An experiment in integrating sentiment features for tech stock prediction in Twitter

Economic analysis indicates a relationship between consumer sentiment and stock price movements. In this study we harness features from Twitter messages to capture public mood related to four Tech companies for predicting the daily up and down price movements of these companies’ NASDAQ stocks. We propose a novel model combining features namely positive and negative sentiment, consumer confidence in the product with respect to ‘bullish’ or ‘bearish’ lexicon and three previous stock market movement days. The features are employed in a Decision Tree classifier using cross-fold validation to yield accuracies of 82.93%,80.49%, 75.61% and 75.00% in predicting the daily up and down changes of Apple (AAPL), Google (GOOG), Microsoft (MSFT) and Amazon (AMZN) stocks respectively in a 41 market day sample

Large-scale exploration of neural relation classification architectures

Experimental performance on the task of relation classification has generally improved using deep neural network architectures. One major drawback of reported studies is that individual models have been evaluated on a very narrow range of datasets, raising questions about the adaptability of the architectures, while making comparisons between approaches difficult. In this work, we present a systematic large-scale analysis of neural relation classification architectures on six benchmark datasets with widely varying characteristics. We propose a novel multi-channel LSTM model combined with a CNN that takes advantage of all currently popular linguistic and architectural features. Our ‘Man for All Seasons’ approach achieves state-of-the-art performance on two datasets. More importantly, in our view, the model allowed us to obtain direct insights into the continued challenges faced by neural language models on this task. Example data and source code are available at: https://github.com/aidantee/ MASS.MR

Sieve-based coreference resolution enhances semi-supervised learning model for chemical-induced disease relation extraction.

The BioCreative V chemical-disease relation (CDR) track was proposed to accelerate the progress of text mining in facilitating integrative understanding of chemicals, diseases and their relations. In this article, we describe an extension of our system (namely UET-CAM) that participated in the BioCreative V CDR. The original UET-CAM system's performance was ranked fourth among 18 participating systems by the BioCreative CDR track committee. In the Disease Named Entity Recognition and Normalization (DNER) phase, our system employed joint inference (decoding) with a perceptron-based named entity recognizer (NER) and a back-off model with Semantic Supervised Indexing and Skip-gram for named entity normalization. In the chemical-induced disease (CID) relation extraction phase, we proposed a pipeline that includes a coreference resolution module and a Support Vector Machine relation extraction model. The former module utilized a multi-pass sieve to extend entity recall. In this article, the UET-CAM system was improved by adding a 'silver' CID corpus to train the prediction model. This silver standard corpus of more than 50 thousand sentences was automatically built based on the Comparative Toxicogenomics Database (CTD) database. We evaluated our method on the CDR test set. Results showed that our system could reach the state of the art performance with F1 of 82.44 for the DNER task and 58.90 for the CID task. Analysis demonstrated substantial benefits of both the multi-pass sieve coreference resolution method (F1 + 4.13%) and the silver CID corpus (F1 +7.3%).Database URL: SilverCID-The silver-standard corpus for CID relation extraction is freely online available at: https://zenodo.org/record/34530 (doi:10.5281/zenodo.34530).H-Q.L. and T.H.D. gratefully acknowledge funding support from Vietnam National University, Hanoi (VNU), under Project No. QG.15.21. N.C. gratefully acknowledges funding support from the UK EPSRC (grant number EP/M005089/1). Funding for open access charge : VNUH Project No. QG.15.21

