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Privacy amplification means that the communication parties extract a shorter but highly confidential string [S] by negotiating on the public channel while sharing a partially confidential string S. Enemy only knows part of the information of the string S and the information that it knows about [S] is almost negligible. Recently, people use the generative adversarial networks (GANs) to realize the secure communication with the present of the adversary. This paper proposes to use the generative adversarial network to achieve a privacy amplification scheme when the adversary ability is limited. First, this paper proposes a privacy amplification implementation scenario. The two parties use the conversation information to generate identical keys, and the adversary listens to the conversation information. Then, with reference to the neural network structure in the basic encrypted communication model of Abadi et al., a privacy amplified communication model is built. The experiment tests the privacy amplified communication when the enemy knows part of the information or the opponent's computing power is weak. By modifying the activation function, increasing the complexity of the model and modifying the filter of convolutional neural network, the final results show that when the adversary gets 70% of the communication information, or when the communicator is more complex than the adversary model, both parties can negotiate a secure key to complete the function of security enhancement.

PurposeThe purpose of this paper is to bring out the development of a flexible model for nonstationary crop yield distributions and its applications to decision-making in crop insurance.Design/methodology/approachThe authors design a nonparametric Bayesian approach based on Gaussian process regressions to model crop yields over time. Further flexibility is obtained via Bayesian model averaging that results in mixed Gaussian processes.FindingsSimulation results on crop insurance premium rates show that the proposed method compares favorably with conventional estimators, especially when the underlying distributions are nonstationary.Originality/valueUnlike conventional two-stage estimation, the proposed method models nonstationary crop yields in a single stage. The authors further adopt a decision theoretic framework in its empirical application and demonstrate that insurance companies can use the proposed method to effectively identify profitable policies under symmetric or asymmetric loss functions.

This study is motivated by the estimation of many crop yield densities, each with a small number of observations. These densities tend to resemble one another if they are spatially proximate. To gain flexibility and improve efficiency, we propose kernel-based estimators refined by empirical likelihood probability weights derived under spatially smoothed moment conditions. We construct spatially smoothed moments based on spline functions, which are robust to outliers and readily customizable. We use these methods to estimate the corn yield distributions of Iowa counties and to predict the premiums of crop insurance programs. Monte Carlo simulations and an empirical application demonstrate the good performance and usefulness of the proposed methods.

This paper applies a novel nonparametric estimator to the modeling of auctions subject to shape restrictions. In particular, we employ a Bayesian estimator with a Gaussian process prior parameterized by a spectral representation. We use squared Gaussian processes to model the functional derivatives and therefore are able to impose global shape restrictions. Our first application is the estimation of a monotonically increasing bidding process of online auctions. The second application concerns the estimation of bidders’ risk-averse latent preferences in sealed-bid timber auctions. The results show that the shape-constrained estimator not only ensures the conformity with economic theories but also improves estimation precision.

Peritoneal carcinomatosis (PC) has an extremely poor prognosis, which leads to a significantly decreased overall survival in patients with peritoneal implantation of cancer cells. Administration of sodium selenite by intraperitoneal injection is highly effective in inhibiting PC. Our previous study found that selenium nanoparticles (SeNPs) have higher redox activity and safety than sodium selenite. In the present study, we examined the therapeutic effect of SeNPs on PC and elucidated the potential mechanism. Our results revealed that intraperitoneal delivery of SeNPs to cancer cells in the peritoneal cavity of mice at a tolerable dose was beneficial for prolonging the survival time of mice, even better than the optimal dose of cisplatin. The underlying mechanism involved in SeNP-induced reactive oxygen species (ROS) production caused protein degradation and apoptotic response in cancer cells. Interestingly, N-acetyl-l-cysteine (NAC), recognized as a ROS scavenger, without reducing the efficacy of SeNPs, enhanced ROS production and cytotoxicity. The effect of NAC was associated with the following mechanisms: (1) the thiol groups in NAC can increase the biosynthesis of endogenous glutathione (GSH), thus increasing the production of SeNP-induced ROS and cytotoxicity and (2) redox cycling of SeNPs was directly driven by thiol groups in NAC to produce ROS. Moreover, NAC, without increasing the systematic toxicity of SeNPs, decreased SeNP-induced lethality in healthy mice. Overall, we demonstrated that SeNPs exert a potential cytotoxicity effect by inducing ROS production in cancer cells; NAC effectively heightens the property of SeNPs in vitro and in vivo.

