A Bayesian network to predict coastal vulnerability to sea level rise

This paper is not subject to U.S. copyright. The definitive version was published in Journal of Geophysical Research 116 (2011): F02009, doi:10.1029/2010JF001891.Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments of prediction uncertainty. A BN is used to define relationships between driving forces, geologic constraints, and coastal response for the U.S. Atlantic coast that include observations of local rates of relative sea level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline change rate. The BN is used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates. Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. Where more specific information is included, the probability of shoreline change increases in a number of cases, indicating more confident predictions. A hindcast evaluation of the BN indicates that the network correctly predicts 71% of the cases. Evaluation of the results using Brier skill and log likelihood ratio scores indicates that the network provides shoreline change predictions that are better than the prior probability. Shoreline change outcomes indicating stability (−1 1 m/yr) was not well predicted. We find that BNs can assimilate important factors contributing to coastal change in response to sea level rise and can make quantitative, probabilistic predictions that can be applied to coastal management decisions.Funding for this work was provided by the USGS Coastal and Marine Geology and Global Change Research programs

Formulation Pre-screening of Inhalation Powders Using Computational Atom–Atom Systematic Search Method

The synthonic modeling approach provides a molecule-centered understanding of the surface properties of crystals. It has been applied extensively to understand crystallization processes. This study aimed to investigate the functional relevance of synthonic modeling to the formulation of inhalation powders by assessing cohesivity of three active pharmaceutical ingredients (APIs, fluticasone propionate (FP), budesonide (Bud), and salbutamol base (SB)) and the commonly used excipient, α-lactose monohydrate (LMH). It is found that FP (−11.5 kcal/mol) has a higher cohesive strength than Bud (−9.9 kcal/mol) or SB (−7.8 kcal/mol). The prediction correlated directly to cohesive strength measurements using laser diffraction, where the airflow pressure required for complete dispersion (CPP) was 3.5, 2.0, and 1.0 bar for FP, Bud, and SB, respectively. The highest cohesive strength was predicted for LMH (−15.9 kcal/mol), which did not correlate with the CPP value of 2.0 bar (i.e., ranking lower than FP). High FP–LMH adhesive forces (−11.7 kcal/mol) were predicted. However, aerosolization studies revealed that the FP–LMH blends consisted of agglomerated FP particles with a large median diameter (∼4–5 μm) that were not disrupted by LMH. Modeling of the crystal and surface chemistry of LMH identified high electrostatic and H-bond components of its cohesive energy due to the presence of water and hydroxyl groups in lactose, unlike the APIs. A direct comparison of the predicted and measured cohesive balance of LMH with APIs will require a more in-depth understanding of highly hydrogen-bonded systems with respect to the synthonic engineering modeling tool, as well as the influence of agglomerate structure on surface–surface contact geometry. Overall, this research has demonstrated the possible application and relevance of synthonic engineering tools for rapid pre-screening in drug formulation and design

A multicentre, randomised controlled trial to compare the clinical and cost-effectiveness of Lee Silverman Voice Treatment versus standard NHS Speech and Language Therapy versus control in Parkinson’s disease: a study protocol for a randomised controlled trial

