) model. This study was conducted using the county-level corn yield and meteorological data, including seasonal Growing Degree Days (GDD), Killing Degree Days (KDD), Vapor Pressure Deficit (VPD), and precipitation (PCPN), from 1981 to 2018 in three Corn Belt states, including Illinois, Indiana, and Iowa. Allowing model coefficients varying in both temporal and spatial dimensions gives the best performance of STVC in simulating the corn yield responses toward various meteorological conditions. The STVC reduced the root-mean-square error to 10.64 Bu/Ac (0.72 Mg/ha) from 15.68 Bu/Ac (1.06 Mg/ha) for TVC and 16.48 Bu/Ac (1.11 Mg/ha) for SVC. Meanwhile, the STVC resulted in a higher R2 of 0.81 compared to 0.56 for SVC and 0.64 for TVC. The STVC showed better performance in handling spatial dependence of corn production, which tends to cluster estimation residuals when counties are close, with the lowest Moran’s I of 0.10. Considering the spatiotemporal non-stationarity, the proposed model significantly improves the power of the meteorological data in explaining the variations of corn yields. 
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  2. Banerjee, A. ; Fukumizu, K. (Ed.)
    We establish the consistency of K-medoids in the context of metric spaces. We start by proving that K-medoids is asymptotically equivalent to K-means restricted to the support of the underlying distribution under general conditions, including a wide selection of loss functions. This asymptotic equivalence, in turn, enables us to apply the work of Pärna (1986) on the consistency of K-means. This general approach applies also to non-metric settings where only an ordering of the dissimilarities is available. We consider two types of ordinal information: one where all quadruple comparisons are available; and one where only triple comparisons are available. We provide some numerical experiments to illustrate our theory. 
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  3. reveal the mechanism of intermittent coupling, where the nodes are connected merely in discontinuous time durations. Instead of the common weighted average technique, by proposing a direct error method and constructing piecewise Lyapunov functions, several intermittently adaptive designs are developed to update the complex-valued coupling weights. Especially, an adaptive pinning protocol is designed for ICCVNs with heterogeneous coupling weights and the synchronization is ensured by piecewise adjusting the complex-valued weights of edges within a spanning tree. For ICCVNs with homogeneous coupling weights, based on a connected dominating set, an intermittently adaptive algorithm is developed which just depends on the information of the dominating set with their neighbors. At the end, the established theoretical results are verified by providing two numerical examples. 
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  4. null (Ed.)
    A non-aqueous proton electrolyte is devised by dissolving H3PO4 into acetonitrile. The electrolyte exhibits unique vibrational signatures from stimulated Raman spectroscopy. Such an electrolyte exhibits unique characteristics compared to aqueous acidic electrolytes: 1) higher (de)protonation potential for a lower desolvation energy of protons, 2) better cycling stability by dissolution suppression, and 3) higher Coulombic efficiency owing to the lack of oxygen evolution reaction. Two non-aqueous proton full cells exhibit better cycling stability, higher Coulombic efficiency, and less self-discharge compared to the aqueous counterpart. 
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  5. Abstract—Excessive power during in–field testing can cause multiple issues, including invalidation of the test results, overheating, and damage to the circuit. In this paper, we evaluate the reduction of capture power when specific segments of a scan chain can be kept from capturing data subject to values stored in a control register. The proposed approach requires no changes to the Automatic Test Pattern Generation (ATPG), no redesign of the circuitry to match a particular test set, and no additional patterns to maintain fault coverage. We will show that our approach can achieve very high capture power reduction—approaching 100% for multiple patterns. Index Terms—Design for Testability (DFT), Low Power Test, On-Chip Decompressor 
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  6. null (Ed.)
    Abstract. This study streamlines modeling of the gas–wall process (GWP) of semivolatile organic compounds (SVOC) by predicting gas–wall equilibrium partitioning constant (𝐾𝑤,𝑖 ) and accommodation coefficient (α𝑤,𝑖) of SVOC(i) using a quantitative structure–activity relationship. PaDEL-Descriptor, software that calculates molecular descriptors, is employed to obtain physicochemical parameters (i.e., hydrogen bond acidity (𝐻𝑑,𝑖), hydrogen bond basicity (𝐻𝑎,𝑖), dipolarity/polarizability (𝑆𝑖), and polarizability (α𝑖)) of SVOC(i). For the prediction of 𝐾𝑤,𝑖, activity coefficients (γw,i) of SVOC(i) to the chamber wall are semiempirically predicted using chamber data in the form of a polynomial equation coupled with the physicochemical parameters. 𝛾𝑤,𝑖 of various SVOCs differ in functionalities and molecular sizes ranging from 100 to 104. We conclude that the estimation of 𝛾𝑤,𝑖 is essential to improve the prediction of 𝐾𝑤,𝑖. To predict the impact of relative humidity (RH) on GWP, each coefficient in the polynomial equation for ln(𝐾𝑤,𝑖) was correlated to RH. Increasing RH enhanced GWP significantly for all polar SVOCs. For example, the predicted 𝐾𝑤,𝑖 of 1-heptanoic acid increased more than three times (from 0.58 to 1.96) by increasing RH from 0.4 to 0.75 due to the reduction in 𝛾𝑤,𝑖. The characteristic time for GWP are estimated using 𝐾𝑤,𝑖 and α𝑤,𝑖 to evaluate the effect of GWP on secondary organic aerosol (SOA) mass. It might be significant in the absence of inorganic aerosol, but insignificant in the presence of electrolytic salts, where aqueous reactions dominate SOA growth. 
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