Particulate air pollution has been suggested as the cause of the recently observed decreasing trends of 10 to 25% in the ratio between hilly and upwind lowland precipitation, downwind of urban and industrial areas. We quantified the dependence of this ratio of the orographic-precipitation enhancement factor on the amounts of aerosols composed mostly of pollution in the free troposphere, based on measurements at Mt. Hua near Xi'an, in central China. The hilly precipitation can be decreased by 30 to 50% during hazy conditions, with visibility of less than 8 kilometers at the mountaintop. This trend shows the role of air pollution in the loss of significant water resources in hilly areas, which is a major problem in China and many other areas of the world.

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Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (W b ). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and W b of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by W b and the satellite-retrieved cloud base drop concentrations (N db ), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25°restricts the satellite coverage to ∼25% of the world area in a single day. (1) states that the uncertainty in aerosol/cloud interactions dominates the uncertainty about the degree of influence that human activities have on climate. Because clouds form in ascending air currents, whereas cloud droplets nucleate on aerosols that serve as cloud condensation nuclei (CCN), we need accurate measurements of both updrafts and CCN supersaturation (S) spectra before we can disentangle aerosol effects on cloud radiative forcing (CRF) from dynamical effects. Need for Global Measurements of Cloud Base Updrafts and CCN(S)Tackling the global change problems as identified by the IPCC requires that these quantities be measured on a global scale. However, satellites have not been able to measure updraft speed of the air that forms the clouds or the concentrations of aerosols that are capable of forming cloud drops, which are ingested into the clouds as they grow. Lack of such fundamental quantities has greatly hindered our capability of disentangling the effects of meteorology and anthropogenic aerosol emissions on cloud properties (2). This situation is starting to change with our recently developed methodology to retrieve updrafts at cloud base (3, 4) using the Visible/Infrared Imager Radiometer Suite (VIIRS) instrument onboard the Suomi National Polar-orbiting Partnership (NPP) satellite. This satellite is sun-synchronous, with an overpass time near 13:30 solar time.Missing such fundamental quantities as CCN(S) and cloud base updraft W b has been preventing us from disentangling the effects of aerosols from atmospheric dynamics (i.e., meteorology). Their absence also has limited our ability to validate the hypothesized impacts of added aerosols on a large range of phenomena, including (i) maintaining full cloud cover in marine stratocumulus, thus incurring a str...

Keeping user data private is a huge problem both in cloud computing and computation outsourcing. One paradigm to achieve data privacy is to use tamper-resistant processors, inside which users' private data is decrypted and computed upon. These processors need to interact with untrusted external memory. Even if we encrypt all data that leaves the trusted processor, however, the address sequence that goes off-chip may still leak information. To prevent this address leakage, the security community has proposed ORAM (Oblivious RAM). ORAM has mainly been explored in server/file settings which assume a vastly different computation model than secure processors. Not surprisingly, naïvely applying ORAM to a secure processor setting incurs large performance overheads.In this paper, a recent proposal called Path ORAM is studied. We demonstrate techniques to make Path ORAM practical in a secure processor setting. We introduce background eviction schemes to prevent Path ORAM failure and allow for a performance-driven design space exploration. We propose a concept called super blocks to further improve Path ORAM's performance, and also show an efficient integrity verification scheme for Path ORAM. With our optimizations, Path ORAM overhead drops by 41.8%, and SPEC benchmark execution time improves by 52.4% in relation to a baseline configuration. Our work can be used to improve the security level of previous secure processors.

[1] Heavy aerosol loads have been observed to suppress warm rain by reducing cloud drop size and slowing drop coalescence. The ice forming nuclei (IFN) activity of the same aerosols glaciate the clouds and create ice precipitation instead of the suppressed warm rain. Satellite observations show that desert dust and heavy air pollution over East Asia have similar ability to glaciate the tops of growing convective clouds at glaciation temperature of Tg < ∼ −20°C, whereas similarly heavy smoke from forest fires in Siberia without dust or industrial pollution glaciated clouds at Tg ≤ −33°C. The observation that both smoke and air pollution have same effect on reducing cloud drop size implies that the difference in Tg is due to the IFN activity. This dependence of Tg on aerosol types appears only for clouds with r e-5 < 12 mm (r e-5 is the cloud drop effective radius at the −5°C isotherm, above which ice rarely forms in cloud tops). For the rest of the clouds the glaciation temperature increases strongly with r e-5 with little relation to the aerosol types, reaching Tg> ∼ −15°C for the largest r e-5 , which are typical to marine clouds in pristine atmosphere. Citation:

