LCCT: a semisupervised model for sentiment classification

Conference Theme: Human Language TechnologiesAnalyzing public opinions towards products, services and social events is an important but challenging task. An accurate sentiment analyzer should take both lexicon-level information and corpus-level information into account. It also needs to exploit the domain-specific knowledge and utilize the common knowledge shared across domains. In addition, we want the algorithm being able to deal with missing labels and learning from incomplete sentiment lexicons. This paper presents a LCCT (Lexicon-based and Corpus-based, Co-Training) model for semi-supervised sentiment classification. The proposed method combines the idea of lexicon-based learning and corpus-based learning in a unified co-training framework. It is capable of incorporating both domain-specific and domain-independent knowledge. Extensive experiments show that it achieves very competitive classification accuracy, even with a small portion of labeled data. Comparing to state-of-the-art sentiment classification methods, the LCCT approach exhibits significantly better performances on a variety of datasets in both English and Chinese. © 2015 Association for Computational Linguisticspublished_or_final_versio

All-fiber ultrafast thulium-doped fiber ring laser with dissipative soliton and noise-like output in normal dispersion by single-wall carbon nanotubes

An ultrafast thulium-doped fiber laser with large net normal dispersion has been developed to produce dissipative soliton and noise-like outputs at 1.9 μm. The mode-locked operation was enabled by using single-wall carbon nanotubes as saturable absorber for all-fiber configuration. Dissipative soliton in normal dispersion produced by the fiber laser oscillator was centered at 1947 nm with 4.1-nm FWHM bandwidth and 0.45 nJ/pulse. The output dissipative soliton pulses were compressed to 2.3 ps outside the laser cavity. © 2013 AIP Publishing LLC

All-fiber passively mode-locked thulium-doped fiber ring laser using optically deposited graphene saturable absorbers

An all-fiber passively mode-locked thulium-doped fiber ring oscillator is constructed using optically deposited few layer graphene micro-sheets as the saturable absorber (SA). The mode-lock operation was achieved by 130-mW pump power at 1.5-μm. The fiber oscillator produces 2.1-ps soliton pulse output with 80-pJ per pulse energy. The 3-dB bandwidth of the laser output was measured as 2.2-nm. The RF signal-to-noise ratio of 50-dB and sub 20-Hz 3-dB bandwidth of the laser output confirms the stable laser operation with low time jittering. This paper shows that graphene can be an effective saturable absorber for the development of mid-IR fiber mode-locked laser. © 2013 American Institute of Physics

The mobile emergency recovery intervention trial (MERIT): Protocol for a 3-year mixed methods observational study of mobile recovery outreach teams in Nevada's emergency departments.

BACKGROUND: The Substance Abuse and Mental Health Administration awarded State Targeted Response grants to support states' efforts to address the opioid epidemic. In Nevada, one component of this grant was mobile recovery outreach teams (MROTs) that utilized peer recovery support specialists to provide care for qualifying patients in emergency departments (EDs). The Mobile Emergency Recovery Intervention Trial (MERIT) is a mixed methods study to assess the feasibility/acceptability and effectiveness of the MROT intervention. This protocol mainly describes the R33 research activities and outcomes. The full protocol can be found protocols.io. METHODS: Data will be derived from state-level data sets containing de-identified emergency department visits, substance use disorder treatment records, and mortality files; in-person mixed methods interviews; participant observation; and self-report process evaluation forms. Primary outcomes include Medication Assisted Treatment (MAT) initiation and non-fatal overdose; secondary outcomes include MAT retention and fatal overdose. Quantitative hypotheses will be tested using generalized linear mixed effects models, Bayesian hierarchical models, and marginal Cox models. Qualitative interview data will be analyzed using an inductive thematic analysis procedure. DISCUSSION: It is impossible to conduct a randomized controlled trial of the effectiveness of the MROTs, given the ethical and logistical considerations of this intervention.This study's innovative design employs a mixed methods formative phase to examine feasibility and acceptability, and a quasi-experimental outcomes evaluation phase employing advanced statistical methods to mitigate bias and suggest causal inference regarding the effectiveness of the MROTs.Innovative interventions have been deployed in many states; evidence regarding their effectiveness is lacking, but critical to informing an effective public health response to the opioid epidemic

Robust Facial Alignment for Face Recognition

© 2017, Springer International Publishing AG. This paper proposes a robust real-time face recognition system that utilizes regression tree based method to locate the facial feature points. The proposed system finds the face region which is suitable to perform the recognition task by geometrically analyses of the facial expression of the target face image. In real-world facial recognition systems, the face is often cropped based on the face detection techniques. The misalignment is inevitably occurred due to facial pose, noise, occlusion, and so on. However misalignment affects the recognition rate due to sensitive nature of the face classifier. The performance of the proposed approach is evaluated with four benchmark databases. The experiment results show the robustness of the proposed approach with significant improvement in the facial recognition system on the various size and resolution of given face images

