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

Analyzing ASR Pretraining for Low-Resource Speech-to-Text Translation

Previous work has shown that for low-resource source languages, automatic speech-to-text translation (AST) can be improved by pretraining an end-to-end model on automatic speech recognition (ASR) data from a high-resource language. However, it is not clear what factors --e.g., language relatedness or size of the pretraining data-- yield the biggest improvements, or whether pretraining can be effectively combined with other methods such as data augmentation. Here, we experiment with pretraining on datasets of varying sizes, including languages related and unrelated to the AST source language. We find that the best predictor of final AST performance is the word error rate of the pretrained ASR model, and that differences in ASR/AST performance correlate with how phonetic information is encoded in the later RNN layers of our model. We also show that pretraining and data augmentation yield complementary benefits for AST.Comment: Accepted at ICASSP 202

Neurotropic viruses and cerebral palsy: population based case-control study

Objective: To investigate the association between cerebral palsy and direct evidence for perinatal exposure to neurotropic viruses. Design: Population based case-control study. Setting: Adelaide Women's and Children's Hospital Research Laboratory. Participants and main outcome measures: Newborn screening cards of 443 white case patients with cerebral palsy and 883 white controls were tested for viral nucleic acids from enteroviruses and herpes viruses by using polymerase chain reaction. Herpes group A viruses included herpes simplex viruses 1 and 2 (HSV-1 and HSV-2), Epstein-Barr virus (EBV), cytomegalovirus (CMV), and human herpes virus 8 (HHV-8), and herpes group B viruses included varicella zoster virus (VZV) and human herpes viruses 6 and 7 (HHV-6 and HHV-7). Results: The prevalence of viral nucleic acids in the control population was high: 39.8% of controls tested positive, and the prevalence was highest in preterm babies. The detection of herpes group B viral nucleic acids increased the risk of developing cerebral palsy (odds ratio 1.68, 95% confidence interval 1.09 to 2.59). Conclusions: Perinatal exposure to neurotropic viruses is associated with preterm delivery and cerebral palsy.Catherine S. Gibson, Alastair H. MacLennan, Paul N. Goldwater, Eric A. Haan, Kevin Priest and Gustaaf A. Dekker

Variant interleukin 1 receptor antagonist gene alleles in sudden infant death syndrome

Objective: To investigate if carriage of interleukin 1 (IL-1) receptor antagonist gene variants are associated with sudden infant death syndrome (SIDS) in a large cohort of case–control demographically matched infants. Design: 118 SIDS and 233 control infants, who were matched to each SIDS infant by date of birth, sex, birth weight (±500 g), gestational age and ethnicity, were genotyped for an IL-1RN 89 bp tandem repeat polymorphism and analysed for significant associations. Results: No significant difference in genotype frequencies was observed between low and normal birthweight infants and year of birth (1987–1994, when the SIDS incidence was higher). In infants born between 1987 and 1994, an association was observed with SIDS and allele 2 where 18% of SIDS infants carried the 2/2 genotype compared with 9% of controls (χ2 p=0.026, OR 2.46). Allele 3 was found at a low frequency, but was significantly more common in SIDS infants (3.1%) compared with controls (0.9%, Fisher's exact p=0.04, OR 3.76). Conclusion: The higher prevalence of IL-1RN allele 2, which predisposes to poor outcomes from infection, in SIDS infants born between 1987 and 1994 (ie, prior to the dramatic decrease in SIDS incidence) suggests that the high incidence during this period could point to infection playing a role in aetiology. An association of IL-1RN allele 3 with SIDS was also found, but should be interpreted with caution due to the low frequency of this variant. The consequence of allele 3 carriage is currently unknown in the absence of functionality studies for this isoform.Amanda R. Highet, Catherine S. Gibson and Paul N. Goldwate

Impact of Outpatient vs Inpatient ABSSSI Treatment on Outcomes: A Retrospective Observational Analysis of Medical Charts Across US Emergency Departments

