Mismatching Measures of Output and Prices: Implications for Measuring the Comovement of Prices and Output

price output correlation

Alternating magnetic field-promoted nanoparticle mixing: the on-chip immunocapture of serum neuronal exosomes for Parkinson’s disease diagnostics

The analysis of cargo proteins in exosome subpopulations has considerable value in diagnostics but a translatable impact has been limited by lengthy or complex exosome extraction protocols. We describe herein a scalable, fast, and low-cost exosome extraction using an alternating (AC) magnetic field to support the dynamic mixing of antibody-coated magnetic beads (MBs) with serum samples within 3D-printed microfluidic chips. Zwitterionic polymer-coated MBs are, specifically, magnetically agitated and support ultraclean exosome capture efficiencies >70% from <50 μL of neat serum in 30 min. Applied herein to the immunocapture of neuronal exosomes using anti-L1CAM antibodies, prior to the array-based assaying of α-synuclein (α-syn) content by a standard duplex electrochemical sandwich ELISA, sub pg/mL detection was possible with an excellent coefficient of variation and a sample-to-answer time of ∼75 min. The high performance and semiautomation of this approach hold promise in underpinning low-cost Parkinson’s disease diagnostics and is of value in exosomal biomarker analyses more generally

A Diabetes Psychosocial Profile

An educational needs assessment instrument for individuals with diabetes has been developed at the Michigan Diabetes Research and Training Center. Responses to the 110-item questionnaire provide subscores on con structs labeled "Control Problems, " "Psychosocial Impact," "Barriers to Compliance, " "Benefits of Regimen, " "Regimen Complexity," and "Risk of Complications." Com bined with demographic and clinical information, these scores form a com prehensive summary of the patient's attitudes, beliefs, behaviors, and knowledge in relation to diabetes. This summary is in the form of an individ ualized graphic profile that highlights possible prob lem areas to be consid ered when developing patient education and management plans.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68817/2/10.1177_014572178601200210.pd

Yrast line for weakly interacting trapped bosons

We compute numerically the yrast line for harmonically trapped boson systems with a weak repulsive contact interaction, studying the transition to a vortex state as the angular momentum L increases and approaches N, the number of bosons. The L=N eigenstate is indeed dominated by particles with unit angular momentum, but the state has other significant components beyond the pure vortex configuration. There is a smooth crossover between low and high L with no indication of a quantum phase transition. Most strikingly, the energy and wave function appear to be analytical functions of L over the entire range 2 < L < N. We confirm the structure of low-L states proposed by Mottelson, as mainly single-particle excitations with two or three units of angular momentum.Comment: 9 pages, 3 EPS-figures, uses psfig.st

Tree-based Unidirectional Neural Networks for Low-Power Computer Vision

This article describes the novel Tree-based Unidirectional Neural Network (TRUNK) architecture. This architecture improves computer vision efficiency by using a hierarchy of multiple shallow Convolutional Neural Networks (CNNs), instead of a single very deep CNN. We demonstrate this architecture’s versatility in performing different computer vision tasks efficiently on embedded devices. Across various computer vision tasks, the TRUNK architecture consumes 65% less energy and requires 50% less memory than representative low-power CNN architectures, e.g., MobileNet v2, when deployed on the NVIDIA Jetson Nano

Directed Acyclic Graph-based Neural Networks for Tunable Low-Power Computer Vision

Processing visual data on mobile devices has many applications, e.g., emergency response and tracking. State-of-the-art computer vision techniques rely on large Deep Neural Networks (DNNs) that are usually too power-hungry to be deployed on resource-constrained edge devices. Many techniques improve DNN efficiency of DNNs by compromising accuracy. However, the accuracy and efficiency of these techniques cannot be adapted for diverse edge applications with different hardware constraints and accuracy requirements. This paper demonstrates that a recent, efficient tree-based DNN architecture, called the hierarchical DNN, can be converted into a Directed Acyclic Graph-based (DAG) architecture to provide tunable accuracy-efficiency tradeoff options. We propose a systematic method that identifies the connections that must be added to convert the tree to a DAG to improve accuracy. We conduct experiments on popular edge devices and show that increasing the connectivity of the DAG improves the accuracy to within 1% of the existing high accuracy techniques. Our approach requires 93% less memory, 43% less energy, and 49% fewer operations than the high accuracy techniques, thus providing more accuracy-efficiency configurations

The Selective Downregulation of Class I Major Histocompatibility Complex Proteins by HIV-1 Protects HIV-Infected Cells from NK Cells

AbstractTo avoid detection by CTL, HIV encodes mechanisms for removal of class I MHC proteins from the surface of infected cells. However, class I downregulation potentially exposes the virus-infected cell to attack by NK cells. Human lymphoid cells are protected from NK cell cytotoxicity primarily by HLA-C and HLA-E. We present evidence that HIV-1 selectively downregulates HLA-A and HLA-B but does not significantly affect HLA-C or HLA-E. We then identify the residues in HLA-C and HLA-E that protect them from HIV downregulation. This selective downregulation allows HIV-infected cells to avoid NK cell–mediated lysis and may represent for HIV a balance between escape from CTL and maintenance of protection from NK cells. These results suggest that subpopulations of CTL and NK cells may be uniquely suited for combating HIV

Geographic Variations in Cardiovascular Health in the United States: Contributions of Stateâ and Individualâ Level Factors

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139063/1/jah3932.pd