In this note, we propose a local maximum likelihood estimator for spatially‐dependent distributions. Our estimator adopts the Poisson regression approach for density ratio models and incorporates spatial smoothing via local regression. We also present a method of smoothing parameter selection. We illustrate this easy‐to‐implement estimator with an application to the estimation of corn yield distributions of Iowa counties. The usefulness of the approach is further demonstrated via an application to the estimation of crop insurance premium.

We propose a copula specification test for copula-based multivariate survival models under censorship. This flexible test is applicable to both Archimedean and non-Archimedean copulas and provides ...

Tile-based approach is widely adopted in adaptive 360\textdegree~video streaming systems. Existing QoE-driven streaming approaches usually obtain the tile selection and adjust the bitrate based on the viewport prediction with a fixed tiling, which fail to consider the unstable prediction performance. However, varying the tiling of the video can produce different number of tiles with different sizes, and thus can have distinct impacts on error tolerance for viewport prediction and on decoding complexity for resource-constrained mobile client. In this work, we introduce adaptive tiling into the conventional bitrate adaptation for mobile 360degree~video streaming. We first analyze the impacts of tilings on tile selection and decoding time, which verify the benefit of tiling adaptation in various practical aspects. We then formulate the QoE optimization problem for adaptive tiling and bitrate streaming and discuss the design details of our adaptation algorithm, which can adapt to the performance of viewport prediction and the decoding capabilities of mobile clients in addition to the conventional influencing factors. Finally, the superiority of our proposed approach compared with the state-of-the-art methods is evaluated through extensive trace-driven simulations.

In this paper we investigate the joint conditional distribution of health (life expectancy) and income growth and its evolution overtime. The conditional distributions of these two variables are obtained by applying nonparametric methods to a bivariate nonparametric regression system of equations. Analyzing the distributions of the non-parametric fitted values from these models we find strong evidence of movement over time and strong evidence of first-order stochastic dominance of the earlier years over the later ones. We also find strong evidence of second-order stochastic dominance by non-OECD countries over OECD countries in each period. Our results complement the findings of Wu, Savvides and Stengos (2008) who explored the unconditional behaviour of these joint distributions over time.JELCode: 01; 015; 057Keywords: Income; Health; Global Distribution; Inequality; Poverty

Summary We have developed a customizable goodness-of-fit test of a parametric density based on its distance to a consistently estimated density. This consistent estimate is obtained via a nonparametric density estimator with a parametric start, wherein the start is set to be the hypothesized parametric density. To cope with the influence of nonparametric estimation bias, nonparametric goodness-of-fit tests have resorted to remedies such as undersmoothing or convolution of the hypothesized density. Our test requires no such devices and possesses enhanced powers against alternative densities because the guided density estimator is free of the typical nonparametric bias under the null hypothesis and attains bias reduction when the underlying density is in a broad nonparametric neighborhood of the hypothesized density. Here, we establish the statistical properties of our test and use Monte Carlo simulations to demonstrate its finite sample performance. We use this test to examine the goodness-of-fit of normal mixtures to the distributions of log income of U.S. states. Although normality is rejected decisively, our results suggest that normal mixtures with two or three components suffice for all but one state.

This article examines the effects of ocean-related decadal climate variability (DCV) phenomena on climate and the effects of both climate shifts and independent DCV events on crop yields. We address three DCV phenomena: the Pacific Decadal Oscillation (PDO), the Tropical Atlantic Sea-Surface Temperature Gradient (TAG), and the Western Pacific Warm Pool (WPWP). We estimate the joint effect of these DCV phenomena on the mean, variance, and skewness of crop yield distributions. We found regionally differentiated impacts of DCV phenomena on growing degree days, precipitation, and extreme weather events, which in turn alter distributions of U.S. regional crop yields.

