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Recovery housing provides substance-free living environments that use peer-support to empower individuals in recovery from substance use disorder. This study estimated the total revenue of the recovery housing industry from recovery houses, nationwide.Using survey data collected in June and July of 2020, we calculate the total revenue of the recovery housing industry and determine the share of revenue that comes from different sources for rural and nonrural houses.We find that individual recovery houses operate with an annual revenue of $250,000 and the whole industry accounts for $4.5 billion annually. COVID-19 has reduced industry revenue by 4%. Rural and nonrural houses differ significantly in their sources of revenue.Our results suggest that COVID-19 reduced the size of the recovery housing industry. Houses in nonrural regions may need more federal support due to the relatively high reliance on resident fees, which may be unreliable during COVID-19.

William Robin Thompson was born on 29 June 1887 in London, Ontario, Canada. He was the only child of William Thompson, schoolmaster and journalist of Derwent, Ontario, and of Alice (Morgan) Thompson of London, Ontario. His mother died within a fortnight of his birth. Thompson was descended on his father’s side from a pioneer Canadian family which migrated from Ulster, Ireland, in 1817 when his great grandfather Arthur and his brother Richard sold their land interests. This family can be traced through maps and deeds to Thomas Thompson (deceased 1717) of Ardunsheen Townland. Arthur Thompson’s son became Sir William John Thompson and was one of the pioneers in the fight against tuberculosis in Ireland. W. R. Thompson’s father, after a period as headmaster of a school, became the first editor of the (London) daily,The Advertiser, and finally editor-in-chief of the agricultural weekly,The Farmer's Advocate. W. R. Thompson’s great uncle, Thomas O’Hara, was a Moravian missionary in Labrador in the late 1860s.

Introduction Alzheimer’s disease (AD) is a chronic and progressive neurodegenerative disease that places a substantial burden on patients and caregivers. Aducanumab is the first AD therapy approved by the US Food and Drug Administration to reduce a defining pathophysiological feature of the disease, brain amyloid plaques. In the phase 3 clinical trial EMERGE (NCT02484547), aducanumab reduced clinical decline in patients with mild cognitive impairment (MCI) due to AD and mild AD dementia and confirmed amyloid pathology. Methods We used a Markov modeling approach to predict the long-term clinical benefits of aducanumab for patients with early AD based on EMERGE efficacy data. In the model, patients could transition between AD severity levels (MCI due to AD; mild, moderate, and severe AD dementia) and care settings (community vs. institution) or transition to death. The intervention was aducanumab added to standard of care (SOC), and the comparator was SOC alone. Data sources for base-case and scenario analyses included EMERGE, published National Alzheimer’s Coordinating Center analyses, and other published literature. Results Per patient over a lifetime horizon, aducanumab treatment corresponded to 0.65 incremental patient quality-adjusted life-years (QALYs) and 0.09 fewer caregiver QALYs lost compared with patients treated with SOC. Aducanumab treatment translated to a lower lifetime probability of transitioning to AD dementia, a lower lifetime probability of transitioning to institutionalization (25.2% vs. 29.4%), delays in the median time to transition to AD dementia (7.50 vs. 4.92 years from MCI to moderate AD dementia or worse), and an incremental median time in the community of 1.32 years compared with SOC. Conclusion The model predicted long-term benefits of aducanumab treatment in patients with MCI due to AD and mild AD dementia and their caregivers. The predicted outcomes provide a foundation for healthcare decision-makers and policymakers to understand the potential clinical and socioeconomic value of aducanumab. Supplementary Information The online version contains supplementary material available at 10.1007/s40120-021-00273-0.

Infectious diseases of plants present an ongoing and increasing threat to international biosecurity, with wide-ranging implications. An important challenge in plant disease management is achieving early detection of invading pathogens in new locations, which requires effective surveillance through the implementation of appropriate monitoring programs. However, when monitoring relies on visual inspection as a means of detection, surveillance is often hindered by a long incubation period (delay from infection to symptom onset) during which plants may be infectious but not displaying visible symptoms. ‘Sentinel’ plants – alternative susceptible host species that display visible symptoms of infection more rapidly – could be introduced to at-risk populations and included in monitoring programs to act as early warning beacons for infection. However, while sentinel hosts exhibit faster disease progression and so allow pathogens to be detected earlier, this often comes at a cost: faster disease progression typically promotes earlier onward transmission. Here, we construct a computational model of pathogen transmission to explore this trade-off and investigate how including sentinel plants in monitoring programmes could facilitate earlier detection of invasive plant pathogens. Using Xylella fastidiosa infection in Olea europaea (European olive) as a current high profile case study, for which Catharanthus roseus (Madagascan periwinkle) is a candidate sentinel host, we apply a Bayesian optimisation algorithm to determine the optimal number of sentinel hosts to introduce for a given sampling effort, as well as the optimal division of limited surveillance resources between crop and sentinel plants. Our results demonstrate that including sentinel plants in monitoring programmes can reduce the expected prevalence of infection upon outbreak detection substantially, increasing the feasibility of local outbreak containment.