Background The objective of this study was to characterize treatment of patients with acute bacterial skin and skin structure infections (ABSSSIs) and describe the association between hospital admission and emergency department (ED) visits or readmissions within 30 days after initial episode of care (IEC). Methods This was a retrospective, observational, cohort study of adults with ABSSSI who presented to an ED between July 1, 2012, and June 30, 2013. Patient, health care facility, and treatment characteristics, including unplanned ED visits or readmissions, were obtained through manual chart review and abstraction. Adjusted logistic regression analysis examined likelihood of all-cause unplanned ED visits or readmissions between admitted and nonadmitted patients. Results Records from 1527 ED visits for ABSSSI from 40 centers were reviewed (admitted, n = 578 [38%]; nonadmitted, n = 949 [62%]). Admitted patients were typically older (mean age, 52.2 years vs 43.0 years), more likely to be morbidly obese (body mass index \u3e 40 kg/m2; 17.3% vs 9.1%), and had more comorbidities (Charlson Comorbidity Index ≥ 4; 24.4% vs 6.8%) compared with those not admitted. In the primary analysis, adjusted logistic regression, controlling for comorbidities and severity of illness, demonstrated that there was a similar likelihood of all-cause unplanned ED visits or readmissions between admitted and nonadmitted patients (odds ratio, 1.03; 95% confidence interval, 0.74–1.43; P = .87). Conclusions ABSSSI treatment pathways leveraging outpatient treatment vs hospital admission support similar likelihood of unplanned 30-day ED visits or readmissions, an important clinical outcome and quality metric at US hospitals. Further research regarding the decision criteria around hospital admission to avoid potentially unnecessary hospitalizations is warranted

Genetic and clinical contributions to cerebral palsy: A multi-variable analysis

All authors are contributors to the Australian Collaborative Cerebral Palsy Research Group The definitive version is available at www.wileyonlinelibrary.comAimThis study aims to examine single nucleotide polymorphism (SNP) associations with cerebral palsy in a multi-variable analysis adjusting for potential clinical confounders and to assess SNP-SNP and SNP-maternal infection interactions as contributors to cerebral palsy.MethodsA case control study including 587 children with cerebral palsy and 1154 control children without cerebral palsy. Thirty-nine candidate SNPs were genotyped in both mother and child. Data linkage to perinatal notes and cerebral palsy registers was performed with a supplementary maternal pregnancy questionnaire. History of known maternal infection during pregnancy was extracted from perinatal databases.ResultsBoth maternal and fetal carriage of inducible nitric oxide synthase SNP rs1137933 were significantly negatively associated with cerebral palsy in infants born at less than 32 weeks gestation after adjustment for potential clinical confounders and correction for multiple testing (odds ratio 0.55, 95% confidence interval 0.38-0.79; odds ratio 0.57, 95% confidence interval 0.4-0.82, respectively). Analysis did not show any statistically significant SNP-SNP or SNP-maternal infection interactions after correction for multiple testing.ConclusionsMaternal and child inducible nitric oxide synthase SNPs are associated with reduced risk of cerebral palsy in infants born very preterm. There was no evidence for statistically significant SNP-SNP or SNP-maternal infection interactions as modulators of cerebral palsy risk.Michael E O’Callaghan, Alastair H MacLennan, Catherine S Gibson, Gai L McMichael, Eric A Haan, Jessica L Broadbent, Peter A Baghurst, Paul N Goldwater, Gustaaf A Dekker and for the Australian Collaborative Cerebral Palsy Research Grou

Modelling Students’ Thematically Associated Knowledge : Networked Knowledge from Affinity Statistics

Peer reviewe

Continuous Interaction with a Virtual Human

Attentive Speaking and Active Listening require that a Virtual Human be capable of simultaneous perception/interpretation and production of communicative behavior. A Virtual Human should be able to signal its attitude and attention while it is listening to its interaction partner, and be able to attend to its interaction partner while it is speaking – and modify its communicative behavior on-the-fly based on what it perceives from its partner. This report presents the results of a four week summer project that was part of eNTERFACE’10. The project resulted in progress on several aspects of continuous interaction such as scheduling and interrupting multimodal behavior, automatic classification of listener responses, generation of response eliciting behavior, and models for appropriate reactions to listener responses. A pilot user study was conducted with ten participants. In addition, the project yielded a number of deliverables that are released for public access