Validation of machine learning models to detect amyloid pathologies across institutions.

Semi-quantitative scoring schemes like the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) are the most commonly used method in Alzheimer's disease (AD) neuropathology practice. Computational approaches based on machine learning have recently generated quantitative scores for whole slide images (WSIs) that are highly correlated with human derived semi-quantitative scores, such as those of CERAD, for Alzheimer's disease pathology. However, the robustness of such models have yet to be tested in different cohorts. To validate previously published machine learning algorithms using convolutional neural networks (CNNs) and determine if pathological heterogeneity may alter algorithm derived measures, 40 cases from the Goizueta Emory Alzheimer's Disease Center brain bank displaying an array of pathological diagnoses (including AD with and without Lewy body disease (LBD), and / or TDP-43-positive inclusions) and levels of Aβ pathologies were evaluated. Furthermore, to provide deeper phenotyping, amyloid burden in gray matter vs whole tissue were compared, and quantitative CNN scores for both correlated significantly to CERAD-like scores. Quantitative scores also show clear stratification based on AD pathologies with or without additional diagnoses (including LBD and TDP-43 inclusions) vs cases with no significant neurodegeneration (control cases) as well as NIA Reagan scoring criteria. Specifically, the concomitant diagnosis group of AD + TDP-43 showed significantly greater CNN-score for cored plaques than the AD group. Finally, we report that whole tissue computational scores correlate better with CERAD-like categories than focusing on computational scores from a field of view with densest pathology, which is the standard of practice in neuropathological assessment per CERAD guidelines. Together these findings validate and expand CNN models to be robust to cohort variations and provide additional proof-of-concept for future studies to incorporate machine learning algorithms into neuropathological practice

Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline.

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline that identifies specific neuropathologies-amyloid plaques and cerebral amyloid angiopathy-in immunohistochemically-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotate > 70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieve strong plaque classification on a 10-WSI hold-out set (0.993 and 0.743 areas under the receiver operating characteristic and precision recall curve, respectively). Prediction confidence maps visualize morphology distributions at high resolution. Resulting network-derived amyloid beta (Aβ)-burden scores correlate well with established semi-quantitative scores on a 30-WSI blinded hold-out. Finally, saliency mapping demonstrates that networks learn patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologist's ability suggests a route to neuropathologic deep phenotyping

Parametrized spaces model locally constant homotopy sheaves

We prove that the homotopy theory of parametrized spaces embeds fully and faithfully in the homotopy theory of simplicial presheaves, and that its essential image consists of the locally homotopically constant objects. This gives a homotopy-theoretic version of the classical identification of covering spaces with locally constant sheaves. We also prove a new version of the classical result that spaces parametrized over X are equivalent to spaces with an action of the loop space of X. This gives a homotopy-theoretic version of the correspondence between covering spaces over X and sets with an action of the fundamental group of X. We then use these two equivalences to study base change functors for parametrized spaces.Comment: 26 pages; exposition improve

CHARACTERISTICS OF SANDHILL CRANE ROOSTS IN THE SACRAMENTO-SAN JOAQUIN DELTA OF CALIFORNIA

The Sacramento-San Joaquin Delta (Delta) region of California is an important wintering region for 2 subspecies of Pacific Flyway sandhill cranes (Grus canadensis): the Central Valley Population of the greater sandhill crane (G. c. tabida) and the Pacific Flyway Population of the lesser sandhill crane (G. c. canadensis). During the winters of 2007-08 and 2008-09 we conducted roost counts, roadside surveys, aerial surveys, and tracked radio-marked birds to locate and assess important habitats for roosting cranes in the Delta. Of the 69 crane night roosts we identified, 35 were flooded cropland sites and 34 were wetland sites. We found that both larger individual roost sites and larger complexes of roost sites supported larger peak numbers of cranes. Water depth used by roosting cranes averaged 10 cm (range 3-21 cm, mode 7 cm) and was similar between subspecies. We found that cranes avoided sites that were regularly hunted or had high densities of hunting blinds. We suggest that managers could decide on the size of roost sites to provide for a given crane population objective using a ratio of 1.5 cranes/ha. The fact that cranes readily use undisturbed flooded cropland sites makes this a viable option for creation of roost habitat. Because hunting disturbance can limit crane use of roost sites we suggest these 2 uses should not be considered readily compatible. However, if the management objective of an area includes waterfowl hunting, limiting hunting to low blind densities and restricting hunting to early morning may be viable options for creating a crane-compatible waterfowl hunt program

Accelerated aging of solid lubricants for the W76-1 TSL : effects of polymer outgassing.