Although new cases of monkeypox have been expected in the Western Pacific Region (WPR) since the virus emerged in Europe earlier this year, there have been only a few reported cases across the WPR (New Zealand 2, Singapore 6, South Korea 1, Taiwan 2), other than a limited number of cases (compared to numbers of cases seen elsewhere in the world) in Australia (33), as of July 15, 2022. In our short communication, we highlight two key reasons for this: i) international travel has still not fully resumed in the WPR following the COVID-19 pandemic, and ii) local public health measures to counter the spread of COVID-19 have not been completely relaxed. We provide supporting evidence for both of these reasons.\ud \ud

Defeating peripheral neuropathy The mechanisms underlying peripheral neuropathies are not well understood. Spaulding et al . studied mouse models of the inherited Charcot-Marie-Tooth (CMT) disease, which is caused by mutations in transfer RNA (tRNA) synthetases. Changes in gene expression and the rate of protein synthesis in neurons in the spinal cord triggered the cell stress response activated by the protein sensor GCN2. When GCN2 was genetically deleted or inhibited with drugs, the stress response was blocked, and the neuropathy was much milder. Zuko et al . found that mutant glycyl-tRNA synthetases bind tRNA Gly but fail to release it, thus depleting the cellular tRNA Gly pool. This process caused stalling of translating ribosomes on glycine codons and activated the integrated stress response. Transgenic tRNA Gly overexpression prevented peripheral neuropathy and protein synthesis defects in mouse and fruit fly models. Thus, elevating tRNA Gly levels or targeting GCN2 may have therapeutic potential for this currently untreatable disease (see the Perspective by Mellado and Willis). —SMH

Purpose With the impending changes to state Medicaid programs and other health reform policies, it is imperative to understand the factors at play in promoting consumer health insurance literacy and health system engagement. This study examines the availability of health system and community‐based programs promoting health insurance literacy and supporting informed consumer health care decision making in rural communities in Kentucky. Methods Forty‐six health systems, community‐based providers, and outreach workers participated in 4 focus groups and 10 semistructured interviews. Descriptive and analytic coding techniques were used to identify 5 major themes and subthemes from interview and focus group transcripts. Findings Consumers were generally identified as having low health insurance literacy, especially in rural communities, serving as a barrier to accessing health care insurance and services. Participants identified their own lack of knowledge and understanding around health systems, resulting from lack of training and challenges with staying updated on constant changes in health systems and policies. Overall, consumer demand or need for health insurance literacy resources and programs far exceeded supply or availability. Constant changes in the status of Kentucky's Medicaid program and the proposed changes to eligibility, specifically work requirements and copays, have caused increased confusion among both providers and consumers. Conclusions Findings indicate a pressing need for implementing programs that provide training, tools, and resources to outreach workers to help them better assist consumers with accessing and using health insurance, especially in low‐income, rural areas. Health reform policies need to be responsive to the health insurance literacy needs and abilities of consumers.

During the COVID-19 pandemic, mathematical modeling of disease transmission has become a cornerstone of key state decisions. To advance the state-of-the-art host viral modeling to handle future pandemics, many scientists working on related issues assembled to discuss the topics. These discussions exposed the reproducibility crisis that leads to inability to reuse and integrate models. This document summarizes these discussions, presents difficulties, and mentions existing efforts towards future solutions that will allow future model utility and integration. We argue that without addressing these challenges, scientists will have diminished ability to build, disseminate, and implement high-impact multi-scale modeling that is needed to understand the health crises we face.

