The Empirical Research Law Librarian. Part 1: Making the Case and Filling the Role

Over the course of the last decade, the Reference Department of the Lillian Goldman Law Library at Yale Law School has seen an increase in requests for assistance with data collection and empirical analysis. These requests have become progressively more sophisticated and technical while our patrons have become more knowledgeable and skilled. Until recently, when a student or faculty member expressed interest in gathering data and engaging in empirical research, the reference librarians would guide the researcher to appropriate places, such as the Sourcebook of Criminal Justice Statistics or TracFed or ICPSR data portal, and then send the researcher to the Yale University StatLab\u27 for additional research assistance and support. Alternatively, members of our faculty who were trained and experienced empiricists often hired a team of research assistants capable of working with the data once they had found it

Research Notes : Selection and inheritance of nitrate reductase mutants in soybeans

Our primary objective in looking for nitrate reductase (NR) mutants in soybeans is to attempt to overcome the inhibition of nitrogen fixation by soil nitrate. The rationale depends upon blocking normal nitrate metabolism by finding defective NR mutants, thus liberating additional carbon and ener-gy for use by nodules in nitrogen fixation. Additional benefits likely to result from the isolation of NR mutants in soybeans are a) a better under-standing of normal nitrate metabolism and b) provision of easily selectable genetic markers

Advances in Decentralized Single-Beacon Acoustic Navigation for Underwater Vehicles: Theory and Simulation

This paper reports the theory and implementation of a decentralized navigation system that enables simultaneous single-beacon navigation of multiple underwater vehicles. In single-beacon navigation, each vehicle uses ranges from a single, moving reference beacon in addition to its own inertial navigation sensors to perform absolute localization and navigation. In this implementation the vehicles perform simultaneous communication and navigation using underwater acoustic modems, encoding and decoding data within the acoustic broadcast. Vehicles calculate range from the time of flight of asynchronous acoustic broadcasts from the reference beacon. Synchronous clocks on the reference beacon and the vehicles enable the measurement of one-way travel-times, whereby the time of launch of the acoustic signal at the reference beacon is encoded in the acoustic broadcast and the time of arrival of the broadcast is measured by each vehicle. The decentralized navigation algorithm, running independently on each vehicle, is implemented using the information form of the extended Kalman filter and has been previously shown to yield results that are identical to a centralized Kalman filter at the instant of each range measurement. We summarize herein the architecture and design of the acoustic communications (Acomms) system consisting of an underwater acoustic modem, synchronous clock, and the software necessary to run them, and salient results from the validation of the decentralized information filter using a simulated data set.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86057/1/swebster-4.pd

Environmental and Economic Implications of Alternative Cruise Ship Pathways in Bermuda

As the cruise ship industry moves towards ever larger vessels, many tourist destinations are faced with dilemmas about how to accommodate the latest generation of ships, which require deeper and wider shipping pathways. The location of nearshore shipping channels traveled by cruise ships has important environmental and economic implications, as dredging larger lanes damages habitat, ship traffic produces sediment plumes that can smother adjacent sensitive habitats (e.g., coral reefs, seagrass beds), and dredging costs vary spatially. These environmental and economic costs should ideally be evaluated in the context of projected benefits from increased tourism. To inform decision-making on cruise ship pathway design, we evaluated tradeoffs among tourism revenue to the local economy, dredging costs, direct coral damage and sedimentation impacts to coral reefs of alternative cruise ship approach channels for the island of Bermuda. We compiled economic data on cruise tourism and dredging costs and developed a sediment particle tracking model, overlaid on maps of coral cover, to track the spread of sediment particles and resulting coral sedimentation caused by cruise ships. Using our models we compared two viable routes, if dredged, for larger ships to reach Bermuda, along with a scenario of no dredging in which the next generation of larger ships is not accommodated. Our tradeoff analysis shows that the status quo (no dredging; no larger ships) scenario performs relatively well except for the risk of a significant loss in tourism revenue. When selecting between the two channel upgrade scenarios, the south channel upgrade is preferable if dredged material can be reused, thereby recouping dredging costs; otherwise, there is a strong tradeoff between upgrade costs and coral sedimentation. While developed with data layers and inputs specific to Bermuda, this analytical approach could easily be configured to other locations facing similar spatial planning decisions about whether and where to allow pathways for larger cruise ships

Preliminary Deep Water Results in Single-Beacon One-Way-Travel-Time Acoustic Navigation for Underwater Vehicles

This paper reports the development and experimental evaluation of a novel navigation system for underwater vehicles that employs Doppler sonar, synchronous clocks, and acoustic modems to achieve simultaneous acoustic communication and navigation. The system reported herein, which is employed to renavigate the vehicle in post-processing, forms the basis for a vehicle-based real-time navigation system. Existing high-precision absolute navigation techniques for underwater vehicles are impractical over long length scales and lack scalability for simultaneously navigating multiple vehicles. The navigation method reported in this paper relies on a single moving reference beacon, eliminating the requirement for the underwater vehicle to remain in a bounded navigable area. The use of underwater modems and synchronous clocks enables range measurements based on one-way time-of-flight information from acoustic data packet broadcasts. The acoustic data packets are broadcast from the single, moving reference beacon and can be received simultaneously by multiple vehicles within acoustic range. We report experimental results from the first deep-water evaluation of this method using data collected from an autonomous underwater vehicle (AUV) survey carried out in 4000 m of water on the southern Mid-Atlantic Ridge. We report a comparative experimental evaluation of the navigation fixes provided by the proposed synchronous acoustic navigation system in comparison to navigation fixes obtained by an independent conventional long baseline acoustic navigation system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86040/1/swebster-7.pd

