AutoDiscern: Rating the Quality of Online Health Information with Hierarchical Encoder Attention-based Neural Networks

Patients increasingly turn to search engines and online content before, or in place of, talking with a health professional. Low quality health information, which is common on the internet, presents risks to the patient in the form of misinformation and a possibly poorer relationship with their physician. To address this, the DISCERN criteria (developed at University of Oxford) are used to evaluate the quality of online health information. However, patients are unlikely to take the time to apply these criteria to the health websites they visit. We built an automated implementation of the DISCERN instrument (Brief version) using machine learning models. We compared the performance of a traditional model (Random Forest) with that of a hierarchical encoder attention-based neural network (HEA) model using two language embeddings, BERT and BioBERT. The HEA BERT and BioBERT models achieved average F1-macro scores across all criteria of 0.75 and 0.74, respectively, outperforming the Random Forest model (average F1-macro = 0.69). Overall, the neural network based models achieved 81% and 86% average accuracy at 100% and 80% coverage, respectively, compared to 94% manual rating accuracy. The attention mechanism implemented in the HEA architectures not only provided 'model explainability' by identifying reasonable supporting sentences for the documents fulfilling the Brief DISCERN criteria, but also boosted F1 performance by 0.05 compared to the same architecture without an attention mechanism. Our research suggests that it is feasible to automate online health information quality assessment, which is an important step towards empowering patients to become informed partners in the healthcare process

SU(5) Octet Scalar at the LHC

Color scalars are salient features of non-minimal SU(5) model, where Higgs sector is extended by 45-dimensional multiplet. We show that gauge coupling unification can be realized in this model with TeV octet scalar and intermediate (~10^6 GeV) color-triplet scalar at scale larger than 10^{15} GeV. We analyze the possible LHC signatures of these TeV octet scalars. We emphasize that multi-(b)-jet final states provide significant signal for direct probe of octet scalars at the LHC.Comment: 8 pages, 6 figure

Neural networks versus Logistic regression for 30 days all-cause readmission prediction

Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease progression and a source of considerable financial burden to the healthcare system. Consequently, the identification of patients at risk for readmission is a key step in improving disease management and patient outcome. In this work, we used a large administrative claims dataset to (1)explore the systematic application of neural network-based models versus logistic regression for predicting 30 days all-cause readmission after discharge from a HF admission, and (2)to examine the additive value of patients' hospitalization timelines on prediction performance. Based on data from 272,778 (49% female) patients with a mean (SD) age of 73 years (14) and 343,328 HF admissions (67% of total admissions), we trained and tested our predictive readmission models following a stratified 5-fold cross-validation scheme. Among the deep learning approaches, a recurrent neural network (RNN) combined with conditional random fields (CRF) model (RNNCRF) achieved the best performance in readmission prediction with 0.642 AUC (95% CI, 0.640-0.645). Other models, such as those based on RNN, convolutional neural networks and CRF alone had lower performance, with a non-timeline based model (MLP) performing worst. A competitive model based on logistic regression with LASSO achieved a performance of 0.643 AUC (95%CI, 0.640-0.646). We conclude that data from patient timelines improve 30 day readmission prediction for neural network-based models, that a logistic regression with LASSO has equal performance to the best neural network model and that the use of administrative data result in competitive performance compared to published approaches based on richer clinical datasets

How do the top 40 business schools in the UK understand, teach and implement KM in their teaching?

Purpose: The emergence of “knowledge economies” brings along new lenses to organizational management and behaviour. One of the key concepts at the heart of this new wave is knowledge management (KM). The purpose of this paper is to scrutinize how KM is taught and discussed within the context of business schools around the UK. Design/methodology/approach: The general research question is: how do top 40 business schools in the UK understand, teach and implement KM in their teaching? To answer this question, the author reviewed the curriculums of leading schools and contacted all schools to collect more information and data. Findings: The study reveals that KM has yet to carve a self-standing place for itself within taught programmes in UK business schools. Research limitations/implications: The study’s methodological design can explore the relevance of KM as a term, but it can only provide limited perspective into how this complex and multidimensional concept is operationalized in business schools’ curriculums. Moreover, the capacity of business schools to frame KM holistically is beyond the scope of this research. Practical implications: Framing KM discourse within the relevant academic literature, this paper outlines that, while KM is being scrutinized as a research topic, interest in KM has yet to be translated into a widespread integration of KM as a taught skill within business schools. Originality/value: The study is considered as one of the first attempts to investigate how KM is understood, taught and implemented in teaching and curriculum design within the UK business schools