Molecularly Engineered Self-Assembling Membranes for Cell-Mediated Degradation

The use of peptide engineering to develop self-assembling membranes that are responsive to cellular enzyme activities is reported. The membranes are obtained by combining hyaluronan (HA) and a rationally designed peptide amphiphile (PA) containing a proteolytic domain (GPQGIWGQ octapeptide) sensitive to matrix metalloproteinase-1 (MMP-1). Insertion of an octapeptide in a typical PA structure does not disturb its self-assembly into fibrillar nanostructures neither the ability to form membranes with HA. In vitro enzymatic degradation with hyaluronidase and MMP-1 shows that membranes containing the MMP-1 substrate exhibit enhanced enzymatic degradation, compared with control membranes (absence of MMP-1 cleavable peptide or containing a MMP-1 insensitive sequence), being completely degraded after 7 days. Cell viability and proliferation is minimally affected by the enzymatically cleavable functionality of the membrane, but the presence of MMP-1 cleavable sequence does stimulate the secretion of MMP-1 by fibroblasts and interfere with matrix deposition, particularly the deposition of collagen. By showing cell-responsiveness to biochemical signals presented on self-assembling membranes, this study highlights the ability of modulating certain cellular activities through matrix engineering. This concept can be further explored to understand the cellular remodeling process and as a strategy to develop artificial matrices with more biomimetic degradation for tissue engineering applications.This work was funded by the European Regional Development Fund (ERDF) through the Operational Competitiveness Programme "COMPETE" (FCOMP-01-0124-FEDER-014758) and national funds through the Portuguese Foundation for Science and Technology (FCT) under the project PTDC/EBB-BIO/114523/2009. The authors also thank a start-up grant provided by the School of Engineering and Materials Science at QMUL. D.S.F. gratefully acknowledges FCT for the PhD scholarship (SFRH/BD/44977/2008)

Acoustic Communication for Medical Nanorobots

Communication among microscopic robots (nanorobots) can coordinate their activities for biomedical tasks. The feasibility of in vivo ultrasonic communication is evaluated for micron-size robots broadcasting into various types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff between efficient acoustic generation and attenuation for communication over distances of about 100 microns. Based on these results, we find power available from ambient oxygen and glucose in the bloodstream can readily support communication rates of about 10,000 bits/second between micron-sized robots. We discuss techniques, such as directional acoustic beams, that can increase this rate. The acoustic pressure fields enabling this communication are unlikely to damage nearby tissue, and short bursts at considerably higher power could be of therapeutic use.Comment: added discussion of communication channel capacity in section

Chemical Power for Microscopic Robots in Capillaries

The power available to microscopic robots (nanorobots) that oxidize bloodstream glucose while aggregated in circumferential rings on capillary walls is evaluated with a numerical model using axial symmetry and time-averaged release of oxygen from passing red blood cells. Robots about one micron in size can produce up to several tens of picowatts, in steady-state, if they fully use oxygen reaching their surface from the blood plasma. Robots with pumps and tanks for onboard oxygen storage could collect oxygen to support burst power demands two to three orders of magnitude larger. We evaluate effects of oxygen depletion and local heating on surrounding tissue. These results give the power constraints when robots rely entirely on ambient available oxygen and identify aspects of the robot design significantly affecting available power. More generally, our numerical model provides an approach to evaluating robot design choices for nanomedicine treatments in and near capillaries.Comment: 28 pages, 7 figure

A mid year comparison study of career satisfaction and emotional states between residents and faculty at one academic medical center

BACKGROUND: The Accreditation Council for Graduate Medical Education's (ACGME) new requirements raise multiple challenges for academic medical centers. We sought to evaluate career satisfaction, emotional states, positive and negative experiences, work hours and sleep among residents and faculty simultaneously in one academic medical center after implementation of the ACGME duty hour requirements. METHODS: Residents and faculty (1330) in the academic health center were asked to participate in a confidential survey; 72% of the residents and 66% of the faculty completed the survey. RESULTS: Compared to residents, faculty had higher levels of satisfaction with career choice, competence, importance and usefulness; lower levels of anxiousness and depression. The most positive experiences for both groups corresponded to strong interpersonal relationships and educational value; most negative experiences to poor interpersonal relationships and issues perceived outside of the physician's control. Approximately 13% of the residents and 14% of the faculty were out of compliance with duty hour requirements. Nearly 5% of faculty reported working more than 100 hours per week. For faculty who worked 24 hour shifts, nearly 60% were out of compliance with the duty-hour requirements. CONCLUSION: Reasons for increased satisfaction with career choice, positive emotional states and experiences for faculty compared to residents are unexplained. Earlier studies from this institution identified similar positive findings among advanced residents compared to more junior residents. Faculty are more frequently at risk for duty-hour violations. If patient safety is of prime importance, faculty, in particular, should be compliant with the duty hour requirements. Perhaps the ACGME should contain faculty work hours as part of its regulatory function