The reproductive number is an important metric that has been widely used to quantify the infectiousness of communicable diseases. The time-varying instantaneous reproductive number is useful for monitoring the real time dynamics of a disease to inform policy making for disease control. Local estimation of this metric, for instance at a county or city level, allows for more targeted interventions to curb transmission. However, simultaneous estimation of local reproductive numbers must account for potential sources of heterogeneity in these time-varying quantities – a key element of which is human mobility. We develop a statistical method that incorporates human mobility between multiple regions for estimating region-specific instantaneous reproductive numbers. The model also can account for exogenous cases imported from outside of the regions of interest. We propose two approaches to estimate the reproductive numbers, with mobility data used to adjust incidence in the first approach and to inform a formal priori distribution in the second (Bayesian) approach. Through a simulation study, we show that region-specific reproductive numbers can be well estimated if human mobility is reasonably well approximated by available data. We use this approach to estimate the instantaneous reproductive numbers of COVID-19 for 14 counties in Massachusetts using CDC case report data and the human mobility data collected by SafeGraph. We found that, accounting for mobility, our method produces estimates of reproductive numbers that are distinct across counties. In contrast, independent estimation of county-level reproductive numbers tends to produce similar values, as trends in county case-counts for the state are fairly concordant. These approaches can also be used to estimate any heterogeneity in transmission, for instance, age-dependent instantaneous reproductive number estimates. As people are more mobile and interact frequently in ways that permit transmission, it is important to account for this in the estimation of the reproductive number.Author summaryTo control the spreading of an infectious disease, it is very important to understand the real-time infectiousness of the pathogen that causes the disease. An existing metric called instantaneous reproductive number is often used to quantify the average number of secondary cases generated by individuals who are infectious at a certain time point, assuming no changes to current conditions. In practice, we might be interested in using the metric to describe the infectiousness in multiple regions. However, this is challenging when there are visitors traveling between these regions, since this could lead to a misclassification of where an individual is actually infected and create biased estimates for the instantaneous reproductive numbers. We developed a method that takes account of human mobility to estimate the instantaneous reproductive numbers for multiple regions simultaneously, which could reveal the heterogeneity of the metric. This method aims to provide helpful information on region-specific infectiousness for disease control measures that focus on the region with higher pathogen infectiousness. This approach is also applicable for estimating the reproductive number in the presence of other sources of heterogeneity, including by age.

Background Spinal muscular atrophy (SMA) is a rare, genetic, progressive neuromuscular disorder characterized by severe muscle atrophy and weakness and is a leading genetic cause of death in infants and children. Nusinersen was the first treatment targeting the underlying cause of disease approved by the FDA, EMA and other countries for patients with SMA. There are currently very limited data available on the health-related quality of life (HRQoL) burden of SMA suitable for use in a cost-effectiveness analysis. Objective This study was designed to estimate quality of life weights or utilities for different SMA states. Methods SMA case studies were developed describing Type I (infantile onset) and Type II (later-onset) patients and different outcomes from treatment. These were developed so that quality of life weights or utilities (where the value of health ranges from 1 - full health to 0 - dead) could be estimated for cost-effectiveness analysis. Clinical experts (n=5) rated each of the case studies using standardized HRQoL instruments - the EQ-5D-Y and PedsQL-NMM (baseline states only). Results The SMA Type I utilities ranged from -0.33 (requires ventilation) to 0.71 (Type I patient reclassified as Type III following treatment), with quite substantial differences between some states. Most Type I states had a utility score below zero indicating the severity of the states. The SMA Type II utilities ranged from -0.13 (worsened) to 0.72 (stands/walks unaided). In general, the results showed HRQoL improved in line with better health states. Conclusion The utility scores obtained in this study highlight the very substantial burden experienced by SMA patients. Despite the limitations in the methods used, this study produced data with face validity and is a useful starting point for understanding the burden of SMA Types I and II in cost-effectiveness analysis.

We address the use of accelerometery to automatically monitor lying behaviour in free-farrowing sows; due to their freedom of movement and the consequent increased variety of movements the sows are able to exhibit, the challenges in automating this are greater than in sows housed in movement restricting farrowing environments. The methodology developed was applied to two salient applications: that of farrowing prediction through detection of nest building activity, and comparison of maternal lying behaviour in conventional movement-restricting and free-farrowing systems. Two sensors were attached at both the front and hind end to each of eight periparturient sows. Movement behaviour was recorded for a period of five days around parturition. Activity transitions were classified by a Support Vector Machine classifier, using data from both sensors individually, and combined; classifier output was validated against ground truth annotations collected from video data. We draw conclusions about the benefits of using multiple sensors over a single sensor, as well as the suitability of different sensor locations on the sow. Activity classification was found to improve through the use of multiple sensors, with a mean F 1 score (a measure of predictive performance between 0 and 1) of 0.84, compared to use of the front sensor alone (mean F 1 = 0.49) and the hind sensor alone (mean F 1 = 0.57). Activity transitions were classified using the dual sensor setup with a mean F 1 score of 0.77. Using a threshold-based approach, taking transition frequency as an indicator of nesting behaviour, we were able to detect the onset of nest building with an average latency to farrowing of 11.1 (±4.65) hours, and an average of 1 premature detection per sow; however, the majority of these premature were in a particular sow. We draw comparisons between the lying behaviour of free-farrowing and restricted sows. Using a mixed-design ANOVA we found a main effect of farrowing environment on transition duration ( p = 0.003 ), peak acceleration ( p = 0.007 ) and rate of change in pitch ( p = 0.009 ) . Improving the classification accuracy of sow activity transitions through the addition of multiple sensors allows for improved performance in applications such as farrowing prediction, which has the capacity to reduce piglet mortality through enabling farrowing supervision. Understanding how movement restriction affects the lying behaviour of farrowing sows has the potential to inform decisions regarding restriction of sows and development of free-farrowing environments.