This study concerns the estimation of spatially similar densities, each with a small number of observations. To achieve flexibility and improved efficiency, we propose kernel-based estimators that are refined by generalized empirical likelihood probability weights associated with spatial moment conditions. We construct spatial moments based on spline basis functions that facilitate desirable local customization. Monte Carlo simulations demonstrate the good performance of the proposed method. To illustruate its usefulness, we apply this method to the estimation of crop yield distributions that are known to be spatically similar.

Scope Tea, made from the plant Camellia sinensis, is known to have anti-diabetes effects and different mechanisms of action are proposed. Kidney is a vital organ in managing water reabsorption and glucose metabolism, and is greatly influenced by diabetes. The present study investigates the effects of tea administration on water reabsorption and gluconeogenesis in the kidney of diabetic mice. Methods and results Db/db mice are given tea infusion as drinking fluid when they begin to exhibit hyperglycemia. It is found that green tea or black tea infusion potently elevates renal proteins vital for water reabsorption, including protein kinase C-α, aquaporin 2, and urea transporter-A1, as well as increases trafficking of these proteins to apical plasma membrane where they exert water reabsorption function. The treatment also downregulates renal gluconeogenic enzymes, including glucose-6-phosphatase-α and phosphoenolpyruvate carboxykinase. Associated with these biochemical changes are the rectified polyuria, polydipsia, polyphagia, and hyperglycemia, all symptoms of diabetes. Conclusions For the first time, the present study demonstrates that tea has robust effects in enhancing kidney water reabsorption proteins and downregulating gluconeogenic enzymes in db/db mice. It remains to be investigated whether such beneficial effects of tea occur in humans.

Background: Coronavirus disease 2019 (COVID-19) is now recognized as a multi-system disease. The CDC recommends multiple preventive methods, including social distancing, hand hygiene, and wearing masks. In addition, some states imposed stay-at-home (SAH) and mandatory face mask (MFM) orders, to reduce the spread of COVID-19. The purpose of this study was to characterize the relationship between SAH and MFM approaches with the incidence rate and fatality-case-ratios (CFR). Methods: The research design is a cross-sectional study examining changes in incidence rate and CFR between states with and without SAH and MFM using available database from CDC during the pandemic periods of the date of the first positive case of each state to the date of 2020-08-23. Findings: The new daily cases curve of the nation was bent or flattened under the order of SAH and increased following the end of SAH and several nation-wide social gathering events. SAH+MFM states (n=34) and SAH+no-MFM states (n=9) have similar incidence rates, but significantly higher averages in daily new cases and daily fatality, and CFR than no-SAH+no-MFM states (n=7 states. P < 0.05), respectively. When normalized to population density, beside higher CFR in no-SAH+no-MFM, there are no significant differences in total positive cases, average daily new cases and average daily fatality among the 3 groups. When comparing masking during the period of SAH, there are significantly higher incidence rates and average daily new cases in MFM states than in no-MFM states (p

Mitophagy is a metabolic process to remove excessive or damaged mitochondria in eukaryotic cells. It is well-known that mitochondria are one of the major sources of reactive oxygen species (ROS). Mitochondrial ROS and damage-associated molecular patterns (DAMPs) can activate inflammasomes to induce inflammatory responses. Once the activation is regulated improperly, excessive inflammation will bring about various tissue injuries, resulting in a series of diseases. However, the selective mitochondrial autophagy can specifically eliminate dysfunctional mitochondria to maintain mitochondrial homeostasis and protect against the hyperinflammation induced by ROS and DAMPs. Recent studies demonstrated that a variety of internal and external factors regulate several inflammatory diseases via altering the level of mitophagy. In this review, we summarize the latest research progress of mitophagy and focus on the inflammatory responses regulated by mitophagy, aiming to illuminate the role of mitophagy in inflammation and provide clues to the diagnosis and therapy of inflammatory diseases.