Organic electrode coatings for next-generation neural interfaces

Traditional neuronal interfaces utilize metallic electrodes which in recent years have reached a plateau in terms of the ability to provide safe stimulation at high resolution or rather with high densities of microelectrodes with improved spatial selectivity. To achieve higher resolution it has become clear that reducing the size of electrodes is required to enable higher electrode counts from the implant device. The limitations of interfacing electrodes including low charge injection limits, mechanical mismatch and foreign body response can be addressed through the use of organic electrode coatings which typically provide a softer, more roughened surface to enable both improved charge transfer and lower mechanical mismatch with neural tissue. Coating electrodes with conductive polymers or carbon nanotubes offers a substantial increase in charge transfer area compared to conventional platinum electrodes. These organic conductors provide safe electrical stimulation of tissue while avoiding undesirable chemical reactions and cell damage. However, the mechanical properties of conductive polymers are not ideal, as they are quite brittle. Hydrogel polymers present a versatile coating option for electrodes as they can be chemically modified to provide a soft and conductive scaffold. However, the in vivo chronic inflammatory response of these conductive hydrogels remains unknown. A more recent approach proposes tissue engineering the electrode interface through the use of encapsulated neurons within hydrogel coatings. This approach may provide a method for activating tissue at the cellular scale, however, several technological challenges must be addressed to demonstrate feasibility of this innovative idea. The review focuses on the various organic coatings which have been investigated to improve neural interface electrodes

Well-being in residency training: a survey examining resident physician satisfaction both within and outside of residency training and mental health in Alberta

BACKGROUND: Despite the critical importance of well-being during residency training, only a few Canadian studies have examined stress in residency and none have examined well-being resources. No recent studies have reported any significant concerns with respect to perceived stress levels in residency. We investigated the level of perceived stress, mental health and understanding and need for well-being resources among resident physicians in training programs in Alberta, Canada. METHODS: A mail questionnaire was distributed to the entire resident membership of PARA during 2003 academic year. PARA represents each of the two medical schools in the province of Alberta. RESULTS: In total 415 (51 %) residents participated in the study. Thirty-four percent of residents who responded to the survey reported their life as being stressful. Females reported stress more frequently than males (40% vs. 27%, p < 0.02). Time pressure was reported as the number one factor contributing to stress (44% of males and 57% of females). A considerable proportion of residents would change their specialty program (14%) and even more would not pursue medicine (22%) if given the opportunity to relive their career. Up to 55% of residents reported experiencing intimidation and harassment. Intimidation and harassment was strongly related to gender (12% of males and 38% of females). Many residents (17%) rated their mental health as fair or poor. This was more than double the amount reported in the Canadian Community Health Survey from the province (8%) or the country (7%). Residents highly valued their colleagues (67%), program directors (60%) and external psychiatrist/psychologist (49%) as well-being resources. Over one third of residents wished to have a career counselor (39%) and financial counselor (38%). CONCLUSION: Many Albertan residents experience significant stressors and emotional and mental health problems. Some of which differ among genders. This study can serve as a basis for future resource application, research and advocacy for overall improvements to well-being during residency training

The Impact of Duty Hours on Resident Self Reports of Errors

BACKGROUND: Resident duty hour limitations aim, in part, to reduce medical errors. Residents’ perceptions of the impact of duty hours on errors are unknown. OBJECTIVE: To determine residents’ self-reported contributing factors, frequency, and impact of hours worked on suboptimal care practices and medical errors. DESIGN: Cross-sectional survey. SUBJECTS: 164 Internal Medicine Residents at the University of California, San Francisco. MEASUREMENTS AND RESULTS: Residents were asked to report the frequency and contributing factors of suboptimal care practices and medical errors, and how duty hours impacted these practices and aspects of resident work-life. One hundred twenty-five residents (76%) responded. The most common suboptimal care practices were working while impaired by fatigue and forgetting to transmit information during sign-out. In multivariable models, residents who felt overwhelmed with work (p = 0.02) and who reported spending >50% of their time in nonphysician tasks (p = 0.002) were more likely to report suboptimal care practices. Residents reported work-stress (a composite of fatigue, excessive workload, distractions, stress, and inadequate time) as the most frequent contributing factor to medical errors. In multivariable models, only engaging in suboptimal practices was associated with self-report of higher risk for medical errors (p < 0.001); working more than 80 hours per week was not associated with suboptimal care or errors. CONCLUSION: Our findings suggest that administrative load and work stressors are more closely associated with resident reports of medical errors than the number of hours work. Efforts to reduce resident duty hours may also need to address the nature of residents’ work to reduce errors