Les raisons d'être de la franchise dans les transactions de services aux entreprises

The Reason for the Franchise in Transactions Business Services Abstract - The franchise, as hybrid form of coordination undertake an asymmetric allocation of legal and economic rights between the parties. The franchise is a governance structure that is particularly successful in achieving balance incentive and control. However, business services represent less than 7% of franchise networks in France. We study why the markets for business services could become "new land of conquest" for the franchise.La franchise, comme forme hybride de coordination procède à une allocation asymétrique des droits juridiques et économiques entre les parties. Elle constitue une forme de coordination particulièrement performante en parvenant à équilibrer incitation et contrôle. Pourtant, les prestations de services aux entreprises représentent moins de 7% des réseaux de franchise recensés en France. Nous montrons pourquoi les marchés des services aux entreprises pourraient devenir de "nouvelles terres de conquête " pour la franchise. contrat de franchise, forme hybride de coordination, actif immatériel, externalité de réseau, relation d'autorité, contrôle et droits économiques

The Sloan Bright Arcs Survey : Six Strongly Lensed Galaxies at z=0.4-1.4

We present new results of our program to systematically search for strongly lensed galaxies in the Sloan Digital Sky Survey (SDSS) imaging data. In this study six strong lens systems are presented which we have confirmed with follow-up spectroscopy and imaging using the 3.5m telescope at the Apache Point Observatory. Preliminary mass models indicate that the lenses are group-scale systems with velocity dispersions ranging from 466-878 km s^{-1} at z=0.17-0.45 which are strongly lensing source galaxies at z=0.4-1.4. Galaxy groups are a relatively new mass scale just beginning to be probed with strong lensing. Our sample of lenses roughly doubles the confirmed number of group-scale lenses in the SDSS and complements ongoing strong lens searches in other imaging surveys such as the CFHTLS (Cabanac et al 2007). As our arcs were discovered in the SDSS imaging data they are all bright ($r\lesssim22$), making them ideally suited for detailed follow-up studies.Comment: 13 pages, 3 figures, submitted to ApJL, the Sloan Bright Arcs page is located here: http://home.fnal.gov/~kubo/brightarcs.htm

Statistical model of the tool/workpiece mechanical interactions in FSW

The robotization of the FSW process is facing two challenges which are to support the amplitude of the tool / workpiece mechanical interaction generated by welding and to apply the process parameters and in particular the axial force. To design the control laws of the robot it is necessary to model the mechanical interaction between the tool and the workpiece as function of the fsw process parameters

Les raisons d'être de la franchise dans les transactions de services aux entreprises

La franchise, comme forme hybride de coordination procède à une allocation asymétrique des droits juridiques et économiques entre les parties. Elle constitue une forme de coordination particulièrement performante en parvenant à équilibrer incitation et contrôle. Pourtant, les prestations de services aux entreprises représentent moins de 7% des réseaux de franchise recensés en France. Nous montrons pourquoi les marchés des services aux entreprises pourraient devenir de "nouvelles terres de conquête " pour la franchise. contrat de franchise, forme hybride de coordination, actif immatériel, externalité de réseau, relation d'autorité, contrôle et droits économiques.contrat de franchise, forme hybride de coordination, actif immatériel, externalité de réseau, relation d'autorité, contrôle et droits économiques.

The Sloan Bright Arcs Survey: Four Strongly Lensed Galaxies with Redshift >2

We report the discovery of four very bright, strongly-lensed galaxies found via systematic searches for arcs in Sloan Digital Sky Survey Data Release 5 and 6. These were followed-up with spectroscopy and imaging data from the Astrophysical Research Consortium 3.5m telescope at Apache Point Observatory and found to have redshift $z>2.0$. With isophotal magnitudes $r = 19.2 - 20.4$ and 3\arcsec-diameter magnitudes $r = 20.0 - 20.6$, these systems are some of the brightest and highest surface brightness lensed galaxies known in this redshift range. In addition to the magnitudes and redshifts, we present estimates of the Einstein radii, which range from 5.0 \arcsec to 12.7 \arcsec, and use those to derive the enclosed masses of the lensing galaxies