Likelihood cross-validation for kernel density estimation is known to be sensitive to extreme observations and heavy-tailed distributions. We propose a robust likelihood-based cross-validation meth...

Substantial structure and restrictions, such as monotonicity and curvature constraints, necessary to give economic interpretation to empirical findings are often furnished by economic theories. Although such restrictions may be imposed in certain parametric empirical settings in a relatively straightforward fashion, incorporating such restrictions in semiparametric models is often problematic. A solution to this problem is provided via penalized splines, where monotonicity and curvature constraints are maintained through integral transformations of spline basis expansions. Large sample properties, implementation and inferential procedures are presented. Extension to multiple regressions under the framework of additive models is also discussed. A series of Monte Carlo simulations illustrate the finite sample properties of the estimator. The proposed method is employed to estimate a Lorenz curve of income and a production function with multiple inputs.

Summary We develop a specification test of predictive densities, based on the fact that the generalized residuals of correctly specified predictive density models are independent and identically distributed uniform. The proposed sequential test examines the hypotheses of serial independence and uniformity in two stages, wherein the first-stage test of serial independence is robust to violation of uniformity. The approach of the data-driven smooth test is employed to construct the test statistics. The asymptotic independence between the two stages facilitates proper control of the overall type I error of the sequential test. We derive the asymptotic null distribution of the test, which is free of nuisance parameters, and we establish its consistency. Monte Carlo simulations demonstrate excellent finite sample performance of the test. We apply this test to evaluate some commonly used models of stock returns.

Given multiple Y observations for each observed X , we propose a conditional kernel density estimator that exploits smoothing of f ( y | x ) across x . We obtain large sample properties of the proposed estimator and present a practical cross validation bandwidth selector. An application to adult BMI densities conditional on age is provided.

Selenium, at high-dose levels approaching its toxicity, protects tissues from dose-limiting toxicities of many cancer chemotherapeutics without compromising their therapeutic effects on tumors, there by allowing the delivery of higher chemotherapeutic doses to achieve increased cure rate. In this regard, selenium nanoparticles (SeNPs), which show the lowest toxicity among extensively investigated selenium compounds including methylselenocysteine and selenomethionine, are more promising for application. The key issue remains to be resolved is whether low-toxicity SeNPs possess a selective protective mechanism. p53 or p53-regulated thrombospondin-1 has each been confirmed to be an appropriate target for therapeutic suppression to reduce side effects of anticancer therapy. The present study demonstrated that SeNPs transiently suppressed the expression of many intestinal p53-associated genes in healthy mice. SeNPs did not interfere with tumor-suppressive effect of nedaplatin, a cisplatin analogue; however, effectively reduced nedaplatin-evoked diarrhea. Nedaplatin-induced diarrhea was associated with activation of intestinal p53 and high expression of intestinal thrombospondin-1. The preventive effect of SeNPs on nedaplatin-induced diarrhea was correlated with a powerful concomitant suppression of p53 and thrombospondin-1. Moreover, the high-dose SeNPs used in the present study did not suppress growth nor caused liver and kidney injuries as well as alterations of hematological parameters in healthy mice. Overall, the present study reveals that chemotherapeutic selectivity conferred by SeNPs involves a dual suppression of two well-documented targets, the p53 and thrombospondin-1, providing mechanistic and pharmacologic insights on low-toxicity SeNPs as a potential chemoprotectant for mitigating chemotherapy-induced diarrhea.

