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In the era of big data, the unprecedented growth of data has been regarded as an important asset and the commercial application of data acquisition markets has emerged accordingly. With the advancement of vehicle manufacturing and sensor technologies, a large amount of data can be collected and stored in electric vehicles (EVs), making the data acquisition scenario gradually extend to the Internet of Vehicles (IoV), and thus the corresponding operational rules and economic feasibility need to be fully investigated there. In this article, we focus on a general IoV-oriented data acquisition market that consists of a data center, multiple EVs, multiple roadside units (RSUs), and a market operator (broker), with the objective of social welfare maximization (SWM) by identifying the optimal data task allocation. However, due to the inherent information asymmetry and fragmentation in such a market, it is not feasible to solve the SWM problem directly. To this end, we propose an iterative double-sided auction (IDA) mechanism, which leverages the self-interested feature of RSUs and EVs to decompose the SWM problem, enabling every participant to make decisions in a distributed manner under the broker’s coordination. A complete set of operational rules covering the data task allocation, bidding, payment, and reimbursement are elaborately designed to achieve SWM, and energy is adopted as the pricing “currency,” such that an IDA-based data-energy transaction (IDADET) ecosystem is established in IoV. We verify the economic feasibility of the proposed IDADET ecosystem by showing its convergence and desirable properties of individual rationality, budget balance, incentive compatibility, and economic efficiency. In addition, considering the psychological effects of practical market participants, we make amendments to the operational rules of the IDADET ecosystem from the behavioral economics perspective, aiming to ensure its long-term well functioning. Extensive numerical r

Water is critical in the evolution of the mantle due to its strong influence on the physicochemical properties of mantle rocks. Mid-ocean ridge basalts (MORBs) are commonly used to study the compositional characteristics of the convecting upper mantle. However, there remains abundant samples in the global MORB data sets without direct measurements of water contents. The commonly observed good correlation between H₂O and other incompatible trace components, such as Ce, has been applied to quantify water contents of MORBs. However, this approach assumes constant H₂O/Ce in the target samples, which is not always true as the H₂O/Ce ratios of MORBs could be rather heterogeneous even in some short ridge segments. Utilizing the present compositional data of global MORB glasses with measured water contents (n = 1,467), we construct a Random Forest Regression model based on machine learning, which can predict water concentrations of samples based on selected major and trace element data, without assuming a ratio between H₂O and other trace elements. This model allows us to precisely recover water contents for MORBs with comparable accuracy with traditional analytical methods. The predicted results of MORB glasses from this model (n = 1,931) expand the water content database of global MORBs and indicate a broad existence of high-H₂O MORBs. This new approach allows us to investigate the water content of MORBs from some ridges lacking previous water content measurements (e.g., the Chile Ridge and the Pacific-Antarctic Ridge) and infer changes in the water content of MORB sources through applying the model to transform fault samples.

The Early Cretaceous Jehol Biota evolution has remarkable spatiotemporal correlation with the destruction of the North China craton though the coupling mechanism remains enigmatic. The craton destruction was accompanied by intense magmatic activity and the released volatiles and nutrients might have had climatic and environmental impacts on the biotic evolution. In this study, we investigated the mentioned hypothetical causal link by determining concentrations and total emissions of volatile elements (S, F, Cl) and bulk-rock P contents of volcanic rocks that were erupted during the pre-flourishing, flourishing and post-flourishing stages of the Jehol Biota. Our results show that the volcanism near the flourishing stage has lower S (1,083–2,370 ppm), Cl (1,277–5,608 ppm) and higher P₂O₅ contents (0.48–0.84 wt.%) than that in the non-flourishing stages with S of 1,991–3,288 ppm, Cl of 7,915–12,315 ppm and P₂O₅ of 0.17–0.23 wt.%. Fluorine contents in the three stages vary from 893 to 3,746 ppm. The total volatile emissions are minor in the flourishing stage (1–14 Gt S, 0.6–10 Gt Cl, 0.6–9 Gt F) but elevated in the non-flourishing stages (2–766 Gt S, 4–1,168 Gt Cl, 1–175 Gt F). Our data suggest that regional climatic and environmental impacts of volcanism in the non-flourishing stages probably hindered the species diversification. The high P flux released from lithospheric mantle-derived lavas during the peak time of craton destruction might have enhanced primary productivity and contributed to the flourishing of the Jehol Biota. Our study provides insights into the relationship between the biosphere and deep geodynamic processes driven by volcanism.

