Cosmology-independent Estimate of the Fraction of Baryon Mass in the IGM from Fast Radio Burst Observations

The excessive dispersion measure (DM) of fast radio bursts (FRBs) has been proposed to be a powerful tool to study intergalactic medium (IGM) and to perform cosmography. One issue is that the fraction of baryons in the IGM, f IGM, is not properly constrained. Here, we propose a method of estimating f IGM using a putative sample of FRBs with the measurements of both DM and luminosity distance d L. The latter can be obtained if the FRB is associated with a distance indicator (e.g., a gamma-ray burst or a gravitational-wave event), or the redshift z of the FRB is measured and d L at the corresponding z is available from other distance indicators (e.g., SNe Ia) at the same redshift. As d L/DM essentially does not depend on cosmological parameters, our method can determine f IGM independent of cosmological parameters. We parameterize f IGM as a function of redshift and model the DM contribution from a host galaxy as a function of star formation rate. Assuming f IGM has a mild evolution with redshift with a functional form and by means of Monte Carlo simulations, we show that an unbiased and cosmology-independent estimate of the present value of f IGM with a ~12% uncertainty can be obtained with 50 joint measurements of d L and DM. In addition, such a method can also lead to a measurement of the mean value of DM contributed from the local host galaxy

Detecting Political Biases of Named Entities and Hashtags on Twitter

Ideological divisions in the United States have become increasingly prominent in daily communication. Accordingly, there has been much research on political polarization, including many recent efforts that take a computational perspective. By detecting political biases in a corpus of text, one can attempt to describe and discern the polarity of that text. Intuitively, the named entities (i.e., the nouns and phrases that act as nouns) and hashtags in text often carry information about political views. For example, people who use the term "pro-choice" are likely to be liberal, whereas people who use the term "pro-life" are likely to be conservative. In this paper, we seek to reveal political polarities in social-media text data and to quantify these polarities by explicitly assigning a polarity score to entities and hashtags. Although this idea is straightforward, it is difficult to perform such inference in a trustworthy quantitative way. Key challenges include the small number of known labels, the continuous spectrum of political views, and the preservation of both a polarity score and a polarity-neutral semantic meaning in an embedding vector of words. To attempt to overcome these challenges, we propose the Polarity-aware Embedding Multi-task learning (PEM) model. This model consists of (1) a self-supervised context-preservation task, (2) an attention-based tweet-level polarity-inference task, and (3) an adversarial learning task that promotes independence between an embedding's polarity dimension and its semantic dimensions. Our experimental results demonstrate that our PEM model can successfully learn polarity-aware embeddings. We examine a variety of applications and we thereby demonstrate the effectiveness of our PEM model. We also discuss important limitations of our work and stress caution when applying the PEM model to real-world scenarios.Comment: Submitted to EPJ -- Data Science, under revie

In-situ monitoring of displacements and stability evaluation of slope based on fiber Bragg grating sensing technology

2009-2010 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

The Impacts of Swimming Exercise on Hippocampal Expression of Neurotrophic Factors in Rats Exposed to Chronic Unpredictable Mild Stress

Depression is associated with stress-induced neural atrophy in limbic brain regions, whereas exercise has antidepressant effects as well as increasing hippocampal synaptic plasticity by strengthening neurogenesis, metabolism, and vascular function. A key mechanism mediating these broad benefits of exercise on the brain is induction of neurotrophic factors, which instruct downstream structural and functional changes. To systematically evaluate the potential neurotrophic factors that were involved in the antidepressive effects of exercise, in this study, we assessed the effects of swimming exercise on hippocampal mRNA expression of several classes of the growth factors (BDNF, GDNF, NGF, NT-3, FGF2, VEGF, and IGF-1) and peptides (VGF and NPY) in rats exposed to chronic unpredictable mild stress (CUMS). Our study demonstrated that the swimming training paradigm significantly induced the expression of BDNF and BDNF-regulated peptides (VGF and NPY) and restored their stress-induced downregulation. Additionally, the exercise protocol also increased the antiapoptotic Bcl-xl expression and normalized the CUMS mediated induction of proapoptotic Bax mRNA level. Overall, our data suggest that swimming exercise has antidepressant effects, increasing the resistance to the neural damage caused by CUMS, and both BDNF and its downstream neurotrophic peptides may exert a major function in the exercise related adaptive processes to CUMS

The in vivo study on the radiobiologic effect of prolonged delivery time to tumor control in C57BL mice implanted with Lewis lung cancer

<p>Abstract</p> <p>Background</p> <p>High-precision radiation therapy techniques such as IMRT or sterotactic radiosurgery, delivers more complex treatment fields than conventional techniques. The increased complexity causes longer dose delivery times for each fraction. The purpose of this work is to explore the radiobiologic effect of prolonged fraction delivery time on tumor response and survival in vivo.</p> <p>Methods</p> <p>1-cm-diameter Lewis lung cancer tumors growing in the legs of C57BL mice were used. To evaluate effect of dose delivery prolongation, 18 Gy was divided into different subfractions. 48 mice were randomized into 6 groups: the normal control group, the single fraction with 18 Gy group, the two subfractions with 30 min interval group, the seven subfractions with 5 min interval group, the two subfractions with 60 min interval group and the seven subfractions with 10 min interval group. The tumor growth tendency, the tumor growth delay and the mice survival time were analyzed.</p> <p>Results</p> <p>The tumor growth delay of groups with prolonged delivery time was shorter than the group with single fraction of 18 Gy (P < 0.05). The tumor grow delay of groups with prolonged delivery time 30 min was longer than that of groups with prolonged delivery time 60 min P < 0.05). There was no significant difference between groups with same delivery time (P > 0.05). Compared to the group with single fraction of 18 Gy, the groups with prolonged delivery time shorten the mice survival time while there was no significant difference between the groups with prolonged delivery time 30 min and the groups with prolonged delivery time 60 min.</p> <p>Conclusions</p> <p>The prolonged delivery time with same radiation dose shorten the tumor growth delay and survival time in the mice implanted with Lewis lung cancer. The anti-tumor effect decreased with elongation of the total interfractional time.</p

Monitoring and analysis of internal displacements of a slope and relationship with rainfall infiltration

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