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting millions of people worldwide and imposing heavy economic burdens to societies. Currently, only symptomatic treatments are available for patients, but there is ongoing research on potential therapies that can modify the course of disease. The main objective of this work is to identify and explore the challenges surrounding decision modeling for economic evaluation of interventions for AD.This article discusses the challenges in modeling the natural history of disease, particularly regarding the selection of disease progression and outcome measures, the inclusion of biomarker status in models, and the approach to model mortality. Challenges stemming from the use of long-term assumptions regarding treatment effects and the need for real-world evidence to fill data gaps are discussed. Lastly, the overwhelming economic impact of disease and the challenges in estimating these costs for modeling are addressed.Value assessment frameworks need to be reconsidered in order to demonstrate the full benefit of new disease-modifying therapies spanning beyond the scope of health systems. Data collection efforts that expand the evidence base, upon which economic models are based, will reduce the uncertainties surrounding the long-term outcomes of interventions in AD.

Transfer RNAs (tRNAs) are highly abundant species and, along their biosynthetic and functional path, they establish interactions with a plethora of proteins. The high number of nucleobase modifications in tRNAs renders conventional RNA quantification approaches unsuitable to study protein-tRNA interactions and their associated functional roles in the cell. We present an immunoprecipitation-based approach to quantify tRNA bound to its interacting protein partner(s). The tRNA-protein complexes are immunoprecipitated from cells or tissues and tRNAs are identified by northern blot and quantified by tRNA-specific fluorescent labeling. The tRNA interacting protein is quantified by an automated western blot and the tRNA amount is presented per unit of the interacting protein. We tested the approach to quantify tRNA(Gly) associated with mutant glycyl-tRNA-synthetase implicated in Charcot-Marie-Tooth disease. This simple and versatile protocol can be easily adapted to any other tRNA binding proteins. Graphic abstract: [Image: see text]

This article explores Jesus' healing of the disabled man at the Pool of Bethesda. This healing is only reported in the Gospel of John, and the location of the healing is described in some detail. After addressing the textual and archaeological challenges in locating the Pool of Bethesda, this article discusses both the tradition of healing associated with this site and the well-known Greco-Roman god of healing, Asclepius. While this healing may serve more than one purpose in John's Gospel, I propose that the location of the healing serves as a challenge to the Gentiles in John's audience: Jesus was more than a god who could heal—he was a God who could provide eternal life.

This paper presents a novel approach to biomass variability assessment within a crop field, and to zone management in Precision Agriculture. The k-means clustering and the fuzzy c-means clustering algorithms are used to create homogeneous management zones in a crop field based on within-field biomass variation, acquired from multispectral data and processed using a vegetation index. To test the accuracy of the delineation of management zones, the segmented maps are compared against an application plan based on approved agricultural models and expert knowledge used as a reference. It is shown that the k-means clustering algorithm is a viable approach to highlighting biomass variability and defining management zones. The proposed zoning functionality is aimed to be added as an extra module to an existing Fertiliser Assessment tool in a plug-and-play principle to enhance its functionality.

Aims: To facilitate regulatory learning, we evaluated similarities and differences in evidence requirements between regulatory and health technology assessment (HTA) bodies of Alzheimer’s disease (AD) approved products. Methods: The European marketing authorisation application dossiers and European public assessment reports (EPARs) of the licensed AD drugs were screened to identify the phase III randomised controlled trials (RCTs) and outcomes used. We also screened the assessment reports of the National Institute of Health and Care Excellence (NICE, England) and the National Health Care Institute (ZiN, the Netherlands) to identify the studies and outcomes used in HTA assessments. Results: The applications dossiers of donepezil, galantamine, rivastigmine, and memantine contained 16 phase III RCTs in total. These trials were also included in HTA assessments except that NICE excluded studies that were not published (n=2) or trials that included patients with other types of dementia (n=3). In the regulatory assessments the focus was on cognitive and global outcomes, and to some extent on function. In the HTA assessment of the clinical effectiveness other domains were also covered including: function, behaviour and mood, and, occasionally, quality of life. In the economic analyses of NICE the domains cognition, function, and quality of life were included. Conclusion: There was a large overlap in inclusion of trials in regulatory and HTA assessments, although the focus on specific outcomes slightly differed. Understanding the methods and perceptions of both authorities can stimulate regulatory and HTA cross-talk and further alignment, and therefore more rapid patient access to new treatments.

