Greenspan’s Monetary Policy in Retrospect: Discretion or Rules?

Is Alan Greenspan to blame for the current housing bubble and the ongoing financial crisis? A growing chorus charges the former Federal Reserve Chairman with being an "inflationist" whose loose monetary policy caused or significantly contributed to our current economic troubles. However, although Greenspan's policies weren't perfect, his monetary policy was in fact tight, and his legacy is one of having overseen low and stable inflation and a striking dampening of the business cycle. Critics charge Greenspan with having carried on an excessively expansionary monetary policy, particularly following the recession of 2001. They note how low interest rates were from 2002 through 2004 and argue that those low rates paved the way for everything from high prices at the pump to high prices at the supermarket, from the housing crisis to the financial crisis. In so doing, those critics make the classic mistake of using interest rates to evaluate monetary policy, reasoning that if interest rates are low, recent monetary policy must have been expansionary. It is not the Federal Reserve but supply and demand that ultimately determines interest rates. Although central banks can push rates up or down to some degree, the globally integrated financial system reduces the Fed’s ability to significantly influence rates. This paper should not be construed as a defense of all of Greenspan’s policies, nor of central banking or the Federal Reserve. In fact, our preference would be to abolish the Fed and deregulate the banking industry. Barring that, we argue that Federal Reserve policy ought to abide by the rules rather than the discretion of its chairman

Evaluating the Reproducibility of Physiological Stress Detection Models

Recent advances in wearable sensor technologies have led to a variety of approaches for detecting physiological stress. Even with over a decade of research in the domain, there still exist many significant challenges, including a near-total lack of reproducibility across studies. Researchers often use some physiological sensors (custom-made or off-the-shelf), conduct a study to collect data, and build machine-learning models to detect stress. There is little effort to test the applicability of the model with similar physiological data collected from different devices, or the efficacy of the model on data collected from different studies, populations, or demographics. This paper takes the first step towards testing reproducibility and validity of methods and machine-learning models for stress detection. To this end, we analyzed data from 90 participants, from four independent controlled studies, using two different types of sensors, with different study protocols and research goals. We started by evaluating the performance of models built using data from one study and tested on data from other studies. Next, we evaluated new methods to improve the performance of stress-detection models and found that our methods led to a consistent increase in performance across all studies, irrespective of the device type, sensor type, or the type of stressor. Finally, we developed and evaluated a clustering approach to determine the stressed/not-stressed classification when applying models on data from different studies, and found that our approach performed better than selecting a threshold based on training data. This paper\u27s thorough exploration of reproducibility in a controlled environment provides a critical foundation for deeper study of such methods, and is a prerequisite for tackling reproducibility in free-living conditions

MR diffusion changes in the perimeter of the lateral ventricles demonstrate periventricular injury in post-hemorrhagic hydrocephalus of prematurity

OBJECTIVES: Injury to the preterm lateral ventricular perimeter (LVP), which contains the neural stem cells responsible for brain development, may contribute to the neurological sequelae of intraventricular hemorrhage (IVH) and post-hemorrhagic hydrocephalus of prematurity (PHH). This study utilizes diffusion MRI (dMRI) to characterize the microstructural effects of IVH/PHH on the LVP and segmented frontal-occipital horn perimeters (FOHP). STUDY DESIGN: Prospective study of 56 full-term infants, 72 very preterm infants without brain injury (VPT), 17 VPT infants with high-grade IVH without hydrocephalus (HG-IVH), and 13 VPT infants with PHH who underwent dMRI at term equivalent. LVP and FOHP dMRI measures and ventricular size-dMRI correlations were assessed. RESULTS: In the LVP, PHH had consistently lower FA and higher MD and RD than FT and VPT (p\u3c.050). However, while PHH FA was lower, and PHH RD was higher than their respective HG-IVH measures (p\u3c.050), the MD and AD values did not differ. In the FOHP, PHH infants had lower FA and higher RD than FT and VPT (p\u3c.010), and a lower FA than the HG-IVH group (p\u3c.001). While the magnitude of AD in both the LVP and FOHP were consistently less in the PHH group on pairwise comparisons to the other groups, the differences were not significant (p\u3e.050). Ventricular size correlated negatively with FA, and positively with MD and RD (p\u3c.001) in both the LVP and FOHP. In the PHH group, FA was lower in the FOHP than in the LVP, which was contrary to the observed findings in the healthy infants (p\u3c.001). Nevertheless, there were no regional differences in AD, MD, and RD in the PHH group. CONCLUSION: HG-IVH and PHH results in aberrant LVP/FOHP microstructure, with prominent abnormalities among the PHH group, most notably in the FOHP. Larger ventricular size was associated with greater magnitude of abnormality. LVP/FOHP dMRI measures may provide valuable biomarkers for future studies directed at improving the management and neurological outcomes of IVH/PHH

Navier-Stokes Analysis of a High Wing Transport High-Lift Configuration with Externally Blown Flaps

Insights and lessons learned from the aerodynamic analysis of the High Wing Transport (HWT) high-lift configuration are presented. Three-dimensional Navier-Stokes CFD simulations using the OVERFLOW flow solver are compared with high Reynolds test data obtained in the NASA Ames 12 Foot Pressure Wind Tunnel (PWT) facility. Computational analysis of the baseline HWT high-lift configuration with and without Externally Blown Flap (EBF) jet effects is highlighted. Several additional aerodynamic investigations, such as nacelle strake effectiveness and wake vortex studies, are presented. Technical capabilities and shortcomings of the computational method are discussed and summarized