We have demonstrated previously that melatonin attenuates hepatotoxicity triggered by high doses of (&minus, )-epigallocatechin-3-gallate (EGCG) in mice. The current work investigated the influence of melatonin on the oncostatic activity of EGCG in two cancer cell lines, wherein melatonin induced an opposite response of p21. In human tongue cancer TCA8113 cells, melatonin-induced p21 and EGCG-mediated formation of quinoproteins were positively associated with the oncostatic effects of melatonin and EGCG. Melatonin-stimulated an increase in p21 which was correlated with a pronounced nuclear translocation of thioredoxin 1 and thioredoxin reductase 1, both of which are known to induce p21 via promoting p53 trans-activation. Melatonin did not influence the EGCG-mediated increase of quinoprotein formation nor did EGCG impair melatonin-induced p21 up-regulation. Co-treatment with both agents enhanced the cell-killing effect as well as the inhibitory activities against cell migration and colony formation. It is known that p21 also plays a powerful anti-apoptotic role in some cancer cells and confers these cells with a survival advantage, making it a target for therapeutic suppression. In human hepatocellular carcinoma HepG2 cells, melatonin suppressed p21 along with the induction of pro-survival proteins, PI3K and COX-2. However, EGCG prevented against melatonin-induced PI3K and COX-2, and melatonin probably sensitized HepG2 cells to EGCG cytotoxicity via down-regulating p21, Moreover, COX-2 and HO-1 were significantly reduced only by the co-treatment, and melatonin aided EGCG to achieve an increased inhibition on Bcl2 and NF&kappa, B. These events occurring in the co-treatment collectively resulted in an enhanced cytotoxicity. In addition, the co-treatment also enhanced the inhibitory activities against cell migration and colony formation. Overall, the results gathered from these two cancer cell lines with a divergent p21 response to melatonin show that the various oncostatic activities of melatonin and EGCG together are more robust than each agent alone, suggesting that they may be useful partners in fighting cancer.

Acute liver failure is divided into hyperacute, acute and subacute liver failure. Ascites is a common complication of subacute liver failure. Although animal models of acute liver failure have been established, the study of the pathogenesis of subacute liver failure with ascites complication is hampered by the lack of experimental animal model. The present study aimed at providing a mouse model of subacute liver failure with ascites complication. Kunming mice were intraperitoneally injected with (-)-epigallocatechin-3-gallate (EGCG), a redox-active polyphenol from green tea, for 32 consecutive days with step-wise increased dosage. The EGCG treatment resulted in liver failure as evidenced by extensive hepatocyte necrosis observed histologically along with significant elevation of serum alanine aminotransferase, aspartate aminotransferase, total bilirubin and direct bilirubin levels as well as significant reduction of serum albumin. Liver fibrosis was not observed by Masson staining and fibrosis-associated proteins were not increased. The mortality was less than 12% and the survival mice developed noticeable ascites. Hepatic thioredoxin and glutathione systems were activated by the EGCG. These adaptive responses might render most mice tolerable to the EGCG treatment. The EGCG treatment significantly up-regulated renal urea transporter A1 and promoted its trafficking to apical membrane. These alterations, known to increase water reabsorption, may be responsible, at least in part, for the formation of the ascites. Overall, the mice treated with gradually elevated doses of EGCG exhibits some of the features observed in patients with subacute liver failure, especially ascites. This mouse model is a useful tool for investigating the pathogenesis of subacute liver failure with ascites complication.

Peritoneal carcinomatosis has an extremely poor overall prognosis and remains one of the greatest oncologic challenges. Prior studies in mice show that sodium selenite administered intraperitoneally is highly effective in inhibiting cancer cells implanted in the peritoneal cavity. However, the pharmacological mechanism remains unclear. The present study revisited the therapeutic effect of selenite and elucidated its mechanism of action. We found that intraperitoneal delivery of selenite to cancer cells in the peritoneal cavity of mice rapidly and robustly killed the cancer cells, with a therapeutic efficacy higher than that of cisplatin. The action of selenite was associated with the following pharmacological mechanisms. 1) Favorable drug distribution: selenite increased selenium levels in the cancer cells by 250-fold, while in normal tissues only by 7-fold. 2) Optimal selenium form: selenite was converted in the cancer cells mainly into selenium nanoparticles (SeNPs), which are more efficient than selenite in producing reactive oxygen species (ROS). 3) Persistent hijacking of two pro-survival systems to generate ROS: selenite did not impair thioredoxin- and glutaredoxin-coupled glutathione systems, which facilitate SeNPs to generate ROS and caused severe organelle injury and apoptotic response in the cancer cells. Overall, these mechanisms tend to maximize the potential of selenite in producing ROS in cancer cells and underlie selenite as a candidate therapeutic agent for peritoneal carcinomatosis.