Abstract. The rapid mass increase of atmospheric nitrate is a critical driving force for the occurrence of fine-particle pollution (referred to as haze hereafter) in Beijing. However, the exact mechanisms for this rapid increase of nitrate mass have not been well constrained from field observations. Here we present the first observations of the oxygen-17 excess of atmospheric nitrate (Δ17O(NO3-)) collected in Beijing haze to reveal the relative importance of different nitrate formation pathways, and we also present the simultaneously observed δ15N(NO3-). During our sampling period, 12 h averaged mass concentrations of PM2.5 varied from 16 to 323 µg m−3 with a mean of (141±88(1SD)) µg m−3, with nitrate ranging from 0.3 to 106.7 µg m−3. The observed Δ17O(NO3-) ranged from 27.5 ‰ to 33.9 ‰ with a mean of (30.6±1.8) ‰, while δ15N(NO3-) ranged from −2.5 ‰ to 19.2 ‰ with a mean of (7.4±6.8) ‰. Δ17O(NO3-)-constrained calculations suggest nocturnal pathways (N2O5+H2O/Cl- and NO3+HC) dominated nitrate production during polluted days (PM2.5≥75 µg m−3), with a mean possible fraction of 56–97 %. Our results illustrate the potentiality of Δ17O in tracing nitrate formation pathways; future modeling work with the constraint of isotope data reported here may further improve our understanding of the nitrogen cycle during haze.

Purpose The purpose of this paper is to examine the roles of four distinct but related aspects of psychological capital – optimism, hope, self-efficacy and resilience – in facilitating employee creativity. Drawing on the psychological capital perspective and the creativity literature, we propose that optimism and hope increase employee self-efficacy and resilience, which benefits employee creativity. Moreover, the authors hypothesize that self-efficacy and resilience have mediating roles in the psychological capital context, which, in turn, has a positive effect on individual employees’ creativity. Design/methodology/approach Data were obtained from a survey of multiple manufacturing firms on individual employee psychological capital and creativity. Structural equation modeling was used to test the hypotheses regarding psychological capital and creativity in a sample of 468 individual employees. Findings The results provide evidence that only resilience plays a mediating role between optimism and hope and employee creativity. The authors found that psychological capital is positively related to employee creativity. Practical implications These findings provide guidance for understanding how to better address the psychological capital that contributes to employee creativity in the workplace. Specifically, this study provides a rationale for facilitating the development of employee creativity by exposing the effect and path of psychological capital. Originality/value This study is the first to examine the antecedents and mediating role of four distinct yet correlated dimensions of psychological capital on employee creativity. The findings of this study contribute to the theoretical development of a conceptual model that investigates the black box of the four aspects of psychological capital and creativity.

This study demonstrates a combined application of chaos theory and support vector machine (SVM) in the analysis of chaotic time series with a very large sample data record. A large data record is often required and causes computational difficulty. The decomposition method is used in this study to circumvent this difficulty. The various parameters inherent in chaos technique and SVM are optimised, with the assistance of an evolutionary algorithm, to yield the minimal prediction error. The performance of the proposed scheme, EC-SVM, is demonstrated on two daily runoff time series: Tryggevælde catchment, Denmark and the Mississippi River at Vicksburg. The prediction accuracy of the proposed scheme is compared with that of the conventional approach and the recently introduced inverse approach. This comparison shows that EC-SVM yields a significantly lower normalised RMSE value of 0.347 for the Tryggevælde catchment runoff and 0.0385 for the Mississippi River flow compared to 0.444 and 0.2064, respectively, resulting from the conventional approach. A slight improvement in accuracy was obtained by analysing the first difference or the daily flow difference time series. It should be noted, however, that the computational speed in analysing the daily flow difference time series is significantly much faster than that of the daily flow time series.