Cough reflex sensitivity improves with speech language pathology management of refractory chronic cough

Rationale: Speech language pathology is an effective management intervention for chronic cough that persists despite medical treatment. The mechanism behind the improvement has not been determined but may include active cough suppression, reduced cough sensitivity or increased cough threshold from reduced laryngeal irritation. Objective measures such as cough reflex sensitivity and cough frequency could be used to determine whether the treatment response was due to reduced underlying cough sensitivity or to more deliberate control exerted by individual patients. The number of treatments required to effect a response was also assessed. Objective: The aim of this study was to investigate subjective and objective measures of cough before, during and after speech language pathology treatment for refractory chronic cough and the mechanism underlying the improvement. Methods: Adults with chronic cough (n = 17) were assessed before, during and after speech language pathology intervention for refractory chronic cough. The primary outcome measures were capsaicin cough reflex sensitivity, automated cough frequency detection and cough-related quality of life. Results: Following treatment there was a significant improvement in cough related quality of life (Median (IQR) at baseline: 13.5 (6.3) vs. post treatment: 16.9 (4.9), p = 0.002), objective cough frequency (Mean ± SD at baseline: 72.5 ± 55.8 vs. post treatment: 25 ± 27.9 coughs/hr, p = 0.009), and cough reflex sensitivity (Mean ± SD log C5 at baseline: 0.88 ± 0.48 vs. post treatment: 1.65 ± 0.88, p < 0.0001). Conclusions: This is the first study to show that speech language pathology management is an effective intervention for refractory chronic cough and that the mechanism behind the improvement is due to reduced laryngeal irritation which results in decreased cough sensitivity, decreased urge to cough and an increased cough threshold. Speech language pathology may be a useful and sustained treatment for refractory chronic cough. Trial Registration: Australian New Zealand Clinical Trials Register, ACTRN12608000284369

Is State Law Looking for Trouble: The Federal Arbitration Act Flexes Its Preemptive Muscle

This article begins with an overview of the preemption concept as it affects the American legal system. The source of preemption power is revealed and the most common forms of preemption are introduced. Next, the article discusses preemption and its interaction with the Federal Arbitration Act (FAA). The discussion begins with a chronological view of the cases that have defined the effects the FAA has on arbitration agreements via its preemption power and ends with a summary of the current state of the law

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is the use of computational algorithms that mimic human cognitive functions to analyze complex medical data. AI technologies like machine learning (ML) support the integration of biological, psychological, and social factors when approaching diagnosis, prognosis, and treatment of disease. This paper serves to acquaint clinicians and other stakeholders with the use, benefits, and limitations of AI for predicting, diagnosing, and classifying mild and major neurocognitive impairments, by providing a conceptual overview of this topic with emphasis on the features explored and AI techniques employed. We present studies that fell into six categories of features used for these purposes: (1) sociodemographics; (2) clinical and psychometric assessments; (3) neuroimaging and neurophysiology; (4) electronic health records and claims; (5) novel assessments (e.g., sensors for digital data); and (6) genomics/other omics. For each category we provide examples of AI approaches, including supervised and unsupervised ML, deep learning, and natural language processing. AI technology, still nascent in healthcare, has great potential to transform the way we diagnose and treat patients with neurocognitive disorders

Shared brain and genetic architectures between mental health and physical activity

Physical activity is correlated with, and effectively treats various forms of psychopathology. However, whether biological correlates of physical activity and psychopathology are shared remains unclear. Here, we examined the extent to which the neural and genetic architecture of physical activity and mental health are shared. Using data from the UK Biobank (N = 6389), we applied canonical correlation analysis to estimate associations between the amplitude and connectivity strength of subnetworks of three major neurocognitive networks (default mode, DMN; salience, SN; central executive networks, CEN) with accelerometer-derived measures of physical activity and self-reported mental health measures (primarily of depression, anxiety disorders, neuroticism, subjective well-being, and risk-taking behaviors). We estimated the genetic correlation between mental health and physical activity measures, as well as putative causal relationships by applying linkage disequilibrium score regression, genomic structural equational modeling, and latent causal variable analysis to genome-wide association summary statistics (GWAS N = 91,105-500,199). Physical activity and mental health were associated with connectivity strength and amplitude of the DMN, SN, and CEN (r\u27s ≥ 0.12, p\u27s \u3c 0.048). These neural correlates exhibited highly similar loading patterns across mental health and physical activity models even when accounting for their shared variance. This suggests a largely shared brain network architecture between mental health and physical activity. Mental health and physical activity (including sleep) were also genetically correlated (|rg| = 0.085-0.121), but we found no evidence for causal relationships between them. Collectively, our findings provide empirical evidence that mental health and physical activity have shared brain and genetic architectures and suggest potential candidate subnetworks for future studies on brain mechanisms underlying beneficial effects of physical activity on mental health