PARSEC: A Constraint-Based Parser for Spoken Language Processing

PARSEC (1), a text-based and spoken language processing framework based on the Constraint Dependency Grammar (CDG) developed by Maruyama [26,27], is discussed. The scope of CDG is expanded to allow for the analysis of sentences containing lexically ambiguous words, to allow feature analysis in constraints, and to efficiently process multiple sentence candidates that are likely to arise in spoken language processing. The benefits of the CDG parsing approach are summarized. Additionally, the development CDG grammars using PARSEC grammar writing tools and the implementation of the PARSEC parser for word graphs is discussed. (1) Parallel ARchitecture Sentence Constraine

Near minimal weighted word graphs for post-processing speech

Large vocabulary speech recognition applications can benefit from an efficient data structure for representing large numbers of acoustic hypotheses compactly. Word graphs or lattices generated by acoustic recognition engines are generally not compact and must be post-processed to keep lattice sizes small; however, algorithms designed for this task need to reduce the size of the lattice without either eliminating hypotheses or distorting their relative acoustic probabilities. In this paper, we will discuss the relevant criteria for measuring graph size, compare the advantages of two different structures for graphs, and introduce a new data structure and compression algorithm which give additional graph compression and maintain exact hypothesis path scores by storing probability information on both nodes and arcs within the graph. 1

A Tighter Lower Bound for 1-D Bin-Packing

For NP-complete problems, it may not be possible to find an optimal solution in polynomial time. However, efficient approximation algorithms for many NP-complete problems do exist. A good approach is to find tighter upper and lower bounds on the optimal solutions. As the gap between these two bounds approaches zero, optimality is reached. For minimization problems, any feasible solution serves as an upper bound. In general, researchers attempt to find heuristic algorithms to narrow the gap by decreasing the upper bound. Another approach is to narrow the gap by increasing the lower bound. To determine a good lower bound on a problem requires careful examination of the problem\u27s characteristics. In this paper, we present an efficient algorithm for calculating a lower bound on the number of bins needed in a bin-packing problem. It is obvious that the sum of the sizes of all objects is a lower bound. In addition to this, we consider objects that cannot share their bins with other objects. We consider a subproblem class which contains only objects whose sizes are greater than L/4, where L is the size of a bin, given the harmonic partition. An O(n1ogn) algorithm finds a lower bound for the subproblem, which in turn is a lower bound for the original problem. Notably, our approach also leads to a polynomial time algorithm for finding optimal solutions of some special cases of bin-packing. Simulation data show that our lower bound provides an estimate of the optimal number of bins required which is equal to or better than the sum. The approximate error rate is normally less than 1% if our bound is used. The improvement can be as high as 79% when compared to the sum

The Association Between the Long-Term Change in Directly Measured Cardiorespiratory Fitness and Mortality Risk

Introduction: There is a strong inverse association between cardiorespiratory fitness (CRF) and mortality outcomes. This relationship has predominantly been assessed cross-sectionally, however low CRF is a modifiable risk factor, thus assessing this association using a single baseline measure may be sub-optimal. Purpose: To examine the association of the long-term change in CRF, measured using cardiopulmonary exercise testing (CPX) with all-cause and disease-specific mortality. Methods: Participants included 833 apparently healthy men and women (42.9±10.8 years) who underwent two maximal CPXs, the second CPX being ≥ 1 year following the baseline assessment. Participants were followed for 17.7 ± 11.8 years for allcause, cardiovascular disease (CVD), and cancer mortality. Cox-proportional hazard models were performed to determine the association between the change in CRF, computed as visit 1 (V1) peak oxygen consumption (VO2peak (ml·kg-1·min-1)) – visit 2 (V2) VO2peak, and mortality outcomes. Results: During follow-up, 172 participants died. Overall, the change in CPX-derived CRF was inversely related to all-cause, CVD, and cancer mortality (p\u3c0.05). Each 1 ml·kg-1·min-1 increase was associated with a 10.8, 14.7, and 15.9% reductions in allcause, CVD, and cancer mortality, respectively. The inverse relationship between CRF and all-cause mortality remained significant (p\u3c0.05) when men and women were examined independently, after adjusting for years since first CPX, baseline VO2peak, and age. Conclusion: Long-term changes in CRF were inversely related to mortality outcomes, and mortality was better predicted by CRF measured at subsequent examination than baseline CRF. These findings support the recent American Heart Association scientific statement advocating CRF as a clinical vital sign that should be assessed routinely in clinical practice, as well as support regular participation in physical activity to maintain adequate CRF levels across the lifespan

Case Selection: A Case for a New Approach

While conducting empirical research regarding the relationship between case characteristics and student performance, the authors were surprised to find a lack of conceptual and empirical research regarding instructor case selection. This conceptual paper explores the case selection process and introduces case selection as an under-investigated component of the case teaching method in management education. Case selection is important because it is a critical component of the case teaching method. There has been no empirical testing of the effectiveness of case selection technique. The authors identify and propose case selection criteria for instructors of management education

Hospital characteristics and patient populations served by physician owned and non physician owned orthopedic specialty hospitals