Antimicrobial photocatalysis involves the UVA excitation of titanium dioxide (TiO2) nanoparticles (particularly the anatase form) to produce reactive oxygen species (ROS) that kill microbial cells. For the first time we report that the addition of sodium bromide to photoactivated TiO2 (P25) potentiates the killing of Gram-positive, Gram-negative bacteria and fungi by up to three logs. The potentiation increased with increasing bromide concentration in the range of 0–10 mM. The mechanism of potentiation is probably due to generation of both short and long-lived oxidized bromine species including hypobromite as shown by the following observations. There is some antimicrobial activity remaining in solution after switching off the light, that lasts for 30 min but not 2 hours, and oxidizes 3,3′,5,5′-tetramethylbenzidine. N-acetyl tyrosine ethyl ester was brominated in a light dose-dependent manner, however no bromine or tribromide ion could be detected by spectrophotometry or LC-MS. The mechanism appears to have elements in common with the antimicrobial system (myeloperoxidase + hydrogen peroxide + bromide).

Our paper concerns the question of whether there exist hedge assets during extreme market conditions, which has become increasingly important since the recent financial crisis. This paper develops a novel extended skew-t copula model to examine the effectiveness of gold and US dollar (USD) as hedge or safe haven asset against stock prices for seven developed markets over the 2000–2013 period. Our results indicate the existence of skewness and heavy/thin tails in the distributions of all three types of assets in most of the developed markets, lending support to the employment of flexible distributions to evaluate the tail dependences among assets. We find that USD is preferred to gold as a hedge asset during normal market conditions, while both assets can serve as safe haven assets for most countries when stock markets crash. Our simultaneous analysis of the three assets advises against a joint hedge strategy of gold and USD due to the high tail dependence between them during extreme market conditions. Thi...

Using external stimuli to control ionic transport behavior in nanopores is an important focus of nanodevice research allowing numerous potential applications. A novel strategy was investigated to control ionic-transport resistance responses to the electric field intensity in a nanopore and regulate ionic selectivity. Molecular simulations were performed to examine the transport behaviors of K+ and Na+ in a carbon nanotube-based biomimetic nanopore under different electric fields. The responses of the modified group to the electric field intensity induced variations in ionic transport resistance, which then led to improved ionic selectivity. This result indicates that driving force and resistance are simultaneously affected by external stimuli under nanoconfinement.

Ultraviolet blood irradiation (UBI) was extensively used in the 1940s and 1950s to treat many diseases including septicemia, pneumonia, tuberculosis, arthritis, asthma, and even poliomyelitis. The early studies were carried out by several physicians in USA and published in the American Journal of Surgery. However, with the development of antibiotics, the use of UBI declined and it has now been called "the cure that time forgot." Later studies were mostly performed by Russian workers, and in other Eastern countries, and the modern view in Western countries is that UBI remains highly controversial. This review discusses the potential of UBI as an alternative approach to current methods used to treat infections, as an immune-modulating therapy and as a method for normalizing blood parameters. Low and mild doses of UV kill microorganisms by damaging the DNA, while any DNA damage in host cells can be rapidly repaired by DNA repair enzymes. However, the use of UBI to treat septicemia cannot be solely due to UV-mediated killing of bacteria in the bloodstream, as only 5-7% of blood volume needs to be treated with UV to produce the optimum benefit, and higher doses can be damaging. There may be some similarities to extracorporeal photopheresis (ECP) using psoralens and UVA irradiation. However, there are differences between UBI and ECP in that UBI tends to stimulate the immune system, while ECP tends to be immunosuppressive. With the recent emergence of bacteria that are resistant to all known antibiotics, UBI should be more investigated as an alternative approach to infections, and as an immune-modulating therapy.

