Utilizing Deep Neural Networks for Brain–Computer Interface-Based Prosthesis Control

Limb amputations affect a significant portion of the world’s population every year. The necessity for these operations can be associated with related health conditions or a traumatic event. Currently, prosthetic devices intended to alleviate the burden of amputation lack many of the premier features possessed by their biological counterparts. The foremost of these features are agility and tactile function. In an effort to address the former, researchers here investigate the fundamental connection between agile finger movement and brain signaling. In this study each subject was asked to move his or her right index finger in sync with a time-aligned finger movement demonstration while each movement was labeled and the subject’s brain waves were recorded via a single-channel electroencephalograph. This data was subsequently used to train and test a deep neural network in an effort to classify each subject’s intention to rest and intention to extend his or her right index finger. On average, the employed model yielded an accuracy of 63.3%, where the most predictable subject’s movements were classified with an accuracy of 70.5%

Quantum control via a genetic algorithm of the field ionization pathway of a Rydberg electron

Quantum control of the pathway along which a Rydberg electron field ionizes is experimentally and computationally demonstrated. Selective field ionization is typically done with a slowly rising electric field pulse. The $(1/n^*)^4$ scaling of the classical ionization threshold leads to a rough mapping between arrival time of the electron signal and principal quantum number of the Rydberg electron. This is complicated by the many avoided level crossings that the electron must traverse on the way to ionization, which in general leads to broadening of the time-resolved field ionization signal. In order to control the ionization pathway, thus directing the signal to the desired arrival time, a perturbing electric field produced by an arbitrary waveform generator is added to a slowly rising electric field. A genetic algorithm evolves the perturbing field in an effort to achieve the target time-resolved field ionization signal.Comment: Corrected minor typographic errors and changed the titl

Development of an Accelerated Test Design for Predicting the Service Life of the Solar Array at Mead, Nebraska

Potential long-term degradation modes for the two types of modules in the Mead array were determined and judgments were made as to those environmental stresses and combinations of stresses which accelerate the degradation of the power output. Hierarchical trees representing the severity of effects of stresses (test conditions) on eleven individual degradation modes were constructed and were pruned of tests judged to be nonessential. Composites of those trees were developed so that there is now one pruned tree covering eight degradation modes, another covering two degradation modes, and a third covering one degradation mode. These three composite trees form the basis for selection of test conditions in the final test plan which is now being prepared

Exploiting Human Memory B Cell Heterogeneity for Improved Vaccine Efficacy

The major goal in vaccination is establishment of long-term, prophylactic humoral memory to a pathogen. Two major components to long-lived humoral memory are plasma cells for the production of specific immunoglobulin and memory B cells that survey for their specific antigen in the periphery for later affinity maturation, proliferation, and differentiation. The study of human B cell memory has been aided by the discovery of a general marker for B cell memory, expression of CD27; however, new data suggests the existence of CD27− memory B cells as well. These recently described non-canonical memory populations have increasingly pointed to the heterogeneity of the memory compartment. The novel B memory subsets in humans appear to have unique origins, localization, and functions compared to what was considered to be a “classical” memory B cell. In this article, we review the known B cell memory subsets, the establishment of B cell memory in vaccination and infection, and how understanding these newly described subsets can inform vaccine design and disease treatment

Effect of charted mental illness on reperfusion therapy in hospitalized patients with an acute myocardial infarction in Florida

Patients with mental illness carry risk factors that predispose them to excess cardiovascular mortality from an acute myocardial infarction (AMI) compared to the general population. The aim of this study was to determine if patients with AMI and charted mental illness (CMI) received less reperfusion therapy following an AMI, compared to AMI patients without CMI in a recent sample population from Florida. A secondary analysis of data was conducted using the Florida Agency for Health Care Administration (FL-AHCA) hospital discharge registry. Adults hospitalized with an AMI from 01/01/2010 to 12/31/2015 were included for the analysis. The dependent variable was administration of reperfusion therapy (thrombolytic, percutaneous coronary intervention [PCI], and coronary artery bypass graft [CABG]), and the independent variable was the presence of CMI (depression, schizophrenia, and bipolar disorder). Multivariate logistic regression models were used to test the association controlling for age, gender, ethnicity, race, health insurance, and comorbidities. The database included 61,614 adults (31.3% women) hospitalized with AMI in Florida. The CMI population comprised of 1036 patients (1.7%) who were on average 5 years younger than non-CMI (60.2 ±12.8 versus 65.2 ±14.1; P \u3c .001). Compared with patients without CMI, patients with CMI had higher proportions of women, governmental health insurance holders, and those with more comorbidities. The adjusted odds ratio indicated that patients with CMI were 30% less likely to receive reperfusion therapy compared with those without CMI (OR = 0.7; 95% CI = 0.6–0.8). Within the AMI population including those with and without CMI, women were 23% less likely to receive therapy than men; blacks were 26% less likely to receive reperfusion therapy than whites; and those holding government health insurances were between 20% and 40% less likely to receive reperfusion therapy than those with private health insurance. Patients with AMI and CMI were statistically significantly less likely to receive reperfusion therapy compared with patients without CMI. These findings highlight the need to implement AMI management care aimed to reduce disparities among medically vulnerable patients (those with CMI, women, blacks, and those with governmental health insurance)

