Recruitment Market Trend Analysis with Sequential Latent Variable Models

Recruitment market analysis provides valuable understanding of industry-specific economic growth and plays an important role for both employers and job seekers. With the rapid development of online recruitment services, massive recruitment data have been accumulated and enable a new paradigm for recruitment market analysis. However, traditional methods for recruitment market analysis largely rely on the knowledge of domain experts and classic statistical models, which are usually too general to model large-scale dynamic recruitment data, and have difficulties to capture the fine-grained market trends. To this end, in this paper, we propose a new research paradigm for recruitment market analysis by leveraging unsupervised learning techniques for automatically discovering recruitment market trends based on large-scale recruitment data. Specifically, we develop a novel sequential latent variable model, named MTLVM, which is designed for capturing the sequential dependencies of corporate recruitment states and is able to automatically learn the latent recruitment topics within a Bayesian generative framework. In particular, to capture the variability of recruitment topics over time, we design hierarchical dirichlet processes for MTLVM. These processes allow to dynamically generate the evolving recruitment topics. Finally, we implement a prototype system to empirically evaluate our approach based on real-world recruitment data in China. Indeed, by visualizing the results from MTLVM, we can successfully reveal many interesting findings, such as the popularity of LBS related jobs reached the peak in the 2nd half of 2014, and decreased in 2015.Comment: 11 pages, 30 figure, SIGKDD 201

A Non-Parametric Bayesian Approach to Spike Sorting

Abstract — In this work we present and apply infinite Gaussian mixture modeling, a non-parametric Bayesian method, to the problem of spike sorting. As this approach is Bayesian, it allows us to integrate prior knowledge about the problem in a principled way. Because it is non-parametric we are able to avoid model selection, a difficult problem that most current spike sorting methods do not address. We compare this approach to using penalized log likelihood to select the best from multiple finite mixture models trained by expectation maximization. We show favorable offline sorting results on real data and discuss ways to extend our model to online applications

Quantum Spectrometry for Arbitrary Noise

We present a technique for recovering the spectrum of a non-Markovian bosonic bath and/or non-Markovian noises coupled to a harmonic oscillator. The treatment is valid under the conditions that the environment is large and hot compared to the oscillator, and that its temporal autocorrelation functions are symmetric with respect to time translation and reflection—criteria which we consider fairly minimal. We model a demonstration of the technique as deployed in the experimental scenario of a nanosphere levitated in a Paul trap, and show that it would effectively probe the spectrum of an electric field noise source from 1 0 2 to 1 0 6     Hz with a resolution inversely proportional to the measurement time. This technique may be deployed in quantum sensing, metrology, computing, and in experimental probes of foundational questions

Towards a Robuster Interpretive Parsing

The input data to grammar learning algorithms often consist of overt forms that do not contain full structural descriptions. This lack of information may contribute to the failure of learning. Past work on Optimality Theory introduced Robust Interpretive Parsing (RIP) as a partial solution to this problem. We generalize RIP and suggest replacing the winner candidate with a weighted mean violation of the potential winner candidates. A Boltzmann distribution is introduced on the winner set, and the distribution’s parameter $T$ is gradually decreased. Finally, we show that GRIP, the Generalized Robust Interpretive Parsing Algorithm significantly improves the learning success rate in a model with standard constraints for metrical stress assignment

Major epidemiological changes in sudden infant death syndrome : a 20-year population-based study in the UK

