Combining Path Integration and Remembered Landmarks When Navigating without Vision

This study investigated the interaction between remembered landmark and path integration strategies for estimating current location when walking in an environment without vision. We asked whether observers navigating without vision only rely on path integration information to judge their location, or whether remembered landmarks also influence judgments. Participants estimated their location in a hallway after viewing a target (remembered landmark cue) and then walking blindfolded to the same or a conflicting location (path integration cue). We found that participants averaged remembered landmark and path integration information when they judged that both sources provided congruent information about location, which resulted in more precise estimates compared to estimates made with only path integration. In conclusion, humans integrate remembered landmarks and path integration in a gated fashion, dependent on the congruency of the information. Humans can flexibly combine information about remembered landmarks with path integration cues while navigating without visual information.National Institutes of Health (U.S.) (Grant T32 HD007151)National Institutes of Health (U.S.) (Grant T32 EY07133)National Institutes of Health (U.S.) (Grant F32EY019622)National Institutes of Health (U.S.) (Grant EY02857)National Institutes of Health (U.S.) (Grant EY017835-01)National Institutes of Health (U.S.) (Grant EY015616-03)United States. Department of Education (H133A011903

A densification mechanism to model the mechanical effect of methane hydrates in sandy sediments

Recent pore‐scale observations and geomechanical investigations suggest the lack of true cohesion in methane hydrate‐bearing sediments (MHBSs) and propose that their mechanical behavior is governed by kinematic constrictions at pore‐scale. This paper presents a constitutive model for MHBS, which does not rely on physical bonding between hydrate crystals and sediment grains but on the densification effect that pore invasion with hydrate has on the sediment mechanical properties. The Hydrate‐CASM extends the critical state model Clay and Sand Model (CASM) by implementing the subloading surface model and introducing the densification mechanism. The model suggests that the decrease of the sediment available void volume during hydrate formation stiffens its structure and has a similar mechanical effect as the increase of sediment density. In particular, the model attributes stress‐strain changes observed in MHBS to the variations in sediment available void volume with hydrate saturation and its consequent effect on isotropic yield stress and swelling line slope. The model performance is examined against published experimental data from drained triaxial tests performed at different confining stress and with distinct hydrate saturation and morphology. Overall, the simulations capture the influence of hydrate saturation in both the magnitude and trend of the stiffness, shear strength, and volumetric response of synthetic MHBS. The results are validated against those obtained from previous mechanical models for MHBS that examine the same experimental data. The Hydrate‐CASM performs similarly to previous models, but its formulation only requires one hydrate‐related empirical parameter to express changes in the sediment elastic stiffness with hydrate saturation

Parasitism of Lepidopterous Stem Borers in Cultivated and Natural Habitats

Plant infestation, stem borer density, parasitism, and parasitoid abundance were assessed during two years in two host plants, Zea mays (L.) (Cyperales: Poaceae) and Sorghum bicolor (L.) (Cyperales: Poaceae), in cultivated habitats. The four major host plants (Cyperus spp., Panicum spp., Pennisetum spp., and Sorghum spp.) found in natural habitats were also assessed, and both the cultivated and natural habitat species occurred in four agroecological zones in Kenya. Across habitats, plant infestation (23.2%), stem borer density (2.2 per plant), and larval parasitism (15.0%) were highest in maize in cultivated habitats. Pupal parasitism was not higher than 4.7% in both habitats, and did not vary with locality during each season or with host plant between each season. Cotesia sesamiae (Cameron) and C. flavipes Cameron (Hymenoptera: Braconidae) were the key parasitoids in cultivated habitats (both species accounted for 76.4% of parasitized stem borers in cereal crops), but not in natural habitats (the two Cotesia species accounted for 14.5% of parasitized stem borers in wild host plants). No single parasitoid species exerted high parasitism rates on stem borer populations in wild host plants. Low stem borer densities across seasons in natural habitats indicate that cereal stem borer pests do not necessarily survive the non-cropping season feeding actively in wild host plants. Although natural habitats provided refuges for some parasitoid species, stem borer parasitism was generally low in wild host plants. Overall, because parasitoids contribute little in reducing cereal stem borer pest populations in cultivated habitats, there is need to further enhance their effectiveness in the field to regulate these pests