Design of an electrochemical micromachining machine

Electrochemical micromachining (μECM) is a non-conventional machining process based on the phenomenon of electrolysis. μECM became an attractive area of research due to the fact that this process does not create any defective layer after machining and that there is a growing demand for better surface integrity on different micro applications including microfluidics systems, stress-free drilled holes in automotive and aerospace manufacturing with complex shapes, etc. This work presents the design of a next generation μECM machine for the automotive, aerospace, medical and metrology sectors. It has three axes of motion (X, Y, Z) and a spindle allowing the tool-electrode to rotate during machining. The linear slides for each axis use air bearings with linear DC brushless motors and 2-nm resolution encoders for ultra precise motion. The control system is based on the Power PMAC motion controller from Delta Tau. The electrolyte tank is located at the rear of the machine and allows the electrolyte to be changed quickly. This machine features two process control algorithms: fuzzy logic control and adaptive feed rate. A self-developed pulse generator has been mounted and interfaced with the machine and a wire ECM grinding device has been added. The pulse generator has the possibility to reverse the pulse polarity for on-line tool fabrication.The research reported in this paper is supported by the European Commission within the project “Minimizing Defects in Micro-Manufacturing Applications (MIDEMMA)” (FP7-2011-NMPICT- FoF-285614)

A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application

© 2016 IEEE. A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications

Dystonic opisthotonus: A "red flag" for neurodegeneration with brain iron accumulation syndromes?

Back arching was reported in one of the very first patients with neurodegeneration with brain iron accumulation syndrome (NBIAs) published in 1936. However, recent reports have mainly focused on the genetic and imaging aspects of these disorders, and the phenotypic characterization of the dystonia has been lost. In evaluating patients with NBIAs in our centers, we have observed that action-induced dystonic opisthotonus is a common and characteristic feature of NBIAs. Here, we present a case series of patients with NBIAs presenting this feature demonstrated by videos. We suggest that dystonic opisthotonus could be a useful "red flag" for clinicians to suspect NBIAs, and we discuss the differential diagnosis of this feature. This would be particularly useful in identifying patients with NBIAs and no iron accumulation as yet on brain imaging (for example, as in phospholipase A2, group IV (cytosolic, calcium-independent) [PLA2G6]-related disorders), and it has management implications.© 2013 International Parkinson and Movement Disorder Society

Damage modelling: the current state and the latest progress on the development of creep damage constitutive equations for high Cr steels

This paper reviews the fundamentals of the development of creep damage constitutive equations for high Cr steels including (1) a concise summary of the characteristics of creep deformation and creep damage evolution and their dependence on the stress level and the importance of cavitation for the final fracture; (2) a critical review of the state of art of creep damage equation for high Cr steels; (3) some discussion and comments on the various approaches; (4) consideration and suggestion for future work. It emphasises the need for better understanding the nucleation, cavity growth and coalesces and the theory for coupling method between creep cavity damage and brittle fracture and generalisatio

The association between vitamin D and multiple sclerosis risk: 1,25(OH)2D3 induces super-enhancers bound by VDR

A super-enhancer (SE) is a cluster of enhancers with a relatively high density of particular chromatin features. SEs typically regulate key genes that can determine cell identity and differentiation. Identifying SEs and their effects may be critical in predicting key regulatory genes, such as master transcription factor genes or oncogenes. Signal inducible SEs are dense stretches of signal terminal transcription factor (TF) binding regions, and may modulate the interaction between environmental factors (e.g., Vitamin D) and genetic factors (i.e., risk variants) in complex diseases such as multiple sclerosis (MS). As a complex autoimmune disease, the etiology and progression of MS, including the interaction between Vitamin D and MS risk variants, is still unclear and can be explored from the aspect of signal SEs. Vitamin D [with its active form: 1,25(OH)2D3], is an environmental risk factor for MS. It binds the Vitamin D receptor (VDR) and regulates gene expression. This study explores the association between VDR super-enhancers (VSEs) and MS risk variants. Firstly, we reanalyse public ChIP-seq and RNA-seq data to classify VSEs into three categories according to their combinations of persistent and secondary VDR binding. Secondly, we indicate the genes with VSE regions that are near MS risk variants. Furthermore, we find that MS risk variants are enriched in VSE regions, and we indicate some genes with a VSE overlapping MS risk variant for further exploration. We also find two clusters of genes from the set of genes showing correlation of expression patterns with the MS risk gene ZMIZ1 that appear to be regulated by VSEs in THP-1 cells. It is the first time that VSEs have been analyzed, and we directly connect the genetic risk factors for MS risk with Vitamin D based on VSEs