Risk, Resources, and Education: Public Versus Private Financing of Higher Education

The paper develops a public education scheme that takes aspects of uncertainty in private educational investments explicitly into account. The social merits of public education schemes are related to the lack of markets in which students can insure against educational risks. A case is made for tuition fees that depend on expected returns of investments in education. The consideration of uncertainty provides a neglected link between educational choice, resource endowment, and productivity growth, which may serve to redefine the public role of education financing. Copyright 2002, International Monetary Fund

Indoor Localization Using Uncooperative Wi-Fi Access Points

Indoor localization using fine time measurement (FTM) round-trip time (RTT) with respect to cooperating Wi-Fi access points (APs) has been shown to work well and provide 1–2 m accuracy in both 2D and 3D applications. This approach depends on APs implementing the IEEE 802.11-2016 (also known as IEEE 802.11mc) Wi-Fi standard (“two-sided” RTT). Unfortunately, the penetration of this Wi-Fi protocol has been slower than anticipated, perhaps because APs tend not to be upgraded as often as other kinds of electronics, in particular in large institutions—where they would be most useful. Recently, Google released Android 12, which also supports an alternative “one-sided” RTT method that will work with legacy APs as well. This method cannot subtract out the “turn-around” time of the signal, and so, produces distance estimates that have much larger offsets than those seen with two-sided RTT—and the results are somewhat less accurate. At the same time, this method makes possible distance measurements for many APs that previously could not be used. This increased accessibility can compensate for the decreased accuracy of individual measurements. We demonstrate here indoor localization using one-sided RTT with respect to legacy APs that do not support IEEE 802.11-2016. The accuracy achieved is 3–4 m in cluttered environments with few line-of-sight readings (and using only 20 MHz bandwidths). This is not as good as for two-sided RTT, where 1–2 m accuracy has been achieved (using 80 MHz bandwidths), but adequate for many applications A wider Wi-Fi channel bandwidth would increase the accuracy further. As before, Bayesian grid update is the preferred method for determining position and positional accuracy, but the observation model now is different from that for two-sided RTT. As with two-sided RTT, the probability of an RTT measurement below the true distance is very low, but, in the other direction, the range of measurements for a given distance can be much wider (up to well over twice the actual distance). We describe methods for formulating useful observation models. As with two-sided RTT, the offset or bias in distance measurements has to be subtracted from the reported measurements. One difference is that here, the offsets are large (typically in the 2400–2700 m range) because of the “turn-around time” of roughly 16 μs (i.e., about two orders of magnitude larger than the time of flight one is attempting to measure). We describe methods for estimating these offsets and for minimizing the effort required to do so when setting up an installation with many APs

Carboniferous pycnoxylic woods from the Dwyka Group of southern Namibia

Glacial deposits of the Dwyka Group between Keetmanshoop and Mariental in southern Namibia have been reinvestigated for palaeontological remains and associated tuff horizons in an attempt to accurately date the deposits. SHRIMP-based dating of juvenile zircons from these tuff horizons provide ages which cumulate in the latest Carboniferous (Gzelian). The pycnoxylic woods Megaporoxylon scherziKrausel and Megaporoxylon kaokense Krausel are described in detail for the first time and are compared with similar permineralised woods from Gondwana. Based on previous fossil wood studies covering the rocks of the main Karoo Basin, these species occur only in the Dwyka and lower Ecca Groups in southern Africa and do not extend to the upper Ecca Group.The Council's Research Committee, University of the Witwatersrand; National Research Foundation (NRF); Palaeo-Anthropology Scientific Trust (PAST); German Research Foundation (DFG) and the Postgraduate Research Program "Interdisciplinary Geoscience Research in Africa

Machine learning predicts putative hematopoietic stem cells within large single-cell transcriptomics data sets.

Hematopoietic stem cells (HSCs) are an essential source and reservoir for normal hematopoiesis, and their function is compromised in many blood disorders. HSC research has benefitted from the recent development of single-cell molecular profiling technologies, where single-cell RNA sequencing (scRNA-seq) in particular has rapidly become an established method to profile HSCs and related hematopoietic populations. The classic definition of HSCs relies on transplantation assays, which have been used to validate HSC function for cell populations defined by flow cytometry. Flow cytometry information for single cells, however, is not available for many new high-throughput scRNA-seq methods, thus highlighting an urgent need for the establishment of alternative ways to pinpoint the likely HSCs within large scRNA-seq data sets. To address this, we tested a range of machine learning approaches and developed a tool, hscScore, to score single-cell transcriptomes from murine bone marrow based on their similarity to gene expression profiles of validated HSCs. We evaluated hscScore across scRNA-seq data from different laboratories, which allowed us to establish a robust method that functions across different technologies. To facilitate broad adoption of hscScore by the wider hematopoiesis community, we have made the trained model and example code freely available online. In summary, our method hscScore provides fast identification of mouse bone marrow HSCs from scRNA-seq measurements and represents a broadly useful tool for analysis of single-cell gene expression data.MRC, Wellcome Trust, Bloodwise, CRU