In economics and government statistics, aggregated data instead of individual level data are usually reported for data confidentiality and for simplicity. In this paper we develop a method of flexibly estimating the probability density function of the population using aggregated data obtained as group averages when individual level data are grouped according to quantile limits. The kernel density estimator has been commonly applied to such data without taking into account the data aggregation process and has been shown to perform poorly. Our method models the quantile function as an integral of the exponential of a spline function and deduces the density function from the quantile function. We match the aggregated data to their theoretical counterpart using least squares, and regularize the estimation by using the squared second derivatives of the density function as the penalty function. A computational algorithm is developed to implement the method. Application to simulated data and US household...

Background Biofilms affect >80% bacterial infections in human and are usually difficult to eradicate because of their inherent drug resistance. Methods We investigated the effectiveness of antimicrobial blue light (aBL) (wavelength, 415 nm) for inactivating Acinetobacter baumannii or Pseudomonas aeruginosa biofilms in 96-well microplates or infected mouse burn wounds. Results In vitro, in 96-well microplates, exposure of 24-hour-old and 72-hour-old A. baumannii biofilms to 432 J/cm(2) aBL resulted in inactivation of 3.59 log10 and 3.18 log10 colony-forming units (CFU), respectively. For P. aeruginosa biofilms, similar levels of inactivation-3.02 log10 and 3.12 log10 CFU, respectively-were achieved. In mouse burn wounds infected with 5 × 10(6) CFU ofA. baumannii, approximately 360 J/cm(2) and 540 J/cm(2) aBL was required to inactivate 3 log10 CFU in biofilms when delivered 24 and 48 hours, respectively, after bacterial inoculation. High-performance liquid chromatography analysis revealed the presence of endogenous porphyrins in both A. baumannii and P. aeruginosa TUNEL assay detected no apoptotic cells in aBL-irradiated mouse skin at up to 24 hours after aBL exposure (540 J/cm(2)). Conclusions aBL has antimicrobial activity in biofilms ofA. baumannii and P. aeruginosa and is a potential therapeutic approach for biofilm-related infections.

In this paper we propose a data driven smooth test of symmetry. We first transform the raw data via the probability integral transformation according to a symmetrized empirical distribution, and show that under the null hypothesis of symmetry, the transformed data has a limiting uniform distribution, reducing testing for symmetry to testing for uniformity. Employing Neyman’s smooth test of uniformity, we show that only odd-ordered orthogonal moments of the transformed data are required in constructing the test statistic. We present a standardized smooth test that is distribution-free asymptotically and derive the asymptotic behavior of the test and establish its consistency. Extension to dependent data case is discussed. We investigate the finite sample performance of the proposed tests on both homogeneous and mixed distributions (with unobserved heterogeneity). An empirical application on testing symmetry of wage adjustment process, based on heterogeneous wage contracts with different durations, is provided.

The likelihood cross validation (LCV) and the least square cross validation (LSCV) are two commonly used methods of bandwidth selection in kernel density estimation. The LCV is generally more efficient but sensitive to tail-heaviness; in contrast, the LSCV fares well for heavy-tailed distributions but tends to undersmooth and is generally more variable. In this study, we propose two novel kernel functions that are robust against heavy-tailed distributions and at the same time adaptive with respect to the sample tail-heaviness in a data-driven manner. The proposed method is simple to implement. Our simulations show that it performs similarly to the LCV for regular- and thin-tailed distributions and outperforms the LSCV for heavy-tailed distributions, suggesting that it can be an overall competitive alternative. An empirical application to income distribution estimation is provided.

With the deterioration of air quality and increasing awareness of the adverse health impacts of air pollution, more people choose to stay indoors and take up various pollution mitigation measures under heavy air pollution. This study contends that these activities entail extraneous electricity consumption, which in turn further exacerbates air quality. We investigate this self-aggravation of air pollution based on the electricity usage of a panel of Chinese households. Our analyses suggest that Chinese households' electricity consumption tends to increase with the severity of heavy air pollution. Our results are shown to be robust across various model specifications, sample configurations and alternative air quality indicators. We also show that the self-aggravation effects are more pronounced for households (i) located in the northern China; (ii) with high consumption capacity and/or located in urban areas; (iii) with vulnerable members such as elderly or preschoolers.