Tracheal intubation is common in the care of critically ill adults and is frequently complicated by hypotension, cardiac arrest, or death. We aimed to evaluate administration of an intravenous fluid bolus to prevent cardiovascular collapse during intubation of critically ill adults.We did a pragmatic, multicentre, unblinded, randomised trial in nine sites (eight ICUs and one emergency department) around the USA. Critically ill adults (≥18 years) undergoing tracheal intubation were randomly assigned (1:1, block sizes of 2, 4, and 6, stratified by study site) to either an intravenous infusion of 500 mL of crystalloid solution or no fluid bolus. The primary outcome, assessed in the intention-to-treat population, was cardiovascular collapse, defined as a new systolic blood pressure65 mm Hg; new or increased vasopressor receipt between induction and 2 min after tracheal intubation; or cardiac arrest or death within 1 h of tracheal intubation. Adverse events were assessed in the as-treated population. This trial, which is now complete, is registered with ClinicalTrials.gov, number NCT03026777.Patients were enrolled from Feb 6, 2017, to Jan 9, 2018, when the data and safety monitoring board stopped the trial on the basis of futility. By trial termination, 337 (63%) of 537 screened adults had been randomly assigned. Cardiovascular collapse occurred in 33 (20%) of 168 patients in the fluid bolus group compared with 31 (18%) of 169 patients in the no fluid bolus group (absolute difference 1·3% [95% CI -7·1% to 9·7%]; p=0·76). The individual components of the cardiovascular collapse composite outcome did not differ between groups (new systolic blood pressure65 mm Hg 11 [7%] in the bolus group vs ten [6%] in the no-bolus group, new or increased vasopressor 32 [19%] vs 31 [18%], cardiac arrest within 1 h seven [4%] vs two [1%], death within 1 h of intubation two [1%] vs one [1%]). In-hospital mortality was not significantly different in the fluid bolus group (48 [29%]) compared with no fluid bolus (59 [35%]).Administration of an intravenous fluid bolus did not decrease the overall incidence of cardiovascular collapse during tracheal intubation of critically ill adults compared with no fluid bolus in this trial.US National Institutes of Health.

Spinal muscular atrophy is a rare neuromuscular disorder with a spectrum of severity related to age at onset and the number of SMN2 gene copies. Infantile-onset (≤ 6 months of age) is the most severe spinal muscular atrophy and is the leading monogenetic cause of infant mortality; patients with later-onset (> 6 months of age) spinal muscular atrophy can survive into adulthood. Nusinersen is a new treatment for spinal muscular atrophy. The objective of this study was to evaluate the cost effectiveness of nusinersen for the treatment of patients with infantile-onset spinal muscular atrophy and later-onset spinal muscular atrophy in Sweden. One Markov cohort health-state transition model was developed for each population. The infantile-onset and later-onset models were based on the efficacy results from the ENDEAR phase III trial and the CHERISH phase III trial, respectively. The cost effectiveness of nusinersen in both models was compared with standard of care in Sweden. For a time horizon of 40 years in the infantile-onset model and 80 years in the later-onset model, treatment with nusinersen resulted in 3.86 and 9.54 patient incremental quality-adjusted life-years and 0.02 and 2.39 caregiver incremental quality-adjusted life-years and an incremental cost of 21.9 and 38.0 million SEK (Swedish krona), respectively. These results translated into incremental cost-effectiveness ratios (including caregiver quality-adjusted life-years) of 5.64 million SEK (€551,300) and 3.19 million SEK (€311,800) per quality-adjusted life-year gained in the infantile-onset model and later-onset model, respectively. Treatment with nusinersen resulted in overall survival and quality-adjusted life-year benefits but with incremental costs above 21 million SEK (€2 million) [mainly associated with maintenance treatment with nusinersen over a patient’s lifespan]. Nusinersen was not cost effective when using a willingness-to-pay threshold of 2 million SEK (€195,600), which has been considered in a recent discussion by the Dental and Pharmaceutical Benefits Agency as a reasonable threshold for rare disease. Nonetheless, nusinersen gained reimbursement in Sweden in 2017 for paediatric patients (below 18 years old) with spinal muscular atrophy type I–IIIa.

Field trials for variety selection often exhibit spatial correlation between plots. When multivariate data are analysed from these field trials, there is the added complication in having to simultaneously account for correlation between the traits at both the residual and genetic levels. This may be temporal correlation in the case of multi-harvest data from perennial crop field trials, or between-trait correlation in multi-trait data sets. Use of parsimonious yet plausible models for the variance–covariance structure of the residuals for such data is a key element to achieving an efficient and inferentially sound analysis. In this paper, a model is developed for the residual variance–covariance structure firstly by considering a multivariate autoregressive model in one spatial direction and then extending this to two spatial directions. Conditions for ensuring that the processes are directionally invariant are presented. Using a canonical decomposition, these directionally invariant processes can be transformed into a set of independent separable processes. This simplifies the estimation process. The new model allows for flexible modelling of the spatial and multivariate interaction and allows for different spatial correlation parameters for each harvest or trait. The methods are illustrated using data from lucerne breeding trials at several environments.