Abstract: Background: Parkinson’s disease (PD) affects approximately 145,519 people in the UK. Speech impairments are common with a reported prevalence of 68%, which increase physical and mental demands during conversation, reliance on family and/or carers, and the likelihood of social withdrawal reducing quality of life. In the UK, two approaches to Speech and Language Therapy (SLT) intervention are commonly available: National Health Service (NHS) SLT or Lee Silverman Voice Treatment (LSVT LOUD®). NHS SLT is tailored to the individuals’ needs per local practice typically consisting of six to eight weekly sessions; LSVT LOUD® comprises 16 sessions of individual treatment with home-based practice over 4 weeks. The evidence-base for their effectiveness is inconclusive. Methods/design: PD COMM is a phase III, multicentre, three-arm, unblinded, randomised controlled trial. Five hundred and forty-six people with idiopathic PD, reporting speech or voice problems will be enrolled. We will exclude those with a diagnosis of dementia, laryngeal pathology or those who have received SLT for speech problems in the previous 2 years. Following informed consent and completion of baseline assessments, participants will be randomised in a 1:1:1 ratio to no-intervention control, NHS SLT or LSVT LOUD® via a central computer-generated programme, using a minimisation procedure with a random element, to ensure allocation concealment. Participants randomised to the intervention groups will start treatment within 4 (NHS SLT) or 7 (LSVT LOUD®) weeks of randomisation. Primary outcome: Voice Handicap Index (VHI) total score at 3 months. Secondary outcomes include: VHI subscales, Parkinson’s Disease Questionnaire-39; Questionnaire on Acquired Speech Disorders; EuroQol-5D-5 L; ICECAP-O; resource utilisation; adverse events and carer quality of life. Mixed-methods process and health economic evaluations will take place alongside the trial. Assessments will be completed before randomisation and at 3, 6 and 12 months after randomisation. The trial started in December 2015 and will run for 77 months. Recruitment will take place in approximately 42 sites around the UK. Discussion: The trial will test the hypothesis that SLT is effective for the treatment of speech or voice problems in people with PD compared to no SLT. It will further test whether NHS SLT or LSVT LOUD® provide greater benefit and determine the cost-effectiveness of both interventions. Trial registration: International Standard Randomised Controlled Trials Number (ISRCTN) Registry, ID: 12421382. Registered on 18 April 2016

A multicentre, randomised controlled trial to compare the clinical and cost-effectiveness of Lee Silverman Voice Treatment versus standard NHS Speech and Language Therapy versus control in Parkinson’s disease: a study protocol for a randomised controlled trial

Abstract: Background: Parkinson’s disease (PD) affects approximately 145,519 people in the UK. Speech impairments are common with a reported prevalence of 68%, which increase physical and mental demands during conversation, reliance on family and/or carers, and the likelihood of social withdrawal reducing quality of life. In the UK, two approaches to Speech and Language Therapy (SLT) intervention are commonly available: National Health Service (NHS) SLT or Lee Silverman Voice Treatment (LSVT LOUD®). NHS SLT is tailored to the individuals’ needs per local practice typically consisting of six to eight weekly sessions; LSVT LOUD® comprises 16 sessions of individual treatment with home-based practice over 4 weeks. The evidence-base for their effectiveness is inconclusive. Methods/design: PD COMM is a phase III, multicentre, three-arm, unblinded, randomised controlled trial. Five hundred and forty-six people with idiopathic PD, reporting speech or voice problems will be enrolled. We will exclude those with a diagnosis of dementia, laryngeal pathology or those who have received SLT for speech problems in the previous 2 years. Following informed consent and completion of baseline assessments, participants will be randomised in a 1:1:1 ratio to no-intervention control, NHS SLT or LSVT LOUD® via a central computer-generated programme, using a minimisation procedure with a random element, to ensure allocation concealment. Participants randomised to the intervention groups will start treatment within 4 (NHS SLT) or 7 (LSVT LOUD®) weeks of randomisation. Primary outcome: Voice Handicap Index (VHI) total score at 3 months. Secondary outcomes include: VHI subscales, Parkinson’s Disease Questionnaire-39; Questionnaire on Acquired Speech Disorders; EuroQol-5D-5 L; ICECAP-O; resource utilisation; adverse events and carer quality of life. Mixed-methods process and health economic evaluations will take place alongside the trial. Assessments will be completed before randomisation and at 3, 6 and 12 months after randomisation. The trial started in December 2015 and will run for 77 months. Recruitment will take place in approximately 42 sites around the UK. Discussion: The trial will test the hypothesis that SLT is effective for the treatment of speech or voice problems in people with PD compared to no SLT. It will further test whether NHS SLT or LSVT LOUD® provide greater benefit and determine the cost-effectiveness of both interventions. Trial registration: International Standard Randomised Controlled Trials Number (ISRCTN) Registry, ID: 12421382. Registered on 18 April 2016

Business Research Methods a Managerial Approach

274.;x.;25 c