VUV frequency combs from below-threshold harmonics

Recent demonstrations of high-harmonic generation (HHG) at very high repetition frequencies (~100 MHz) may allow for the revolutionary transfer of frequency combs to the vacuum ultraviolet (VUV). This advance necessitates unifying optical frequency comb technology with strong-field atomic physics. While strong-field studies of HHG have often focused on above-threshold harmonic generation (photon energy above the ionization potential), for VUV frequency combs an understanding of below-threshold harmonic orders and their generation process is crucial. Here we present a new and quantitative study of the harmonics 7-13 generated below and near the ionization threshold in xenon gas. We show multiple generation pathways for these harmonics that are manifested as on-axis interference in the harmonic yield. This discovery provides a new understanding of the strong-field, below-threshold dynamics under the influence of an atomic potential and allows us to quantitatively assess the achievable coherence of a VUV frequency comb generated through below threshold harmonics. We find that under reasonable experimental conditions temporal coherence is maintained. As evidence we present the first explicit VUV frequency comb structure beyond the 3rd harmonic.Comment: 16 pages, 4 figures, 1 tabl

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

Acne and smoking: is there a relationship?

BACKGROUND: There are contradictory reports on the relationship between acne vulgaris and cigarette smoking. The objective of this study was to examine the relation between acne and cigarette smoking in a case-control study. METHODS: A questionnaire on smoking habits was offered to 350 patients with acne vulgaris and 350 patients suffering from skin diseases other than acne, aged 15 – 40 years, attending in a skin clinic in Tehran, Iran. The patients completed the questionnaires anonymously in the waiting room. RESULTS: Two hundred and ninety-three patients with acne (response rate 83.7 %) and 301 patients with other skin diseases (response rate 86.0 %) completed the questionnaires. Twelve acne patients (4.1 %) and 27 control patients (9.0 %) were current smokers (odds ratio = 0.43, 95% confidence limits 0.22 – 0.87, p < 0.05). But after adjustment for sex, this difference was not significant (odds ratio: 0.61, 95% CI: 0.30–1.26, p > 0.05, Mantel-Haenszel test). CONCLUSION: An association between acne and cigarette smoking was not found in this study

Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study

<p>Abstract</p> <p>Background</p> <p>The appropriate handling of missing covariate data in prognostic modelling studies is yet to be conclusively determined. A resampling study was performed to investigate the effects of different missing data methods on the performance of a prognostic model.</p> <p>Methods</p> <p>Observed data for 1000 cases were sampled with replacement from a large complete dataset of 7507 patients to obtain 500 replications. Five levels of missingness (ranging from 5% to 75%) were imposed on three covariates using a missing at random (MAR) mechanism. Five missing data methods were applied; a) complete case analysis (CC) b) single imputation using regression switching with predictive mean matching (SI), c) multiple imputation using regression switching imputation, d) multiple imputation using regression switching with predictive mean matching (MICE-PMM) and e) multiple imputation using flexible additive imputation models. A Cox proportional hazards model was fitted to each dataset and estimates for the regression coefficients and model performance measures obtained.</p> <p>Results</p> <p>CC produced biased regression coefficient estimates and inflated standard errors (SEs) with 25% or more missingness. The underestimated SE after SI resulted in poor coverage with 25% or more missingness. Of the MI approaches investigated, MI using MICE-PMM produced the least biased estimates and better model performance measures. However, this MI approach still produced biased regression coefficient estimates with 75% missingness.</p> <p>Conclusions</p> <p>Very few differences were seen between the results from all missing data approaches with 5% missingness. However, performing MI using MICE-PMM may be the preferred missing data approach for handling between 10% and 50% MAR missingness.</p

Rah, rah, ROS: metabolic changes caused by loss of adhesion induce cell death

The high rate of glucose utilization by cancer cells has been well characterized. Recent data suggest that when normal mammary epithelial cells are cultured under nonadherent conditions, glucose consumption decreases, ATP levels fall, and concentrations of reactive oxygen species rise. The rise in reactive oxygen species causes death of nonadherent cells, which can be suppressed with antioxidants. Nonadherent ErbB2-transformed mammary epithelial cells maintain glucose transport and antioxidant production; however, antioxidants appear to enhance anchorage-independent growth. These findings integrate aspects of glucose metabolism, anoikis suppression and antioxidant production in tumor cell biology and suggest that antioxidant therapy could stimulate tumor survival

Soil Moisture and Fungi Affect Seed Survival in California Grassland Annual Plants

