Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users

If people with high risk of suicide can be identified through social media like microblog, it is possible to implement an active intervention system to save their lives. Based on this motivation, the current study administered the Suicide Probability Scale(SPS) to 1041 weibo users at Sina Weibo, which is a leading microblog service provider in China. Two NLP (Natural Language Processing) methods, the Chinese edition of Linguistic Inquiry and Word Count (LIWC) lexicon and Latent Dirichlet Allocation (LDA), are used to extract linguistic features from the Sina Weibo data. We trained predicting models by machine learning algorithm based on these two types of features, to estimate suicide probability based on linguistic features. The experiment results indicate that LDA can find topics that relate to suicide probability, and improve the performance of prediction. Our study adds value in prediction of suicidal probability of social network users with their behaviors

Sulfidation enhances stability and mobility of carboxymethyl cellulose stabilized nanoscale zero-valent iron in saturated porous media

Sulfidation can enhance the reactivity and longevity of nanoscale zero-valent iron (nZVI), but little is known about its effect on the fate and transport of nZVI in saturated porous media. This work compared the stability and mobility of carboxymethyl cellulose (CMC) stabilized nZVI (CMC-nZVI) and sulfidated nZVI (CMC-S-nZVI) particles in saturated porous media. After sulfidation, the hydrodynamic size of CMC-S-nZVI was 100–150 nm larger than CMC-nZVI due to enhanced adsorption of CMC onto the S-nZVI surface, which was facilitated by the bidentate bridging interaction between CMC and the FeSx phase on S-nZVI. Of note is that they had a similar core size and zeta potential. In comparison to CMC-nZVI, CMC-S-nZVI exhibited less physical settling (0–5% vs. 5–73%) and chemical dissolution (2–10% vs. 3–27%) within 55 min under the same ionic conditions (Na+, K+ < 200 mM; Al3+ < 0.75 mM). Column breakthrough experiments showed that both CMC-S-nZVI and CMC-nZVI had relatively high mobility in saturated porous media. However, CMC-S-nZVI exhibited greater breakthrough (C/C0 = 0.57–1.0) and corresponding greater mass recovery rates than the corresponding CMC-nZVI (C/C0 = 0.44–1.0) under most of the experimental conditions (e.g., different ion type and concentration, flow rate, and input concentration). The fitted colloid filtration theory model was in good agreement with experiments. This work suggests that in addition to the significant reactivity and longevity improvements demonstrated in other studies, CMC-S-nZVI is also more mobile than CMC-nZVI suggesting that CMC-S-nZVI has many of the characteristics favorable for field application

Atmospheric emissions from the deepwater Horizon spill constrain air-water partitioning, hydrocarbon fate, and leak rate

The fate of deepwater releases of gas and oil mixtures is initially determined by solubility and volatility of individual hydrocarbon species; these attributes determine partitioning between air and water. Quantifying this partitioning is necessary to constrain simulations of gas and oil transport, to predict marine bioavailability of different fractions of the gas-oil mixture, and to develop a comprehensive picture of the fate of leaked hydrocarbons in the marine environment. Analysis of airborne atmospheric data shows massive amounts (∼258,000 kg/day) of hydrocarbons evaporating promptly from the Deepwater Horizon spill; these data collected during two research flights constrain air-water partitioning, thus bioavailability and fate, of the leaked fluid. This analysis quantifies the fraction of surfacing hydrocarbons that dissolves in the water column (∼33% by mass), the fraction that does not dissolve, and the fraction that evaporates promptly after surfacing (∼14% by mass). We do not quantify the leaked fraction lacking a surface expression; therefore, calculation of atmospheric mass fluxes provides a lower limit to the total hydrocarbon leak rate of 32,600 to 47,700 barrels of fluid per day, depending on reservoir fluid composition information. This study demonstrates a new approach for rapid-response airborne assessment of future oil spills. Copyright 2011 by the American Geophysical Union

Vector mode inter-modal wavelength conversion in a dispersion tailored highly nonlinear few-mode fibre

We present the design and fabrication of a dispersion tailored highly nonlinear few-mode fibre with an inter-modal nonlinear coefficient of 2.81 (W \ub7 km)-1, the highest reported to date. Inter-modal wavelength conversion between the HE21 and TE01 vector modes is demonstrated in the fibre

Second primary cancer risk - the impact of applying different definitions of multiple primaries: results from a retrospective population-based cancer registry study

Background: There is evidence that cancer survivors are at increased risk of second primary cancers. Changes in the prevalence of risk factors and diagnostic techniques may have affected more recent risks.&lt;p&gt;&lt;/p&gt; Methods: We examined the incidence of second primary cancer among adults in the West of Scotland, UK, diagnosed with cancer between 2000 and 2004 (n = 57,393). We used National Cancer Institute Surveillance Epidemiology and End Results and International Agency for Research on Cancer definitions of multiple primary cancers and estimated indirectly standardised incidence ratios (SIR) with 95% confidence intervals (CI).&lt;p&gt;&lt;/p&gt; Results: There was a high incidence of cancer during the first 60 days following diagnosis (SIR = 2.36, 95% CI = 2.12 to 2.63). When this period was excluded the risk was not raised, but it was high for some patient groups; in particular women aged &#60;50 years with breast cancer (SIR = 2.13, 95% CI = 1.58 to 2.78), patients with bladder (SIR = 1.41, 95% CI = 1.19 to 1.67) and head &#38; neck (SIR = 1.93, 95% CI = 1.67 to 2.21) cancer. Head &#38; neck cancer patients had increased risks of lung cancer (SIR = 3.75, 95% CI = 3.01 to 4.62), oesophageal (SIR = 4.62, 95% CI = 2.73 to 7.29) and other head &#38; neck tumours (SIR = 6.10, 95% CI = 4.17 to 8.61). Patients with bladder cancer had raised risks of lung (SIR = 2.18, 95% CI = 1.62 to 2.88) and prostate (SIR = 2.41, 95% CI = 1.72 to 3.30) cancer.&lt;p&gt;&lt;/p&gt; Conclusions: Relative risks of second primary cancers may be smaller than previously reported. Premenopausal women with breast cancer and patients with malignant melanomas, bladder and head &#38; neck cancers may benefit from increased surveillance and advice to avoid known risk factors