Objective The purpose of this study was to assess the feasibility and effectiveness of live telemedicine applications in hearing amplification and cochlear implantation. Data sources and study selection A systematic search was performed in PubMed, MEDLINE, PsychINFO, CINALH, and Web of Science to identify peer-reviewed research. Inclusion criteria were titles containing words from the search terms 1) audiology, otolaryngology, and hearing impairment, 2) rehabilitative methods, and 3) telemedicine. Exclusion criteria were: 1) non-English articles, and 2) non-original research. Data extraction and synthesis Twelve eligible studies were identified. The studies employed a prospective design in nine of the articles and retrospective case series in three. The use of telemedicine for the provision of cochlear implant services was examined in eight of the articles and with hearing aids in four of the articles. The types of services include intraoperative cochlear implant telemetry; implant programming and assessment of electrode-specific measures and speech recognition after implantation. Hearing aid programming and remote gain assessments were also reported. Many studies assess patient and provider satisfaction along with encounter time comparison. The studies occurred from 2009 to 2014 and took place in seven countries. Conclusions This review examined the feasibility of remote telemedicine connection to provide in auditory rehabilitation services through hearing aids and cochlear implants. There are significant concerns regarding Internet bandwidth limitations for remote clinics. There is a paucity of research examining reimbursement and cost-effectiveness for services. Further prospective research investigating cost-effectiveness and bandwidth limitations is warranted to assess long-term sustainability of remote audiological rehabilitative service delivery.

Human activity recognition (HAR), i.e., the automated detection and classification of specific activities that a person pursues, is one of the core concerns of mobile and ubiquitous computing. Multimodal sensing facilities of modern mobile devices allow for detailed capture of contextual information, most importantly movement data recorded with inertial measurement units that are now standard in most mobile devices. The majority of HAR applications aim at automatically documenting when something of interest has happened and what that was. For example, the popular moves app on iOS and Android devices "automatically records any walking, cycling, and running [a user does]" [7] and as such automatically generates a life log for those interested in their daily movement patterns. Beyond the mere recognition of certain activities of interest, few applications currently go a step further and analyze the quality of a person's activities, i.e., how (well) their activities were performed, which directly corresponds to a person's abilities or skills .

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers.

I review my scientific career in terms of eight areas and 16 papers. The first two areas are associated with childhood. The other six are associated with residual maximum likelihood (REML), canonical transformation, inbreeding in selected populations, average information residual maximum likelihood (AIREML), the computer program ASReml and sampling-based estimation.

Vaccination is an important tool for decreasing the spread and disease burden of the widespread bacterial pathogen Streptococcus pneumoniae. However, current vaccines target only a subset of pneumococcal serotypes, and the nonvaccine types often remain at high frequencies after vaccination. In some cases, nonvaccine types display a disconcerting increase in antibiotic resistance frequencies after a population has been vaccinated by the commonly used PCV7 or PCV13, and the reason for this is unclear. Using mathematical modeling, we show that removal of competition with the vaccine types may induce this rise in antibiotic resistance. Our model explores the conditions leading to such an increase and contributes to a better understanding of this process.

Veterinarians and pet owners have limited ability to assess pruritic behaviors in dogs. This pilot study assessed the capacity of the Vetrax® triaxial accelerometer to measure these behaviors in six dogs with pruritus likely due to environmental allergens. Dogs wore the activity monitor for two weeks while consuming their usual pet food (baseline), then for eight weeks while consuming a veterinary-exclusive pet food for dogs with suspected non-food-related skin conditions (Hill’s Prescription Diet® Derm DefenseTM Canine dry food). Veterinarians and owners completed questionnaires during baseline, phase 1 (days 1–28) and phase 2 (days 29–56) without knowledge of the activity data. Continuous 3-axis accelerometer data was processed using proprietary behavior recognition algorithms and analyzed using general linear mixed models with false discovery rate-adjusted p values. Veterinarian-assessed overall clinical signs of pruritus were significantly predicted by scratching (β 0.176, p = 0.008), head shaking (β 0.197, p < 0.001) and sleep quality (β −0.154, p < 0.001), while owner-assessed quality of life was significantly predicted by scratching (β −0.103, p = 0.013) and head shaking (β −0.146, p < 0.001). Among dogs exhibiting pruritus signs eating the veterinary-exclusive food, the Vetrax® sensor provided an objective assessment of clinically relevant pruritic behaviors that agreed with owner and veterinarian reports.

Teenage boys in the first year of secondary school were interviewed about their Kodaly influenced, voice based classroom music course with a view to improving the subject offering in terms of educational efficacy and popularity at the site of the research. Discourse analysis of the interview transcripts revealed that the singing aspect of the course was not as unpopular with the students as some research predicted. Indeed, the boys enjoyed singing and playing instruments. They enjoyed the cognitive challenge of rigorous music education. The discourse analysis revealed that identity creation and friendship building in the first year of secondary schooling was more important to the students than the researcher had expected. Students enjoyed learning music by making music and advocated for more opportunities for paired and small group music making to have more opportunities to make friends, to learn about each other and to negotiate and construct their identities. The course was developed in line with the findings of the initial interviews in an action research framework. The study found that asking students about their learning and interrogating thoroughly what they say can assist in matching pedagogy to student needs. It found that practitioners should adopt a site and child specific, rather than a one size fits all approach when applying pedagogical practices.