Off-nadir antenna bias correction using Amazon rain sigma(0) data

The radar response from the Amazon rain forest was studied to determine the suitability of this region for use as a standard target to calibrate a scatterometer like that proposed for the National Oceanic Satellite System (NOSS). Backscattering observations made by the SEASAT Scatterometer System (SASS) showed the Amazon rain forest to be a homogeneous, azimuthally-isotropic, radar target which was insensitive to polarization. The variation with angle of incidence was adequately modeled as scattering coefficient (dB) = a theta b with typical values for the incidence-angle coefficient from 0.07 to 0.15 dB/deg. A small diurnal effect occurs, with measurements at sunrise being 0.5 dB to 1 dB higher than the rest of the day. Maximum-likelihood estimation algorithms presented here permit determination of relative bias and true pointing angle for each beam. Specific implementation of these algorithms for the proposed NOSS scatterometer system is also discussed

Patterns and predictors of statin prescription in patients with type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>The benefit of statins for prevention of cardiovascular events in type 2 diabetes is established, but a gap exists between guideline recommendations and clinical practice. The aim of the study was to identify patient-related factors predicting statin prescription.</p> <p>Methods</p> <p>We assessed the quality of care in 51,640 patients with type 2 diabetes in a German diabetes registry. Patients were stratified according to primary and secondary prevention. Five-year risk for cardiovascular events was calculated in primary prevention patients. A multivariate adjusted logistic regression model was constructed to determine which parameters influenced statin prescription.</p> <p>Results</p> <p>34% had established atherosclerotic disease and 25.5% received a statin. Prescription was significantly higher in the secondary compared to the primary prevention group (38.1% [95% CI 37.4–38.9%] vs. 18.5% [95% CI 18.0–19.0%], respectively). In primary prevention the odds for statin prescription increased with estimated cardiovascular risk (OR 1.17 per 5% increase in 5-year risk, 95% CI 1.11–1.22). Positive predictors for statin prescription were secondary prevention, hypertension, former smoking, baseline LDL-cholesterol, and microalbuminuria. The odds of receiving a statin had an inverted U-shaped relation with age (nadir, 66 years), age at first diagnosis of diabetes (nadir, 56 years), and body mass index (nadir, 32 kg/m²). The model predicted prescription in 70% of the patients correctly.</p> <p>Conclusion</p> <p>The majority of patients with type 2 diabetes are not receiving statins. The predominant factors determining statin prescription are the patient's prevention status and, in primary prevention, estimated cardiovascular risk. The results suggest that although physicians are aware of the general concept of cardiovascular risk, they fail to consistently implement guidelines.</p

Öffentliche oder private Umsetzung des staatlichen Bildungsauftrages? : Eine Analyse auf der Grundlage der Theorie unvollständiger Verträge

Soll der Staat den gesetzlichen Bildungsauftrag durch die Errichtung öffentlicher Bildungseinrichtungen umsetzen, oder soll er private Unternehmen beauftragen, für ein ausreichendes Angebot an Bildung zu sorgen? Diese Frage wurde in der bisherigen bildungsökonomischen Diskussion weitgehend unter verteilungspolitischen Gesichtspunkten betrachtet oder aus historischer Perspektive beantwortet. Wir thematisieren dagegen in der vorliegenden Arbeit den Effizienzaspekt der öffentlichen und der privaten Bildungsproduktion, wobei wir die vertraglichen Grundlagen der beiden Produktionsalternativen und die dadurch bedingten Anreize in den Bildungseinrichtungen in den Mittelpunkt unserer Analyse stellen

Ezetimibe alone or in combination with simvastatin increases small dense low-density lipoproteins in healthy men: a randomized trial

Aims The predominance of small dense low-density lipoproteins (sdLDLs) has been associated with increased cardiovascular risk. The effect of ezetimibe on LDL subfraction distribution has not been fully elucidated. This study assessed by gradient gel electrophoresis the effects of ezetimibe alone, simvastatin alone, and their combination on sdLDL subfraction distribution. Methods and results A single-centre, randomized, parallel three-group open-label study was performed in 72 healthy men with a baseline LDL-cholesterol (LDL-C) concentration of 111 ± 30 mg/dL (2.9 ± 0.8 mmol/L). They were treated with ezetimibe (10 mg/day, n = 24), simvastatin (40 mg/day, n = 24), or their combination (n = 24) for 14 days. Blood was drawn before and after the treatment period. Generalized estimating equations were used to assess the influence of drug therapy on LDL subfraction distribution, controlling for within-subject patterns (clustering). We adjusted for age, body mass index, and baseline concentrations of LDL-C and triglycerides. Ezetimibe alone changed LDL subfraction distribution towards a more atherogenic profile by significantly increasing sdLDL subfractions (LDL-IVA +14.2%, P = 0.0216 and LDL-IVB +16.7%, P = 0.039; fully adjusted Wald χ2 test). In contrast, simvastatin alone significantly decreased the LDL-IVB subfraction (−16.7%, P = 0.002). This effect was offset when simvastatin was combined with ezetimibe (LDL-IVB +14.3%, P = 0.44). All three treatments decreased the large, more buoyant LDL-I subfraction, the effects of ezetimibe being the most pronounced (ezetimibe -13.9%, P < 0.0001; combination therapy −7.3%, P = 0.0743; simvastatin −4.6%, P < 0.0001). Conclusion In healthy men, treatment with ezetimibe alone is associated with the development of a pro-atherogenic LDL subfraction profile. Potentially atheroprotective effects of simvastatin are offset by ezetimibe. This study is registered with ClinicalTrials.gov, identifier no. NCT0031799