A Weakly Supervised Approach for Estimating Spatial Density Functions from High-Resolution Satellite Imagery

We propose a neural network component, the regional aggregation layer, that makes it possible to train a pixel-level density estimator using only coarse-grained density aggregates, which reflect the number of objects in an image region. Our approach is simple to use and does not require domain-specific assumptions about the nature of the density function. We evaluate our approach on several synthetic datasets. In addition, we use this approach to learn to estimate high-resolution population and housing density from satellite imagery. In all cases, we find that our approach results in better density estimates than a commonly used baseline. We also show how our housing density estimator can be used to classify buildings as residential or non-residential.Comment: 10 pages, 8 figures. ACM SIGSPATIAL 2018, Seattle, US

The Creation of the Catholic School Leadership Program at Seton Hall University

This article summarizes the development and implementation of a Catholic school leadership program at a diocesan university. Supported by university faculty as well as seminary faculty, this program offers a unique response to the training of future school leaders. The course work blends leadership theory, theology, and educational administration and is delivered via a cohort model

Energy Return Characteristics of EVA and E-TPU Midsoles During a Drop Jump

Expanded Thermoplastic Polyurethane (E-TPU) is a material used in shoe midsoles that has been described as having greater energy return than traditional Ethylene Vinyl-Acetate (EVA) midsole material. PURPOSE: The purpose of this study was to compare the landing and energy return characteristics of shoes using EVA and E-TPU midsoles. METHODS: Ten collegiate female athletes (19.7±1.0 yrs, 75.74±10.9 kg, 1.72±0.08 m) volunteered and provided informed consent to participate in this study. Participants performed five drop jumps from a height of 50 cm under two conditions; while wearing EVA midsole shoes and while wearing E-TPU midsole shoes. Peak force, rate of loading and impulse were measured from a Bertec force plate sampled at 1000 Hz during the initial landing phase of the drop jump. Coefficient of Restitution (COR) was determined by measuring the bounce height of a 1 in steel ball bearing dropped from a 1 m height onto the shoes. All measures were compared between midsole conditions using paired t-tests. RESULTS: Peak vertical force when landing with the EVA shoe (3265.6±554.2 N) was not different (p=0.19) than when landing with the E-TPU shoe (3406.6± 590.3 N). Similar rates of loading (p=0.71) were found for the EVA shoes (56106.3±9995.8 N/s) and the E-TPU shoes (54232.4±12167.0). Likewise impulse was not different (p=0.30) between the EVA shoe (710.5±177.7 Ns) and E-TPU shoe (693.9±162.6 Ns). However, COR was slightly higher (p=0.01) in the E-TPU shoe (0.67±.05) than the EVA shoe (0.66±0.02). CONCLUSION: The difference in COR values coupled with the similar landing characteristics observed for the different midsole materials may suggest that individuals are able to compensate for material differences by using different physiological strategies such as using different muscle stiffness during the landing phase depending on midsole material. Further testing to examine physiological measures during these movements is warranted

On computational irreducibility and the predictability of complex physical systems

Using elementary cellular automata (CA) as an example, we show how to coarse-grain CA in all classes of Wolfram's classification. We find that computationally irreducible (CIR) physical processes can be predictable and even computationally reducible at a coarse-grained level of description. The resulting coarse-grained CA which we construct emulate the large-scale behavior of the original systems without accounting for small-scale details. At least one of the CA that can be coarse-grained is irreducible and known to be a universal Turing machine.Comment: 4 pages, 2 figures, to be published in PR

Concurrent MEK targeted therapy prevents MAPK pathway reactivation during BRAFV600E targeted inhibition in a novel syngeneic murine glioma model.