Machine learning reduced workload with minimal risk of missing studies: development and evaluation of an RCT classifier for Cochrane Reviews

BACKGROUND: To describe the development, calibration and evaluation of a machine learning classifier designed to reduce study identification workload in Cochrane for producing systematic reviews. METHODS: A machine learning classifier for retrieving RCTs was developed (the ‘Cochrane RCT Classifier’), with the algorithm trained using a dataset of title-abstract records from Embase, manually labelled by the Cochrane Crowd. The classifier was then calibrated using a further dataset of similar records manually labelled by the Clinical Hedges team, aiming for 99% recall. Finally, the recall of the calibrated classifier was evaluated using records of RCTs included in Cochrane Reviews that had abstracts of sufficient length to allow machine classification. RESULTS: The Cochrane RCT Classifier was trained using 280,620 records (20,454 of which reported RCTs). A classification threshold was set using 49,025 calibration records (1,587 of which reported RCTs) and our bootstrap validation found the classifier had recall of 0.99 (95% CI 0.98 to 0.99) and precision of 0.08 (95% CI 0.06 to 0.12) in this dataset. The final, calibrated RCT classifier correctly retrieved 43,783 (99.5%) of 44,007 RCTs included in Cochrane Reviews but missed 224 (0.5%). Older records were more likely to be missed than those more recently published. CONCLUSIONS: The Cochrane RCT Classifier can reduce manual study identification workload for Cochrane reviews, with a very low and acceptable risk of missing eligible RCTs. This classifier now forms part of the Evidence Pipeline, an integrated workflow deployed within Cochrane to help improve the efficiency of the study identification processes that support systematic review production

Low loss tapered polysilicon core fibers

We have fabricated small core polysilicon waveguides by tapering bulk, as-drawn silicon optical fibers. The taper process acts to improve the local crystallinity of the core, resulting in a significant reduction in the material los

Early abdominal closure with mesh reduces multiple organ failure after ruptured abdominal aortic aneurysm repair: Guidelines from a 10-year case-control study

AbstractObjective: The objectives of this study were the comparison of patients who needed mesh closure of the abdomen with patients who underwent standard abdominal closure after ruptured abdominal aortic aneurysm repair and the determination of the impact of timing of mesh closure on multiple organ failure (MOF) and mortality. Methods: We performed a case-control study of patients who needed mesh-based abdominal closure (n = 45) as compared with patients who underwent primary closure (n = 90) after ruptured abdominal aortic aneurysm repair. Results: Before surgery, the patients who needed mesh abdominal closure had more blood loss (8 g versus 12 g of hemoglobin; P <.05), had prolonged hypotension (18 minutes versus 3 minutes; P <.01), and more frequently needed cardiopulmonary resuscitation (31% versus 2%; P <.01) than did the patients who underwent primary closure. During surgery, the patients who needed mesh closure also had more severe acidosis (base deficit, 14 versus 7; P <.01), had profound hypothermia (32°C versus 35°C; P <.01), and needed more fluid resuscitation (4.0 L/h versus 2.7 L/h; P <.01). With this adverse clinical profile, the patients who needed mesh closure had a higher mortality rate than did the patients who underwent primary closure (56% versus 9%; P <.01). However, the patients who underwent mesh closure at the initial operation (n = 35) had lower MOF scores (P <.05), a lower mortality rate (51% versus 70%), and were less likely to die from MOF (11% versus 70%; P <.05) than the patients who underwent mesh closure after a second operation in the postoperative period for abdominal compartment syndrome (n = 10). Conclusion: This study reports the largest experience of mesh-based abdominal closure after ruptured abdominal aortic aneurysm repair and defines clinical predictors for patients who need to undergo this technique. Recognition of these predictors and initial use of mesh closure minimize abdominal compartment syndrome and reduce the rate of mortality as the result of MOF. (J Vasc Surg 2002;35:246-53.

Improving the State Selectivity of Field Ionization With Quantum Control

The electron signals from the field ionization of two closely spaced Rydberg states of rubidium-85 are separated using quantum control. In selective field ionization, the state distribution of a collection of Rydberg atoms is measured by ionizing the atoms with a ramped electric field. Generally, atoms in higher energy states ionize at lower fields, so ionized electrons which are detected earlier in time can be correlated with higher energy Rydberg states. However, the resolution of this technique is limited by the Stark effect. As the electric field is increased, the electron encounters numerous avoided Stark level crossings which split the amplitude among many states, thus broadening the time-resolved ionization signal. Previously, a genetic algorithm has been used to control the signal shape of a single Rydberg state. The present work extends this technique to separate the signals from the 34s and 33p states of rubidium-85, which are overlapped when using a simple field ramp as in selective field ionization