Identification of sex hormone-binding globulin in the human hypothalamus

Gonadal steroids are known to influence hypothalamic functions through both genomic and non-genomic pathways. Sex hormone-binding globulin ( SHBG) may act by a non-genomic mechanism independent of classical steroid receptors. Here we describe the immunocytochemical mapping of SHBG-containing neurons and nerve fibers in the human hypothalamus and infundibulum. Mass spectrometry and Western blot analysis were also used to characterize the biochemical characteristics of SHBG in the hypothalamus and cerebrospinal fluid (CSF) of humans. SHBG-immunoreactive neurons were observed in the supraoptic nucleus, the suprachiasmatic nucleus, the bed nucleus of the stria terminalis, paraventricular nucleus, arcuate nucleus, the perifornical region and the medial preoptic area in human brains. There were SHBG-immunoreactive axons in the median eminence and the infundibulum. A partial colocalization with oxytocin could be observed in the posterior pituitary lobe in consecutive semithin sections. We also found strong immunoreactivity for SHBG in epithelial cells of the choroid plexus and in a portion of the ependymal cells lining the third ventricle. Mass spectrometry showed that affinity-purified SHBG from the hypothalamus and choroid plexus is structurally similar to the SHBG identified in the CSF. The multiple localizations of SHBG suggest neurohypophyseal and neuroendocrine functions. The biochemical data suggest that CSF SHBG is of brain rather than blood origin. Copyright (c) 2005 S. Karger AG, Base

Preparation and Measurement of Three-Qubit Entanglement in a Superconducting Circuit

Traditionally, quantum entanglement has played a central role in foundational discussions of quantum mechanics. The measurement of correlations between entangled particles can exhibit results at odds with classical behavior. These discrepancies increase exponentially with the number of entangled particles. When entanglement is extended from just two quantum bits (qubits) to three, the incompatibilities between classical and quantum correlation properties can change from a violation of inequalities involving statistical averages to sign differences in deterministic observations. With the ample confirmation of quantum mechanical predictions by experiments, entanglement has evolved from a philosophical conundrum to a key resource for quantum-based technologies, like quantum cryptography and computation. In particular, maximal entanglement of more than two qubits is crucial to the implementation of quantum error correction protocols. While entanglement of up to 3, 5, and 8 qubits has been demonstrated among spins, photons, and ions, respectively, entanglement in engineered solid-state systems has been limited to two qubits. Here, we demonstrate three-qubit entanglement in a superconducting circuit, creating Greenberger-Horne-Zeilinger (GHZ) states with fidelity of 88%, measured with quantum state tomography. Several entanglement witnesses show violation of bi-separable bounds by 830\pm80%. Our entangling sequence realizes the first step of basic quantum error correction, namely the encoding of a logical qubit into a manifold of GHZ-like states using a repetition code. The integration of encoding, decoding and error-correcting steps in a feedback loop will be the next milestone for quantum computing with integrated circuits.Comment: 7 pages, 4 figures, and Supplementary Information (4 figures)

A Statistical Model for Assessing Genetic Susceptibility as a Risk Factor in Multifactorial Diseases: Lessons from Occupational Asthma

BACKGROUND: Incorporating the influence of genetic variation in the risk assessment process is often considered, but no generalized approach exists. Many common human diseases such as asthma, cancer, and cardiovascular disease are complex in nature, as they are influenced variably by environmental, physiologic, and genetic factors. The genetic components most responsible for differences in individual disease risk are thought to be DNA variants (polymorphisms) that influence the expression or function of mediators involved in the pathological processes. OBJECTIVE: The purpose of this study was to estimate the combinatorial contribution of multiple genetic variants to disease risk. METHODS: We used a logistic regression model to help estimate the joint contribution that multiple genetic variants would have on disease risk. This model was developed using data collected from molecular epidemiology studies of allergic asthma that examined variants in 16 susceptibility genes. RESULTS: Based on the product of single gene variant odds ratios, the risk of developing asthma was assigned to genotype profiles, and the frequency of each profile was estimated for the general population. Our model predicts that multiple disease variants broaden the risk distribution, facilitating the identification of susceptible populations. This model also allows for incorporation of exposure information as an independent variable, which will be important for risk variants associated with specific exposures. CONCLUSION: The present model provided an opportunity to estimate the relative change in risk associated with multiple genetic variants. This will facilitate identification of susceptible populations and help provide a framework to model the genetic contribution in probabilistic risk assessment