Inhibitors of BRAFV600E kinase are currently under investigations in preclinical and clinical studies involving BRAFV600E glioma. Studies demonstrated clinical response to such individualized therapy in the majority of patients whereas in some patients tumors continue to grow despite treatment. To study resistance mechanisms, which include feedback activation of mitogen-activated protein kinase (MAPK) signaling in melanoma, we developed a luciferase-modified cell line (2341luc) from a BrafV600E mutant and Cdkn2a- deficient murine high-grade glioma, and analyzed its molecular responses to BRAFV600E- and MAPK kinase (MEK)-targeted inhibition. Immunocompetent, syngeneic FVB/N mice with intracranial grafts of 2341luc were tested for effects of BRAFV600E and MEK inhibitor treatments, with bioluminescence imaging up to 14-days after start of treatment and survival analysis as primary indicators of inhibitor activity. Intracranial injected tumor cells consistently generated high-grade glioma-like tumors in syngeneic mice. Intraperitoneal daily delivery of BRAFV600E inhibitor dabrafenib only transiently suppressed MAPK signaling, and rather increased Akt signaling and failed to extend survival for mice with intracranial 2341luc tumor. MEK inhibitor trametinib delivered by oral gavage daily suppressed MAPK pathway more effectively and had a more durable anti-growth effect than dabrafenib as well as a significant survival benefit. Compared with either agent alone, combined BRAFV600E and MEK inhibitor treatment was more effective in reducing tumor growth and extending animal subject survival, as corresponding to sustained MAPK pathway inhibition. Results derived from the 2341luc engraftment model application have clinical implications for the management of BRAFV600E glioma

Metabolic Profiling of IDH Mutation and Malignant Progression in Infiltrating Glioma.

Infiltrating low grade gliomas (LGGs) are heterogeneous in their behavior and the strategies used for clinical management are highly variable. A key factor in clinical decision-making is that patients with mutations in the isocitrate dehydrogenase 1 and 2 (IDH1/2) oncogenes are more likely to have a favorable outcome and be sensitive to treatment. Because of their relatively long overall median survival, more aggressive treatments are typically reserved for patients that have undergone malignant progression (MP) to an anaplastic glioma or secondary glioblastoma (GBM). In the current study, ex vivo metabolic profiles of image-guided tissue samples obtained from patients with newly diagnosed and recurrent LGG were investigated using proton high-resolution magic angle spinning spectroscopy (1H HR-MAS). Distinct spectral profiles were observed for lesions with IDH-mutated genotypes, between astrocytoma and oligodendroglioma histologies, as well as for tumors that had undergone MP. Levels of 2-hydroxyglutarate (2HG) were correlated with increased mitotic activity, axonal disruption, vascular neoplasia, and with several brain metabolites including the choline species, glutamate, glutathione, and GABA. The information obtained in this study may be used to develop strategies for in vivo characterization of infiltrative glioma, in order to improve disease stratification and to assist in monitoring response to therapy

Phenotypic integration of behavioural and physiological traits is related to variation in growth among stocks of Chinook salmon

The selection for a single organismal trait like growth in breeding programs of farmed aquaculture species can counterintuitively lead to lowered harvestable biomass. We outbred a domesticated aquaculture stock of Chinook salmon (Oncorhynchus tshawytscha (Walbaum in Artedi, 1792)) with seven wild stocks from British Columbia, Canada. We then examined how functionally related traits underlying energy management – diel variation in cortisol and foraging, social, and movement behaviours — predicted stock-level variation in growth during the freshwater life history stage, which is a performance metric under aquaculture selection. Outbreeding generated significant variation in diel cortisol secretion and behaviours across stocks, and these traits co-varied, suggesting tight integration despite hybridization. The coupling of nighttime cortisol exposure with the daytime behavioural phenotype was the strongest predictor of stock-level variation in body mass. Our results suggest that selection for an integrated phenotype rather than on a single mechanistic trait alone can generate the greatest effect on aquaculture fish growth under outbreeding practices. Furthermore, selecting for these traits at the stock level may increase efficiency of farming methods designed to consistently maximize fish performance on a large scale

Phenotypic integration of behavioural and physiological traits is related to variation in growth among stocks of Chinook salmon

The selection for a single organismal trait like growth in breeding programs of farmed aquaculture species can counter-intuitively lead to lowered harvestable biomass. We outbred a domesticated aquaculture stock of Chinook salmon (Oncorhynchus tshawytscha) with 7 wild stocks from British Columbia, Canada. We then examined how functionally related traits underlying energy management - diel variation in cortisol; foraging, social, and movement behaviours - predicted stock-level variation in growth during the freshwater life history stage, a performance metric under aquaculture selection. Outbreeding generated significant variation in diel cortisol secretion and behaviours across stocks, and these traits covaried, suggesting tight integration despite hybridization. The coupling of nighttime cortisol exposure with daytime behavioural phenotype was the strongest predictor of stock-level variation in body mass. Our results suggest selecting for an integrated phenotype rather than on single mechanistic traits alone can generate the greatest effect on aquaculture fish growth under outbreeding practices. Furthermore, selecting for these traits at the stock level may increase efficiency of farming methods designed to consistently maximize fish performance on a large scale