Objective/Hypothesis Hearing loss is a public health concern, yet hearing healthcare disparities exist and influence utilization of rehabilitation services. The objective of this review was to systematically analyze the published literature on motivators, barriers, and compliance factors affecting adult patient access and utilization of hearing rehabilitation healthcare. Data Sources Pubmed, PsychINFO, CINAHL, and Web of Science were searched for relevant articles. Eligible studies were those containing original, peer-reviewed research in English pertaining to factors affecting adult hearing healthcare access and utilization of hearing aids and cochlear implantation. The search encompassed 1990 to 2015. Methods Two investigators independently reviewed all articles and extracted data. Specific variables regarding access to care and compliance to recommended care were extracted from each study. Results Thirty articles were reviewed. The factors affecting access and utilization of hearing rehabilitation could be classified into motivators, barriers, and compliance in treatment or device use. The key motivators to seek care include degree of hearing loss, self-efficacy, family support, and self-recognition of hearing loss. The primary barriers to care were financial limitations, stigma of hearing devices, inconvenience, competing chronic health problems, and unrealistic expectations. Compliance is most affected by self-efficacy, education level, and engagement in the rehabilitation process. Conclusion Accessing hearing healthcare is complicated by multiple factors. Considering the current climate in healthcare policy and legislation toward improved access of care, a deeper understanding of motivators, barriers, and compliance factors can aid in delivery of effective and efficient hearing healthcare. Laryngoscope, 2016

Disease resistance is often measured as plant survival, which involves taking multiple counts of plants before and after disease incidence. Often, survival data are analyzed by forming a single derived variable, namely final counts expressed as a percentage of initial counts. In this study we propose a bivariate linear mixed model approach in which the two variables are the initial and final counts. This approach is demonstrated using data from nine blackleg disease nurseries in the 2009 growing season in Australia. Replicated experiments were grown at each nursery with a mixture of commercial Australian canola cultivars and breeding lines (collectively called ‘entries’) being tested. Plant survival was determined by counting all the seedlings at emergence and then recounting the number surviving at maturity in each plot. The counts were considered as two ‘traits’, which were log transformed prior to a bivariate linear mixed model analysis. Each trait had different error variances, spatial components (both local and global) and outliers. The variance of entry effects was non-zero for both traits at all locations. The correlation of entry effects between the traits ranged from 0.218 to 0.935 across locations. Best Linear Unbiased Predictors (BLUPs) of entry effects at both sampling times provided three possible indices for selection: (log) counts at emergence, (log) counts at maturity and the difference between these two which could be exponentiated to provide percentage survival values. Thus the bivariate mixed model approach for the analysis of plant survival data provided a more detailed picture of the impact of disease resistance compared with the univariate analysis of percentage survival data. Additionally the predicted entry effects for survival were more accurate in the bivariate analysis.

The cultural critic and historian Kitazawa Noriaki discusses the origins of the creation of the concept of “Fine Art” in Japan. The term “Bijutsu” was coined in the context of the World Exposition in Vienna in 1873, referring to all the arts, including literature and music. Thereafter, its meaning was gradually reduced to refer specifically to the visual arts. Kitazawa discusses this term and its meaning in relation to cultural influences from the West, Japanese art institutions, governmental policies, and the role of the arts in the formation of a national cultural identity. These policies were part of a governmental agenda and private interests to establish a favorable international position for Japan in both economic and political terms.

Tanaka Jun presents a new, philosophical, and urban-anthropological perspective on Moriyama Daidō’s photographs of Tokyo. The first part of the essay discusses the motif of the city with reference to Walter Benjamin’s theory of arcades and methods of “collective photographic observation” of the city, following the ideas of Akasegawa Genpei, Gotō Noriaki, and Sekine Yasumasa. It is argued that Moriyama Daidō’s series on Tokyo’s Shinjuku district represents the place as one to experience as a “passage.” Tanaka’s analysis of Moriyama’s photography as a form of urban representation will appeal to readers interested in philosophy and aesthetics as well as photography and urban studies.

This essay, first written in Japanese and published in 1939 by the young Japanese architect Tange Kenzō, reflects on the work and creativity of two major figures in Western art. Drawing on the writ...

This essay by the Japanese architect Horiguchi Sutemi, first published in Japanese in 1932, is a critique of the architectural style known as “Japanese taste.” This style, also known as “Imperial Crown Style,” emerged in the late 1920s and ’30s in response to the growth of nationalism in Japan. It was characterized by modern technology and elements from traditional Japanese architecture. Horiguchi is critical of the imitation and recreation of past examples in the name of modern “Japanese taste” architecture, and argues that the style would have to evolve in response to changing functions and developing technology.

