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Purpose The purpose of this paper is to understand the enabling and constraining roles of blockchain technology (BCT) in managerial work practices and conceptualise the technology–performance relationship in supply chain management (SCM). Design/methodology/approach A structured literature review and a theory-driven approach are used. A set of propositions are developed, suggesting how the use of BCT in supply chains can be understood to simultaneously enable and constrain SCM and performance. Findings The analysis identifies four enabling and three constraining blockchain identities to explain how the technology either “facilitates” or “impedes” SCM and supply chain performance. Traceability, which emanates from its ability to provide data immutability, ranks highly as a core innovation of the technology. The blockchain is mainly seen as an opportunity to exploit existing supply chain resources and competencies. Research limitations/implications One limitation of the research is its conceptual nature. Future research should test the developed propositions empirically. Further research should focus on BCT as an opportunity to explore and as a relationship-building technology. More research is also needed focussing on the complex and simultaneous enabling and constraining effects of BCT in supply chains. Originality/value The paper shows the important and complex Janus-faced implications of embedding BCT in supply chains and demonstrates how organisational theory can be applied to explore the relationship between blockchain and SCM.

Exposure to news, opinion, and civic information increasingly occurs through social media. How do these online networks influence exposure to perspectives that cut across ideological lines? Using deidentified data, we examined how 10.1 million U.S. Facebook users interact with socially shared news. We directly measured ideological homophily in friend networks and examined the extent to which heterogeneous friends could potentially expose individuals to cross-cutting content. We then quantified the extent to which individuals encounter comparatively more or less diverse content while interacting via Facebook's algorithmically ranked News Feed and further studied users' choices to click through to ideologically discordant content. Compared with algorithmic ranking, individuals' choices played a stronger role in limiting exposure to cross-cutting content.

This paper proposes different short-circuit current limiting schemes using FSFCL on autotransformers, derives the equivalent models of installing the fast switch fault current limiter at different positions of autotransformers, and simulates the current limiting effect of each scheme using PSASP. The simulation results show that the fast switch fault current limiter on the side near the neutral point of the common winding of the autotransformer is the optimal scheme for comprehensive parameters.

For \\(p \\in (0,1)\\), sample a binary sequence from the infinite product measure of Bernoulli\\((p)\\) distributions. It is known that for \\(p=1/2\\), almost every binary sequence is Poisson generic in the sense of Peres and Weiss, a property that reflects a specific statistical pattern in the frequency of finite substrings. However, this behaviour is highly exceptional: it fails for any \\(p \\ne 1/2\\). In these other cases, we show that the frequency of substrings of almost every sequence has either trivial or peculiar behaviour. Nevertheless, the Poisson limiting regime can be recovered if one restricts attention to substrings with a fixed number of successes in the Bernoulli\\((p)\\) trials.

Many in-memory computing frameworks demand electronic devices with specific switching characteristics to achieve the desired level of computational complexity. Existing memristive devices cannot be reconfigured to meet the diverse volatile and non-volatile switching requirements, and hence rely on tailored material designs specific to the targeted application, limiting their universality. “Reconfigurable memristors” that combine both ionic diffusive and drift mechanisms could address these limitations, but they remain elusive. Here we present a reconfigurable halide perovskite nanocrystal memristor that achieves on-demand switching between diffusive/volatile and drift/non-volatile modes by controllable electrochemical reactions. Judicious selection of the perovskite nanocrystals and organic capping ligands enable state-of-the-art endurance performances in both modes – volatile (2 × 10 6 cycles) and non-volatile (5.6 × 10 3 cycles). We demonstrate the relevance of such proof-of-concept perovskite devices on a benchmark reservoir network with volatile recurrent and non-volatile readout layers based on 19,900 measurements across 25 dynamically-configured devices. Existing memristors cannot be reconfigured to meet the diverse switching requirements of various computing frameworks, limiting their universality. Here, the authors present a nanocrystal memristor that can be reconfigured on-demand to address these limitations

The factors constraining the development and implementation of filter-compensating installations are considered. The data on the limit values of the parameters of the elements of resonant circuits and the degree of their influence on the quality factor are summarized. It is shown that the main criterion for the efficiency of filter-compensating installations is to ensure the resistance of a sequential resonant circuit significantly less than the impedance of the power grid.