The behavior of MoS{sub 2} lubricants intended for the W76-1 TSL was evaluated after 17 and 82 thermal cycles, each lasting seven days and including a low temperature of -35 C and a high temperature of 93 C, in a sealed container containing organic materials. The MoS{sub 2} was applied by tumbling with MoS{sub 2} powder and steel pins (harperized), or by spraying with a resin binder (AS Mix). Surface composition measurements indicated an uptake of carbon and silicon on the lubricant surfaces after aging. Oxidation of the MoS{sub 2} on harperized coupons, where enough MoS{sub 2} was present at the surface to result in significant Mo and S concentrations, was found to be minimal for the thermal cycles in an atmosphere of primarily nitrogen. Bare steel surfaces showed a reduction in friction for exposed coupons compared to control coupons stored in nitrogen, at least for the initial cycles of sliding until the adsorbed contaminants were worn away. Lubricated surfaces showed no more than a ten percent increase in steady-state friction coefficient after exposure. Initial coefficient of friction was up to 250 percent higher than steady-state for AS Mix films on H950 coupons after 82 thermal cycles. However, the friction coefficient exhibited by lubricated coupons was never greater than 0.25, and more often less than 0.15, even after the accelerated aging exposures

Pseudoscalar and Scalar Meson Photoproduction Interpreted by Regge Phenomenology

We have evaluated pseudoscalar and scalar neutral pion photoproduction in $\vec{\gamma}p\to\pi^0p$ and $\vec{\gamma}p\to a_0^0p$ above the resonance region and within Regge phenomenology. Our fit, including GlueX $\Sigma$ pseudoscalar photoproduction data, shows that previous SLAC $\Sigma$ measurements for $\vec{\gamma}p \to \pi^0p$ above $E_\gamma = 4~\mathrm{GeV}$ are at variance with SLAC data with more recent measurements made by GlueX in vicinity of $E_\gamma = 9~\mathrm{GeV}$. The Regge model predicts that the beam polarization asymmetry $\Sigma$ of the scalar meson is opposite to that of pseudoscalar meson photoproduction, however, the cross sections are similar. While the vector natural parity meson exchange is dominant in both cases, the contribution of the pseudovector unnatural parity meson exchange is very small. Using Regge phenomenology, we predicted high energy behavior for double polarized observables $\mathbb{E}$, $\mathbb{F}$, $\mathbb{G}$, and $\mathbb{H}$ for the reactions $\gamma p\to \pi^0p$ and $\gamma p\to a_0^0p$.Comment: 8 pages, 5 figures, several small glitches were fixe

Mechanics and tribology of MEMS materials.

Micromachines have the potential to significantly impact future weapon component designs as well as other defense, industrial, and consumer product applications. For both electroplated (LIGA) and surface micromachined (SMM) structural elements, the influence of processing on structure, and the resultant effects on material properties are not well understood. The behavior of dynamic interfaces in present as-fabricated microsystem materials is inadequate for most applications and the fundamental relationships between processing conditions and tribological behavior in these systems are not clearly defined. We intend to develop a basic understanding of deformation, fracture, and surface interactions responsible for friction and wear of microelectromechanical system (MEMS) materials. This will enable needed design flexibility for these devices, as well as strengthen our understanding of material behavior at the nanoscale. The goal of this project is to develop new capabilities for sub-microscale mechanical and tribological measurements, and to exercise these capabilities to investigate material behavior at this size scale

Elementary Classroom Teachers’ Self-Reported Use of Movement Integration Products and Perceived Facilitators and Barriers Related to Product Use

Movement integration (MI) products are designed to provide children with physical activity during general education classroom time. The purpose of this study was to examine elementary classroom teachers’ self-reported use of MI products and subsequent perceptions of the facilitators of and barriers to MI product use. This study utilized a mixed-methods design. Elementary classroom teachers (n = 40) at four schools each tested four of six common MI products in their classroom for one week. Teachers completed a daily diary, documenting duration and frequency of product use. Following each product test, focus groups were conducted with teachers to assess facilitators and barriers. MI product use lasted for 11.2 (Standard Deviation (SD) = 7.5) min/occasion and MI products were used 4.1 (SD = 3.5) times/week on average. Activity Bursts in the Classroom for Fitness, GoNoodle, and Physical Activity Across the Curriculum were most frequently used. Facilitators of and barriers to MI product use were identified within three central areas—logistics, alignment with teaching goals, and student needs and interests. Teachers were receptive to MI products and used them frequently throughout the week. When considering the adoption of MI products, teachers, administrators, and policy makers should consider products that are readily usable, align with teaching goals, and are consistent with student needs and interests

Input Subsidies to Improve Smallholder Maize Productivity in Malawi: Toward an African Green Revolution

Recent hikes in food prices have created economic and social turmoil in many African countries. But in Malawi, fertilizer and seed subsidies have enabled small-scale farmers to improve maize productivity and achieve food security