Insecticide-resistant clones of the peach-potato aphid, Myzus persicae (Sulzer), have previously been shown to have a reduced response to aphid alarm pheromone compared to susceptible ones. The resulting vulnerability of susceptible and resistant aphids to attack by the primary endoparasitoid, Diaeretiella rapae (McIntosh), was investigated across three spatial scales. These scales ranged from aphids confined on individual leaves exposed to single female parasitoids, to aphids on groups of whole plants exposed to several parasitoids. In all experiments, significantly fewer aphids from insecticide-susceptible clones became parasitised compared to insecticide-resistant aphids. Investigations of aphid movement showed at the largest spatial scale that more susceptible aphids than resistant aphids moved from their inoculation leaves to other leaves on the same plant after exposure to parasitoids. The findings imply that parasitoids, and possibly other natural enemies, can influence the evolution and dynamics of insecticide resistance through pleiotropic effects of resistance genes on important behavioural traits.

A variance shift outlier model (VSOM), previously used for detecting outliers in the linear model, is extended to the variance components model. This VSOM accommodates outliers as observations with inflated variance, with the status of the ith observation as an outlier indicated by the size of the associated shift in the variance. Likelihood ratio and score test statistics are assessed as objective measures for determining whether the ith observation has inflated variance and is therefore an outlier. It is shown that standard asymptotic distributions do not apply to these tests for a VSOM, and a modified distribution is proposed. A parametric bootstrap procedure is proposed to account for multiple testing. The VSOM framework is extended to account for outliers in random effects and is shown to have an advantage over case-deletion approaches. A simulation study is presented to verify the performance of the proposed tests. Challenges associated with computation and extensions of the VSOM to the general linear mixed model with correlated errors are discussed.

The primary aim of crop variety evaluation programs is to reliably predict the performance of potential new varieties relative to existing commercial varieties. This is achieved through multienvironment trials (METs), that is, series of field trials conducted across a range of geographic trial locations and possibly over several years. Usually, a program of METs is established to take varieties through from the initial selection of potential breeding lines (often called early generation variety evaluation trials) to eventual commercial release and recommendation to farmers (late-stage variety evaluation trials). This paper is concerned with METs in the latter stages of this process, although many of our results will also apply to early generation trials. The Australian and UK late-stage variety testing systems were used as the basis of this study. In both cases, a series of trials is set up annually to test a relatively small number (• 100) of candidate varieties, which usually contains a set of standard or control varieties, highlyperforming established varieties and emerging varieties identified from earlier trials. The set of trials within (and across) years is designed to provide a range of growing conditions, and the term environments is used to describe the set of trial conditions. The aim of the statistical analysis is to use an appropriate model to provide reliable predictions of variety performance across target environments. The focus in this paper is on the use of linear mixed models which can be implemented as one-stage or two-stage analyses [1]. In a one-stage analysis individual plot data from all trials is combined in a single analysis. In a two-stage analysis variety means are first obtained from the separate analysis of individual trials (stage I), and are then combined in an overall mixed model analysis (stage II). The stage II analysis may be unweighted or weighted to reflect the relative precision of variety means from each trial. In each case, a linear mixed model may be constructed to describe the structure of the data, and this model is usually fitted using REML estimation. Two sets of trials from Australia and the UK are used to provide realistic scenarios for a simulation study to evaluate the different methods of analysis. This study showed that a one-stage approach gave the most accurate predictions of variety performance overall or within each environment, across a range of models, as measured by mean squared error of prediction or realised genetic gain. A weighted two-stage approach performed adequately for both overall variety predictions and variety predictions within environments. A two-stage unweighted approach performed poorly both for overall variety predictions and for variety predictions at individual environments. The performance of the two-stage methods was related to the change in heritability between the methods.

Udgivelsesdato: November An analysis of litter size and average piglet weight at birth in Landrace and Yorkshire using a standard two-trait mixed model (SMM) and a recursive mixed model (RMM) is presented. The RMM establishes a one-way link from litter size to average piglet weight. It is shown that there is a one-to-one correspondence between the parameters of SMM and RMM and that they generate equivalent likelihoods. As parameterized in this work, the RMM tests for the presence of a recursive relationship between additive genetic values, permanent environmental effects, and specific environmental effects of litter size, on average piglet weight. The equivalent standard mixed model tests whether or not the covariance matrices of the random effects have a diagonal structure. In Landrace, posterior predictive model checking supports a model without any form of recursion or, alternatively, a SMM with diagonal covariance matrices of the three random effects. In Yorkshire, the same criterion favors a model with recursion at the level of specific environmental effects only, or, in terms of the SMM, the association between traits is shown to be exclusively due to an environmental (negative) correlation. It is argued that the choice between a SMM or a RMM should be guided by the availability of software, by ease of interpretation, or by the need to test a particular theory or hypothesis that may best be formulated under one parameterization and not the other