Inside the Internet

Conventional wisdom—particularly in the legal literatures—suggests that competition reigns the inside of the internet. This common understanding has shaped regulatory approaches to questions of network security and competition policy among service providers. But the original research presented here undermines that long-held assumption. Where the markets for internet traffic exchange (and related services) have long been thought to be characterized by robust competition among various network services providers, our findings suggest that these markets have consolidated. These trends raise a host of concerns for network reliability, online speech, and consumer choice, among other matters. Indeed, some recent high-profile internet outages reflect some of these concerns. And so we consider how the internet’s regulatory infrastructure might respond to these new revelations about the internet’s interior network infrastructure. Specifically, we call for regulation to enhance visibility of the internet’s interior and to assure a regime of fair carriage for all the internet’s users

One-Step, Three-Factor Passthought Authentication With Custom-Fit, In-Ear EEG

In-ear EEG offers a promising path toward usable, discreet brain-computer interfaces (BCIs) for both healthy individuals and persons with disabilities. To test the promise of this modality, we produced a brain-based authentication system using custom-fit EEG earpieces. In a sample of N = 7 participants, we demonstrated that our system has high accuracy, higher than prior work using non-custom earpieces. We demonstrated that both inherence and knowledge factors contribute to authentication accuracy, and performed a simulated attack to show our system's robustness against impersonation. From an authentication standpoint, our system provides three factors of authentication in a single step. From a usability standpoint, our system does not require a cumbersome, head-worn device

Connecting livestock disease dynamics to human learning and biosecurity decisions

The acceleration of animal disease spread worldwide due to increased animal, feed, and human movement has driven a growing body of epidemiological research as well as a deeper interest in human behavioral studies aimed at understanding their interconnectedness. Biosecurity measures can reduce the risk of infection, but human risk tolerance can hinder biosecurity investments and compliance. Humans may learn from hardship and become more risk averse, but sometimes they instead become more risk tolerant because they forget negative experiences happened in the past or because they come to believe they are immune. We represent the complexity of the hog production system with disease threats, human decision making, and human risk attitude using an agent-based model. Our objective is to explore the role of risk tolerant behaviors and the consequences of delayed biosecurity investments. We set up experiment with Monte Carlo simulations of scenarios designed with different risk tolerance amongst the swine producers and we derive distributions and trends of biosecurity and porcine epidemic diarrhea virus (PEDv) incidence emerging in the system. The output data allowed us to examine interactions between modes of risk tolerance and timings of biosecurity response discussing consequences for disease protection in the production system. The results show that hasty and delayed biosecurity responses or slow shifts toward a biosecure culture do not guarantee control of contamination when the disease has already spread in the system. In an effort to support effective disease prevention, our model results can inform policy making to move toward more resilient and healthy production systems. The modeled dynamics of risk attitude have also the potential to improve communication strategies for nudging and establishing risk averse behaviors thereby equipping the production system in case of foreign disease incursions

COVID-19 Severity Among American Indians and Alaska Natives in 16 States - January 1, 2020, to March 31, 2021

Objective: To compare rates and risk factors of severe COVID-19-related outcomes between American Indian/Alaska Native (AI/AN) and non-Hispanic White people (NHW). Methods: Aggregate Social Vulnerability Index (SVI), COVID-19-related risk factor, hospitalization, and mortality data were obtained from 16 states for January 1, 2020-March 31, 2021. Generalized estimating equation Poisson regression models calculated age-adjusted cumulative incidences, incidence ratios (IR), and 95% confidence intervals (CI) comparing AI/AN and NHW persons by age, sex, and county-level SVI status. Results: Race data were missing for 42.7% of COVID-19 cases, 24.7% of hospitalizations, and 10.1% of deaths. Risk of AI/AN COVID-19 mortality was 2.6 times that of NHW persons (IR 2.6, 95% CI: 1.7 – 3.4); risk of COVID-19-related hospitalization among AI/AN persons was 3.5 times that of NHW (IR: 3.5, 95% CI: 2.7 – 4.3). Severe COVID-19 outcomes were significantly higher for AI/AN persons compared to NHW persons across all age and sex groups. There was no statistically significant difference in COVID-19 outcomes by SVI status. Associations between severe COVID-19 outcomes and co-morbid risk factors were inconsistent. Conclusions: Results describe increased risk of severe COVID-19 outcomes for AI/AN persons compared to NHW persons despite quality issues in public health surveillance data. Data linkages and improved ascertainment reduce race/ethnicity misclassification and improve data quality. COVID-19-related health burdens among AI/AN persons warrant improved access for AI/AN communities to medical countermeasures and healthcare resources

Soluble receptor for advanced glycation end products (sRAGE) as a biomarker of COPD

BACKGROUND: Soluble receptor for advanced glycation end products (sRAGE) is a proposed emphysema and airflow obstruction biomarker; however, previous publications have shown inconsistent associations and only one study has investigate the association between sRAGE and emphysema. No cohorts have examined the association between sRAGE and progressive decline of lung function. There have also been no evaluation of assay compatibility, receiver operating characteristics, and little examination of the effect of genetic variability in non-white population. This manuscript addresses these deficiencies and introduces novel data from Pittsburgh COPD SCCOR and as well as novel work on airflow obstruction. A meta-analysis is used to quantify sRAGE associations with clinical phenotypes. METHODS: sRAGE was measured in four independent longitudinal cohorts on different analytic assays: COPDGene (n = 1443); SPIROMICS (n = 1623); ECLIPSE (n = 2349); Pittsburgh COPD SCCOR (n = 399). We constructed adjusted linear mixed models to determine associations of sRAGE with baseline and follow up forced expiratory volume at one second (FEV1) and emphysema by quantitative high-resolution CT lung density at the 15th percentile (adjusted for total lung capacity). RESULTS: Lower plasma or serum sRAGE values were associated with a COPD diagnosis (P < 0.001), reduced FEV1 (P < 0.001), and emphysema severity (P < 0.001). In an inverse-variance weighted meta-analysis, one SD lower log10-transformed sRAGE was associated with 105 ± 22 mL lower FEV1 and 4.14 ± 0.55 g/L lower adjusted lung density. After adjusting for covariates, lower sRAGE at baseline was associated with greater FEV1 decline and emphysema progression only in the ECLIPSE cohort. Non-Hispanic white subjects carrying the rs2070600 minor allele (A) and non-Hispanic African Americans carrying the rs2071288 minor allele (A) had lower sRAGE measurements compare to those with the major allele, but their emphysema-sRAGE regression slopes were similar. CONCLUSIONS: Lower blood sRAGE is associated with more severe airflow obstruction and emphysema, but associations with progression are inconsistent in the cohorts analyzed. In these cohorts, genotype influenced sRAGE measurements and strengthened variance modelling. Thus, genotype should be included in sRAGE evaluations

BigBOSS: The Ground-Based Stage IV BAO Experiment

The BigBOSS experiment is a proposed DOE-NSF Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with an all-sky galaxy redshift survey. The project is designed to unlock the mystery of dark energy using existing ground-based facilities operated by NOAO. A new 4000-fiber R=5000 spectrograph covering a 3-degree diameter field will measure BAO and redshift space distortions in the distribution of galaxies and hydrogen gas spanning redshifts from 0.2&lt; z&lt; 3.5. The Dark Energy Task Force figure of merit (DETF FoM) for this experiment is expected to be equal to that of a JDEM mission for BAO with the lower risk and cost typical of a ground-based experiment