Characterization of single-nucleotide variation in Indian-origin rhesus macaques (Macaca mulatta)

<p>Abstract</p> <p>Background</p> <p>Rhesus macaques are the most widely utilized nonhuman primate model in biomedical research. Previous efforts have validated fewer than 900 single nucleotide polymorphisms (SNPs) in this species, which limits opportunities for genetic studies related to health and disease. Extensive information about SNPs and other genetic variation in rhesus macaques would facilitate valuable genetic analyses, as well as provide markers for genome-wide linkage analysis and the genetic management of captive breeding colonies.</p> <p>Results</p> <p>We used the available rhesus macaque draft genome sequence, new sequence data from unrelated individuals and existing published sequence data to create a genome-wide SNP resource for Indian-origin rhesus monkeys. The original reference animal and two additional Indian-origin individuals were resequenced to low coverage using SOLiD™ sequencing. We then used three strategies to validate SNPs: comparison of potential SNPs found in the same individual using two different sequencing chemistries, and comparison of potential SNPs in different individuals identified with either the same or different sequencing chemistries. Our approach validated approximately 3 million SNPs distributed across the genome. Preliminary analysis of SNP annotations suggests that a substantial number of these macaque SNPs may have functional effects. More than 700 non-synonymous SNPs were scored by Polyphen-2 as either possibly or probably damaging to protein function and these variants now constitute potential models for studying functional genetic variation relevant to human physiology and disease.</p> <p>Conclusions</p> <p>Resequencing of a small number of animals identified greater than 3 million SNPs. This provides a significant new information resource for rhesus macaques, an important research animal. The data also suggests that overall genetic variation is high in this species. We identified many potentially damaging non-synonymous coding SNPs, providing new opportunities to identify rhesus models for human disease.</p

Seroprevalence of Zika virus in wild African green monkeys and baboons

ABSTRACT Zika virus (ZIKV) has recently spread through the Americas and has been associated with a range of health effects, including birth defects in children born to women infected during pregnancy. Although the natural reservoir of ZIKV remains poorly defined, the virus was first identified in a captive “sentinel” macaque monkey in Africa in 1947. However, the virus has not been reported in humans or nonhuman primates (NHPs) in Africa outside Gabon in over a decade. Here, we examine ZIKV infection in 239 wild baboons and African green monkeys from South Africa, the Gambia, Tanzania, and Zambia using combinations of unbiased deep sequencing, quantitative reverse transcription-PCR (qRT-PCR), and an antibody capture assay that we optimized using serum collected from captive macaque monkeys exposed to ZIKV, dengue virus, and yellow fever virus. While we did not find evidence of active ZIKV infection in wild NHPs in Africa, we found variable ZIKV seropositivity of up to 16% in some of the NHP populations sampled. We anticipate that these results and the methodology described within will help in continued efforts to determine the prevalence, natural reservoir, and transmission dynamics of ZIKV in Africa and elsewhere. IMPORTANCE Zika virus (ZIKV) is a mosquito-borne virus originally discovered in a captive monkey living in the Zika Forest of Uganda, Africa, in 1947. Recently, an outbreak in South America has shown that ZIKV infection can cause myriad health effects, including birth defects in the children of women infected during pregnancy. Here, we sought to investigate ZIKV infection in wild African primates to better understand its emergence and spread, looking for evidence of active or prior infection. Our results suggest that up to 16% of some populations of nonhuman primate were, at some point, exposed to ZIKV. We anticipate that this study will be useful for future studies that examine the spread of infections from wild animals to humans in general and those studying ZIKV in primates in particular. Podcast: A podcast concerning this article is available

An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels

Pre-trained language models derive substantial linguistic and factual knowledge from the massive corpora on which they are trained, and prompt engineering seeks to align these models to specific tasks. Unfortunately, existing prompt engineering methods require significant amounts of labeled data, access to model parameters, or both. We introduce a new method for selecting prompt templates \textit{without labeled examples} and \textit{without direct access to the model}. Specifically, over a set of candidate templates, we choose the template that maximizes the mutual information between the input and the corresponding model output. Across 8 datasets representing 7 distinct NLP tasks, we show that when a template has high mutual information, it also has high accuracy on the task. On the largest model, selecting prompts with our method gets 90\% of the way from the average prompt accuracy to the best prompt accuracy and requires no ground truth labels

An allometric scaling relationship in the brain of preterm infants

Allometry has been used to demonstrate a power–law scaling relationship in the brain of premature born infants. Forty-nine preterm infants underwent neonatal MRI scans and neurodevelopmental testing at age 2. Measures of cortical surface area and total cerebral volume demonstrated a power–law scaling relationship (α = 1.27). No associations were identified between these measures and investigated clinical variables. Term equivalent cortical surface area and total cerebral volume measures and scaling exponents were not related to outcome. These findings confirm a previously reported allometric scaling relationship in the preterm brain, and suggest that scaling is not a sensitive indicator of aberrant cortical maturation