The efficient buffer space management in intermittently connected Internet of Things (IC-IoT) is of great importance for data delivery performance guarantee in such networks. This article considers two typical buffer space management policies for IC-IoT, i.e., buffer-space sharing (BS) and buffer-space allocation (BA). The BS policy allows the buffer space of each device to be fully shared by the exogenous packets and the packets from other devices, while the BA policy divides the buffer space into the source buffer and relay buffer for storing the two kinds of packets separately. With the help of the queueing theory and Markov chain theory, we develop a theoretical framework to capture the sophisticated queueing processes for the buffer space under either BS or BA policy, which enables the limiting distribution of the buffer occupation state to be determined. We then provide theoretical modeling for throughput and expected end-to-end delay to evaluate the fundamental performance of the IC-IoT under the BS and BA policies. Finally, extensive simulation and numerical results are presented to validate theoretical models and to demonstrate the effects of BS and BA policies on the IC-IoT performance.

This article focuses on the secure routing problem in the decentralized Internet of Things (IoT). We consider a typical decentralized IoT scenario composed of peer legitimate devices, unauthorized devices (eavesdroppers), and selfish helper jamming devices (jammers), and propose a novel incentive jamming-based secure routing scheme. For a pair of source and destination, we first provide theoretical modeling to reveal how the transmission security performance of a given route is related to the jamming power of jammers in the IoT. Then, we design an incentive mechanism with which the source pays some rewards to stimulate the artificial jamming among selfish jammers, and also develop a two-stage Stackelberg game framework to determine the optimal source rewards and jamming power. Finally, with the help of the theoretical modeling as well as the source rewards and jamming power setting results, we formulate a shortest weighted path-finding problem to identify the optimal route for secure data delivery between the source-destination pair, which can be solved by employing the Dijkstra’s or Bellman-Ford algorithm. We prove that the proposed routing scheme is individually rational, stable, distributed, and computationally efficient. Simulation and numerical results are provided to demonstrate the performance of our routing scheme.

Background: There is little evidence on the use of secondary prevention medicines for cardiovascular disease by socioeconomic groups in countries at different levels of economic development. Methods: We assessed use of antiplatelet, cholesterol, and blood-pressure-lowering drugs in 8492 individuals with self-reported cardiovascular disease from 21 countries enrolled in the Prospective Urban Rural Epidemiology (PURE) study. Defining one or more drugs as a minimal level of secondary prevention, wealth-related inequality was measured using the Wagstaff concentration index, scaled from −1 (pro-poor) to 1 (pro-rich), standardised by age and sex. Correlations between inequalities and national health-related indicators were estimated. Findings: The proportion of patients with cardiovascular disease on three medications ranged from 0% in South Africa (95% CI 0–1·7), Tanzania (0–3·6), and Zimbabwe (0–5·1), to 49·3% in Canada (44·4–54·3). Proportions receiving at least one drug varied from 2·0% (95% CI 0·5–6·9) in Tanzania to 91·4% (86·6–94·6) in Sweden. There was significant (p<0·05) pro-rich inequality in Saudi Arabia, China, Colombia, India, Pakistan, and Zimbabwe. Pro-poor distributions were observed in Sweden, Brazil, Chile, Poland, and the occupied Palestinian territory. The strongest predictors of inequality were public expenditure on health and overall use of secondary prevention medicines. Interpretation: Use of medication for secondary prevention of cardiovascular disease is alarmingly low. In many countries with the lowest use, pro-rich inequality is greatest. Policies associated with an equal or pro-poor distribution include free medications and community health programmes to support adherence to medications. Funding: Full funding sources listed at the end of the paper (see Acknowledgments).

The genesis of large igneous provinces (LIP) is controlled by multiple factors including anomalous mantle temperatures, the presence of fusible fertile components and volatiles in the mantle source, and the extent of decompression. The lack of a comprehensive examination of all these factors in one specific LIP makes the mantle plume model debatable. Here, we report estimates of the water content in picrites from the Emeishan LIP in southwestern China. Although these picrites display an island arc-like H2O content (up to 3.4 by weight percent), the trace element characteristics do not support a subduction zone setting but point to a hydrous reservoir in the deep mantle. Combining with previous studies, we propose that hydrous and hot plumes occasionally appeared in the Phanerozoic era to produce continental LIPs (e.g., Tarim, Siberian Trap, Karoo). The wide sampling of hydrous reservoirs in the deep mantle by mantle plumes thus indicates that the Earth’s interior is largely hydrated.

This research examines the effect of experiencing messiness, induced by a messy environment or by priming the concept of messiness, on consumers. We propose that messiness is an aversive state and consumers are motivated to attenuate this state by seeking simplicity in their cognitions, preferences, and choices. Six experiments support our theorizing. Experiments 1a-1c (conducted in the laboratory) and experiment 2 (conducted in the field) demonstrate that when messiness is salient, consumers form simpler product categorizations, are willing to pay more for a t-shirt with a simple picture, and seek less variety in their choices. Experiment 3 brings additional evidence for the underlying role of the need for simplicity by showing that when the need for simplicity is satiated, the effects of messiness disappear. A final experiment shows a boundary condition of the messiness effect: political conservatives are more susceptible to messiness primes compared to liberals.