Survival of seeds in the seed bank is important for the population dynamics of many plant species, yet the environmental factors that control seed survival at a landscape level remain poorly understood. These factors may include soil moisture, vegetation cover, soil type, and soil pathogens. Because many soil fungi respond to moisture and host species, fungi may mediate environmental drivers of seed survival. Here, I measure patterns of seed survival in California annual grassland plants across 15 species in three experiments. First, I surveyed seed survival for eight species at 18 grasslands and coastal sage scrub sites ranging across coastal and inland Santa Barbara County, California. Species differed in seed survival, and soil moisture and geographic location had the strongest influence on survival. Grasslands had higher survival than coastal sage scrub sites for some species. Second, I used a fungicide addition and exotic grass thatch removal experiment in the field to tease apart the relative impact of fungi, thatch, and their interaction in an invaded grassland. Seed survival was lower in the winter (wet season) than in the summer (dry season), but fungicide improved winter survival. Seed survival varied between species but did not depend on thatch. Third, I manipulated water and fungicide in the laboratory to directly examine the relationship between water, fungi, and survival. Seed survival declined from dry to single watered to continuously watered treatments. Fungicide slightly improved seed survival when seeds were watered once but not continually. Together, these experiments demonstrate an important role of soil moisture, potentially mediated by fungal pathogens, in driving seed survival

Diabetes status and post-load plasma glucose concentration in relation to site-specific cancer mortality: findings from the original Whitehall study

ObjectiveWhile several studies have reported on the relation of diabetes status with pancreatic cancer risk, the predictive value of this disorder for other malignancies is unclear. Methods: The Whitehall study, a 25year follow-up for mortality experience of 18,006 men with data on post-challenge blood glucose and self-reported diabetes, allowed us to address these issues. Results: There were 2158 cancer deaths at follow-up. Of the 15 cancer outcomes, diabetes status was positively associated with mortality from carcinoma of the pancreas and liver, while the relationship with lung cancer was inverse, after controlling for a range of potential covariates and mediators which included obesity and socioeconomic position. After excluding deaths occurring in the first 10years of follow-up to examine the effect of reverse causality, the magnitude of the relationships for carcinoma of the pancreas and lung was little altered, while for liver cancer it was markedly attenuated. Conclusions: In the present study, diabetes status was related to pancreatic, liver, and lung cancer risk. Cohorts with serially collected data on blood glucose and covariates are required to further examine this area

A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs

A large fraction of the electronic health records (EHRs) consists of clinical measurements collected over time, such as lab tests and vital signs, which provide important information about a patient's health status. These sequences of clinical measurements are naturally represented as time series, characterized by multiple variables and large amounts of missing data, which complicate the analysis. In this work, we propose a novel kernel which is capable of exploiting both the information from the observed values as well the information hidden in the missing patterns in multivariate time series (MTS) originating e.g. from EHRs. The kernel, called TCK$_{IM}$, is designed using an ensemble learning strategy in which the base models are novel mixed mode Bayesian mixture models which can effectively exploit informative missingness without having to resort to imputation methods. Moreover, the ensemble approach ensures robustness to hyperparameters and therefore TCK$_{IM}$ is particularly well suited if there is a lack of labels - a known challenge in medical applications. Experiments on three real-world clinical datasets demonstrate the effectiveness of the proposed kernel.Comment: 2020 International Workshop on Health Intelligence, AAAI-20. arXiv admin note: text overlap with arXiv:1907.0525

Lovelock theories, holography and the fate of the viscosity bound

We consider Lovelock theories of gravity in the context of AdS/CFT. We show that, for these theories, causality violation on a black hole background can occur well in the interior of the geometry, thus posing more stringent constraints than were previously found in the literature. Also, we find that instabilities of the geometry can appear for certain parameter values at any point in the geometry, as well in the bulk as close to the horizon. These new sources of causality violation and instability should be related to CFT features that do not depend on the UV behavior. They solve a puzzle found previously concerning unphysical negative values for the shear viscosity that are not ruled out solely by causality restrictions. We find that, contrary to previous expectations, causality violation is not always related to positivity of energy. Furthermore, we compute the bound for the shear viscosity to entropy density ratio of supersymmetric conformal field theories from d=4 till d=10 - i.e., up to quartic Lovelock theory -, and find that it behaves smoothly as a function of d. We propose an approximate formula that nicely fits these values and has a nice asymptotic behavior when d goes to infinity for any Lovelock gravity. We discuss in some detail the latter limit. We finally argue that it is possible to obtain increasingly lower values for the shear viscosity to entropy density ratio by the inclusion of more Lovelock terms.Comment: 42 pages, 17 figures, JHEP3.cls. v2: reference adde

The fate of steroid estrogens: Partitioning during wastewater treatment and onto river sediments

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 Springer Science+Business Media B.V.The partitioning of steroid estrogens in wastewater treatment and receiving waters is likely to influence their discharge to, and persistence in, the environment. This study investigated the partitioning behaviour of steroid estrogens in both laboratory and field studies. Partitioning onto activated sludge from laboratory-scale Husmann units was rapid with equilibrium achieved after 1 h. Sorption isotherms and Kd values decreased in the order 17α-ethinyl estradiol > 17α-estradiol > estrone > estriol without a sorption limit being achieved (1/n >1). Samples from a wastewater treatment works indicated no accumulation of steroid estrogens in solids from primary or secondary biological treatment, however, a range of steroid estrogens were identified in sediment samples from the River Thames. This would indicate that partitioning in the environment may play a role in the long-term fate of estrogens, with an indication that they will be recalcitrant in anaerobic conditions.EPSR