Background Results of case-control studies in the past 5 years suggest that the epidemiology of sudden infant death syndrome (SIDS) has changed since the 1991 UK Back to Sleep campaign. The campaign's advice that parents put babies on their back to sleep led to a fall in death rates. We used a longitudinal dataset to assess these potential changes. Methods Population-based data from home visits have been collected for 369 consecutive unexpected infant deaths (300 SIDS and 69 explained deaths) in Avon over 20 years (1984—2003). Data obtained between 1993 and 1996 from 1300 controls with a chosen “reference” sleep before interview have been used for comparison. Findings Over the past 20 years, the proportion of children who died from SIDS while co-sleeping with their parents, has risen from 12% to 50% (p<0·0001), but the actual number of SIDS deaths in the parental bed has halved (p=0·01). The proportion seems to have increased partly because the Back to Sleep campaign led to fewer deaths in infants sleeping alone—rather than because of a rise in deaths of infants who bed-shared, and partly because of an increase in the number of deaths in infants sleeping with their parents on a sofa. The proportion of deaths in families from deprived socioeconomic backgrounds has risen from 47% to 74% (p=0·003), the prevalence of maternal smoking during pregnancy from 57% to 86% (p=0·0004), and the proportion of pre-term infants from 12% to 34% (p=0·0001). Although many SIDS infants come from large families, first-born infants are now the largest group. The age of infants who bed-share is significantly smaller than that before the campaign, and fewer are breastfed. Interpretation Factors that contribute to SIDS have changed in their importance over the past 20 years. Although the reasons for the rise in deaths when a parent sleeps with their infant on a sofa are still unclear, we strongly recommend that parents avoid this sleeping environment. Most SIDS deaths now occur in deprived families. To better understand contributory factors and plan preventive measures we need control data from similarly deprived families, and particularly, infant sleep environments

Perspectives on Implementing a Multidomain Approach to Caring for Older Adults With Heart Failure

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153220/1/jgs16183_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153220/2/jgs16183-sup-0001-supinfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153220/3/jgs16183.pd

Childhood tetanus in Australia: ethical issues for a should-be-forgotten preventable disease

Refusal of a parent to have a child vaccinated against tetanus raised ethical issues for the treating clinicians. The clinicians felt their duty to the child was compromised, but recognised that our society leaves the authority for such decisions with the parents. As there was no reason, other than different beliefs about vaccination, to doubt the parent\u27s care for the child, the clinicians limited their response to providing strong recommendations in favour of vaccination. Other issues raised by this case include community protection, and the costs to the community of treating a vaccine-preventable disease

ITI-007 demonstrates brain occupancy at serotonin 5-HT2A and dopamine D2 receptors and serotonin transporters using positron emission tomography in healthy volunteers

© 2015 Springer-Verlag Berlin Heidelberg.Rationale: Central modulation of serotonin and dopamine underlies efficacy for a variety of psychiatric therapeutics. ITI-007 is an investigational new drug in development for treatment of schizophrenia, mood disorders, and other neuropsychiatric disorders. Objectives: The purpose of this study was to determine brain occupancy of ITI-007 at serotonin 5-HT2A receptors, dopamine D2 receptors, and serotonin transporters using positron emission tomography (PET) in 16 healthy volunteers. Methods: Carbon-11-MDL100907, carbon-11-raclopride, and carbon-11-3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)-benzonitrile) (carbon-11-DASB) were used as the radiotracers for imaging 5-HT2A receptors, D2 receptors, and serotonin transporters, respectively. Brain regions of interest were outlined using magnetic resonance tomography (MRT) with cerebellum as the reference region. Binding potentials were estimated by fitting a simplified reference tissue model to the measured tissue-time activity curves. Target occupancy was expressed as percent change in the binding potentials before and after ITI-007 administration. Results: Oral ITI-007 (10-40 mg) was safe and well tolerated. ITI-007 rapidly entered the brain with long-lasting and dose-related occupancy. ITI-007 (10 mg) demonstrated high occupancy (>80 %) of cortical 5-HT2A receptors and low occupancy of striatal D2 receptors (~12 %). D2 receptor occupancy increased with dose and significantly correlated with plasma concentrations (r 2∈=∈0.68, p∈=∈0.002). ITI-007 (40 mg) resulted in peak occupancy up to 39 % of striatal D2 receptors and 33 % of striatal serotonin transporters. Conclusions: The results provide evidence for a central mechanism of action via dopaminergic and serotonergic pathways for ITI-007 in living human brain and valuable information to aid dose selection for future clinical trials