搜索结果：Increases

This paper investigates the heterogeneous effects of military spending news shocks on household income and wealth inequality for a large, panel of advanced and emerging economies. Confirming prior literature, we find that military spending news shocks lead to persistent increases in aggregate output and Total Factor Productivity. Our primary contribution is documenting contrasting distributional impacts. We find that expansionary military spending is associated with a mitigation of income inequality, as income gains are disproportionately larger at the left tail of the distribution, primarily driven by a rise in labour income and employment in industry. Conversely, the shock is found to increase wealth inequality, particularly in high-income countries, by raising the wealth share of the top decile via effects on business asset holdings.

In the "Bits Through Queues" paper, it was hypothesized that full feedback always increases the capacity of first-in-first-out queues, except when the service time distribution is memoryless. More recently, a non-explicit sufficient condition under which feedback increases capacity was provided, along with simple examples of service times meeting this condition. While this condition yields examples where feedback is beneficial, it does not offer explicit structural properties of such service times. In this paper, we show that full feedback increases capacity whenever the service time has bounded support. This is achieved by investigating a generalized notion of feedback, with full feedback and weak feedback as particular cases.

Recent increases in the computational demands of deep neural networks (DNNs) have sparked interest in efficient deep learning mechanisms, e.g., quantization or pruning. These mechanisms enable the construction of a small, efficient version of commercial-scale models with comparable accuracy, accelerating their deployment to resource-constrained devices. In this paper, we study the security considerations of publishing on-device variants of large-scale models. We first show that an adversary can exploit on-device models to make attacking the large models easier. In evaluations across 19 DNNs, by exploiting the published on-device models as a transfer prior, the adversarial vulnerability of the original commercial-scale models increases by up to 100x. We then show that the vulnerability increases as the similarity between a full-scale and its efficient model increase. Based on the insights, we propose a defense, $similarity$-$unpairing$, that fine-tunes on-device models with the objective of reducing the similarity. We evaluated our defense on all the 19 DNNs and found that it reduces the transferability up to 90% and the number of queries required by a factor of 10-100x. Our results

Segregation on the basis of ethnic groups stands as a pervasive and persistent social challenge in many cities across the globe. Public spaces provide opportunities for diverse encounters but recent research suggests individuals adjust their time spent in such places to cope with extreme temperatures. We evaluate to what extent such adaptation affects racial segregation and thus shed light on a yet unexplored channel through which global warming might affect social welfare. We use large-scale foot traffic data for millions of places in 315 US cities between 2018 and 2020 to estimate an index of experienced isolation in daily visits between whites and other ethnic groups. We find that heat increases segregation. Results from panel regressions imply that a week with temperatures above 33°C in a city like Los Angeles induces an upward shift of visit isolation by 0.7 percentage points, which equals about 14% of the difference in the isolation index of Los Angeles to the more segregated city of Atlanta. The segregation-increasing effect is particularly strong for individuals living in lower-income areas and at places associated with leisure activities. Combining our estimates with clima

Carbon dioxide (CO2) increase has been well documented, and global net primary production is of importance to a variety of ecological topics. Since CO2 increases primary production in laboratory experiments, the global effects of increasing CO2 on global primary production are of interest in both climate science and ecology. Various studies have considered increases in primary production over different regions and time scales, but the global effects of increased atmospheric CO2 and primary production remain unquantified. This study aims to compare these two variables globally to assist in determining the potential for increases in primary production to contribute to carbon sequestration, possibly slowing increases in atmospheric CO2 resulting from fossil fuel emissions. Monthly CO2 concentration data from 1985 through 2015 in distinct latitude bands (every 10 degrees) was retrieved from the NOAA Earth System Research Laboratory for a total of 18 datasets. As a proxy to quantify net primary production, the magnitude of annual CO2 cycling was computed for each dataset through Fourier analysis. Relative increases were then calculated for both CO2 increase and amplitude increase to com

Quantum volume is a single-number metric which, loosely speaking, reports the number of usable qubits on a quantum computer. While improvements to the underlying hardware are a direct means of increasing quantum volume, the metric is "full-stack" and has also been increased by improvements to software, notably compilers. We extend this latter direction by demonstrating that error mitigation, a type of indirect compilation, increases the effective quantum volume of several quantum computers. Importantly, this increase occurs while taking the same number of overall samples. We encourage the adoption of quantum volume as a benchmark for assessing the performance of error mitigation techniques.

Distant planets in globally ice-covered, "snowball", states may depend on increases in their host stars' luminosity to become hospitable for surface life. Using a General Circulation Model (GCM), we simulated the equilibrium climate response of a planet to a range of instellations from an F-, G-, or M- dwarf star. The range of instellation that permits both complete ice cover and at least partially ice-free climate states is a measure of the climate hysteresis that a planet can exhibit. An ice-covered planet with high climate hysteresis would show a higher resistance to the initial loss of surface ice coverage with increases in instellation, and abrupt, extreme ice loss once deglaciation begins. Our simulations indicate that the climate hysteresis depends sensitively on the host star spectral energy distribution. Under fixed CO2 conditions, a planet orbiting an M-dwarf star exhibits a smaller climate hysteresis, requiring a smaller instellation to initiate deglaciation than planets orbiting hotter, brighter stars. This is due to the higher absorption of near-IR radiation by ice on the surfaces and greenhouse gases and clouds in the atmosphere of an M-dwarf planet. Increases in atmo

Many membrane-bound molecules in cells form small clusters. It has been hypothesized that these clusters convert an analog extracellular signal into a digital intracellular signal and that this conversion increases signaling fidelity. However, the mechanism by which clusters digitize a signal and the subsequent effects on fidelity remain poorly understood. Here we demonstrate using a stochastic model of cooperative cluster formation that sufficient cooperation leads to digital signaling. We show that despite reducing the number of output states, which decreases fidelity, digitization also reduces noise in the system, which increases fidelity. The tradeoff between these effects leads to an optimal cluster size that agrees with experimental measurements.

In the pool of people seeking partners, a uniformly greater preference for abstinence increases the prevalence of infection and worsens everyone's welfare. In contrast, prevention and treatment reduce prevalence and improve payoffs. The results are driven by adverse selection: people who prefer more partners are likelier disease carriers. A given decrease in the number of matches is a smaller proportional reduction for people with many partners, thus increases the fraction of infected in the pool. The greater disease risk further decreases partner-seeking and payoffs.

Toom's north-east-self voting cellular automaton rule R is known to suppress small minorities. A variant which we call R^+ is also known to turn an arbitrary initial configuration into a homogenous one (without changing the ones that were homogenous to start with). Here we show that R^+ always increases a certain property of sets called thickness. This result is intended as a step towards a proof of the fast convergence towards consensus under R^+. The latter is observable experimentally, even in the presence of some noise.

Consumers value keeping some information about them private from potential marketers. E-commerce dramatically increases the potential for marketers to accumulate otherwise private information about potential customers. Online marketers claim that this information enables them to better market their products. Policy makers are currently drafting rules to regulate the way in which these marketers can collect, store, and share this information. However, there is little evidence yet either of consumers' valuation of their privacy or of the benefits they might reap through better target marketing. We provide a framework for measuring a portion of the benefits from allowing marketers to make better use of consumer information. Target marketing is likely to reduce consumer search costs, improve consumer product selection decisions, and lower the marketing costs of goods sold. Our model allows us to estimate the value to consumers of only the latter, price reductions from more efficient marketing.

We demonstrate an improved concatenated encoded ancilla preparation procedure. Simulations show that this procedure significantly increases the error threshold beneath which arbitrarily long quantum computations are possible.