This paper studies sparse elliptic random matrix models which generalize both the classical elliptic ensembles and sparse i.i.d. matrix models by incorporating correlated entries and a tunable sparsity parameter \\(p_n\\). Each \\(n\\times n\\) matrix \\(X_n\\) is formed by entry-wise multiplication of an elliptic random matrix by an elliptic matrix of Bernoulli(\\(p_n\\)) variables, where \\(np_n\\to\\infty\\), allowing for interpolation between dense and sparse regimes. The main result establishes that under appropriate normalization, the empirical spectral measures of these matrices converge weakly in probability to the uniform measure on a rotated ellipsoid in the complex plane as the dimension \\(n\\) tends to infinity. Interestingly, the shape of the limiting ellipsoid depends not just on the mirrored entry-wise correlation structure, but also non-trivially on the sparsity limit \\(p=\\lim\\limits_{n\\to\\infty}p_n\\in[0,1]\\). The main result generalizes and recovers many classical results in sparse and dense regimes for elliptic and i.i.d. random matrix models.

Income-based energy poverty metrics ignore people’s behavior patterns, particularly reducing energy consumption to limit financial stress. We investigate energy-limiting behavior in low-income households using a residential electricity consumption dataset. We first determine the outdoor temperature at which households start using cooling systems, the inflection temperature. Our relative energy poverty metric, the energy equity gap , is defined as the difference in the inflection temperatures between low and high-income groups. In our study region, we estimate the energy equity gap to be between 4.7–7.5 °F (2.6–4.2 °C). Within a sample of 4577 households, we found 86 energy-poor and 214 energy-insecure households. In contrast, the income-based energy poverty metric, energy burden (10% threshold), identified 141 households as energy-insecure. Only three households overlap between our energy equity gap and the income-based measure. Thus, the energy equity gap reveals a hidden but complementary aspect of energy poverty and insecurity. In the summer, low-income households in the Arizona, US wait 4 - 7 °F (2.6–4.2 °C) longer than high-income households to turn on their AC units to save money on energy bills. This energy limiting behavior indicates a hidden form of energy poverty.

This paper studies Hausdorff-Young-type inequalities within the framework of Lorentz spaces \\(L_{p,q}\\). Focusing on the dependence of the associated constants on the integrability parameter \\(p\\), we derive optimal bounds in the limiting case \\(p\\rightarrow 2\\), addressing the Herz-Bochkarev problem. The results obtained refine the pioneering estimates in [3] and are comparable to recent advances in [16]. The main ingredients of our approach are new grand Lorentz space techniques.

A bstract Positivity bounds are powerful tools to constrain effective field theories. Utilizing the partial wave expansion in the dispersion relation and the full crossing symmetry of the scattering amplitude, we derive several sets of generically nonlinear positivity bounds for a generic scalar effective field theory: we refer to these as the P Q , D su , D stu and D ¯ stu bounds. While the PQ bounds and D su bounds only make use of the s ↔ u dispersion relation, the D stu and D ¯ stu bounds are obtained by further imposing the s ↔ t crossing symmetry. In contradistinction to the linear positivity for scalars, these inequalities can be applied to put upper and lower bounds on Wilson coefficients, and are much more constraining as shown in the lowest orders. In particular we are able to exclude theories with soft amplitude behaviour such as weakly broken Galileon theories from admitting a standard UV completion. We also apply these bounds to chiral perturbation theory and we find these bounds are stronger than the previous bounds in constraining its Wilson coefficients.