<p>Abstract</p> <p>Background</p> <p>The emergence of physician owned specialty hospitals focusing on high margin procedures has generated significant controversy. Yet, it is unclear whether physician owned specialty hospitals differ significantly from non physician owned specialty hospitals and thus merit the additional scrutiny that has been proposed. Our objective was to assess whether physician owned specialty orthopedic hospitals and non physician owned specialty orthopedic hospitals differ with respect to hospital characteristics and patient populations served.</p> <p>Methods</p> <p>We conducted a descriptive study using Medicare data of beneficiaries who underwent total hip replacement (THR) (N = 10,478) and total knee replacement (TKR) (N = 15,312) in 29 physician owned and 8 non physician owned specialty orthopedic hospitals during 1999–2003. We compared hospital characteristics of physician owned and non physician owned specialty hospitals including procedural volumes of major joint replacements (THR and TKR), hospital teaching status, and for profit status. We then compared demographics and prevalence of common comorbid conditions for patients treated in physician owned and non physician owned specialty hospitals. Finally, we examined whether the socio-demographic characteristics of the neighborhoods where physician owned and non physician owned specialty hospitals differed, as measured by zip code level data.</p> <p>Results</p> <p>Physician owned specialty hospitals performed fewer major joint replacements on Medicare beneficiaries in 2003 than non physician owed specialty hospitals (64 vs. 678, P < .001), were less likely to be affiliated with a medical school (6% vs. 43%, P = .05), and were more likely to be for profit (94% vs. 28%, P = .001). Patients who underwent major joint replacement in physician owned specialty hospitals were less likely to be black than patients in non physician owned specialty hospitals (2.5% vs. 3.1% for THR, P = .15; 1.8% vs. 6.3% for TKR, P < .001), yet physician owned specialty hospitals were located in neighborhoods with a higher proportion of black residents (8.2% vs. 6.7%, P = .76). Patients in physician owned hospitals had lower rates of most common comorbid conditions including heart failure and obesity (P < .05 for both).</p> <p>Conclusion</p> <p>Physician owned specialty orthopedic hospitals differ significantly from non physician owned specialty orthopedic hospitals and may warrant the additional scrutiny policy makers have proposed.</p

Evolution of high pathogenicity of H5 avian influenza virus: haemagglutinin cleavage site selection of reverse-genetics mutants during passage in chickens

Low pathogenicity avian influenza viruses (LPAIVs) are generally asymptomatic in their natural avian hosts. LPAIVs can evolve into highly pathogenic forms, which can affect avian and human populations with devastating consequences. The switch to highly pathogenic avian influenza virus (HPAIV) from LPAIV precursors requires the acquisition of multiple basic amino acids in the haemagglutinin cleavage site (HACS) motif. Through reverse genetics of an H5N1 HPAIV, and experimental infection of chickens, we determined that viruses containing five or more basic amino acids in the HACS motif were preferentially selected over those with three to four basic amino acids, leading to rapid replacement with virus types containing extended HACS motifs. Conversely, viruses harbouring low pathogenicity motifs containing two basic amino acids did not readily evolve to extended forms, suggesting that a single insertion of a basic amino acid into the cleavage site motif of low-pathogenic viruses may lead to escalating selection for extended motifs. Our results may explain why mid-length forms are rarely detected in nature. The stability of the short motif suggests that pathogenicity switching may require specific conditions of intense selection pressure (such as with high host density) to boost selection of the initial mid-length HACS forms

GDF15 promotes weight loss by enhancing energy expenditure in muscle

Funding Information: We thank R. Seeley for sharing GFRAL-null mice; B. Lowell for sharing β-less mice; and J. Wu for shipping β-less mice to us. G.R.S. was supported by a Diabetes Canada Investigator Award (DI-5-17-5302-GS), a Canadian Institutes of Health Research Foundation Grant (201709FDN-CEBA-116200), a Tier 1 Canada Research Chair in Metabolic Diseases and a J. Bruce Duncan Endowed Chair in Metabolic Diseases; D.W. by Fellowship Grants from the McMaster Institute for Research on Aging (MIRA) at McMaster University; S.R. by a postdoctoral fellowship supported by MITACS and Novo Nordisk; L.K.T. by a CIHR Post-Doctoral Fellowship Award and Michael DeGroote Fellowship Award in Basic Biomedical Science; E.M.D. by a Vanier Canada Graduate Scholarship; G.P.H. by the Natural Sciences and Engineering Research Council of Canada (NSERC: 400362); G.J.D. and S.M.F. by NSERC-CGSM scholarships; L.D. by the Fonds de Recherche du Québec-Santé doctoral training award; D.P.B. by the GSK Chair in Diabetes of Université de Sherbrooke and a FRQS J1 salary award. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by the NCI, NHGRI, NHLBI, NIDA, NIMH and NINDS. Funding Information: S.B.J. and R.E.K. are employees of Novo Nordisk, a pharmaceutical company producing and selling medicine for the treatment of diabetes and obesity. G.R.S. is a co-founder and shareholder of Espervita Therapeutics. McMaster University has received funding from Espervita Therapeutics, Esperion Therapeutics, Poxel Pharmaceuticals and Nestle for research conducted in the laboratory of G.R.S. S.R. is supported by a MITACS postdoctoral fellowship sponsored by Novo Nordisk. H.C.G. holds the McMaster-Sanofi Population Health Institute Chair in Diabetes Research and Care. G.R.S., G.P. and H.C.G. are inventors listed on a patent for identifying GDF15 as a biomarker for metformin. G.R.S. has received consulting/speaking fees from Astra Zeneca, Eli Lilly, Esperion Therapeutics, Merck, Poxel Pharmaceuticals and Cambrian Biosciences. The other authors declare no competing interests. Publisher Copyright: © 2023, The Author(s).Peer reviewedPublisher PD