Using an insect mushroom body circuit to encode route memory in complex natural environments

Ants, like many other animals, use visual memory to follow extended routes through complex environments, but it is unknown how their small brains implement this capability. The mushroom body neuropils have been identified as a crucial memory circuit in the insect brain, but their function has mostly been explored for simple olfactory association tasks. We show that a spiking neural model of this circuit originally developed to describe fruitfly (Drosophila melanogaster) olfactory association, can also account for the ability of desert ants (Cataglyphis velox) to rapidly learn visual routes through complex natural environments. We further demonstrate that abstracting the key computational principles of this circuit, which include one-shot learning of sparse codes, enables the theoretical storage capacity of the ant mushroom body to be estimated at hundreds of independent images

Identification of modifiable factors associated with owner-reported equine laminitis in Britain using a web-based cohort study approach

Equine laminitis is a complex disease that manifests as pain and lameness in the feet, often with debilitating consequences. There is a paucity of data that accounts for the multifactorial nature of laminitis and considers time-varying covariates that may be associated with disease development; particularly those that are modifiable and present potential interventions. A previous case-control study identified a number of novel, modifiable factors associated with laminitis which warranted further investigation and corroboration. The aim of this study was to identify factors associated with equine laminitis in horses/ponies in Great Britain (GB) using a prospective, web-based cohort study design, with particular interest in evaluating modifiable factors previously identified in the case-control study

PPARα Deficiency in Inflammatory Cells Suppresses Tumor Growth

Inflammation in the tumor bed can either promote or inhibit tumor growth. Peroxisome proliferator-activated receptor (PPAR)α is a central transcriptional suppressor of inflammation, and may therefore modulate tumor growth. Here we show that PPARα deficiency in the host leads to overt inflammation that suppresses angiogenesis via excess production of the endogenous angiogenesis inhibitor thrombospondin-1 and prevents tumor growth. Bone marrow transplantation and granulocyte depletion show that PPARα expressing granulocytes are necessary for tumor growth. Neutralization of thrombospondin-1 restores tumor growth in PPARα-deficient mice. These findings suggest that the absence of PPARα activity renders inflammatory infiltrates tumor suppressive and, thus, may provide a target for inhibiting tumor growth by modulating stromal processes, such as angiogenesis

Successful Cognitive Aging in Rats: A Role for mGluR5 Glutamate Receptors, Homer 1 Proteins and Downstream Signaling Pathways

Normal aging is associated with impairments in cognition, especially learning and memory. However, major individual differences are known to exist. Using the classical Morris Water Maze (MWM) task, we discriminated a population of 24-months old Long Evans aged rats in two groups - memory-impaired (AI) and memory-unimpaired (AU) in comparison with 6-months old adult animals. AI rats presented deficits in learning, reverse memory and retention. At the molecular level, an increase in metabotropic glutamate receptors 5 (mGluR5) was observed in post-synaptic densities (PSD) in the hippocampus of AU rats after training. Scaffolding Homer 1b/c proteins binding to group 1 mGluR facilitate coupling with its signaling effectors while Homer 1a reduces it. Both Homer 1a and 1b/c levels were up-regulated in the hippocampus PSD of AU animals following MWM task. Using immunohistochemistry we further demonstrated that mGluR5 as well as Homer 1b/c stainings were enhanced in the CA1 hippocampus sub-field of AU animals. In fact mGluR5 and Homer 1 isoforms were more abundant and co-localized in the hippocampal dendrites in AU rats. However, the ratio of Homer 1a/Homer 1b/c bound to mGluR5 in the PSD was four times lower for AU animals compared to AI rats. Consequently, AU animals presented higher PKCγ, ERK, p70S6K, mTOR and CREB activation. Finally the expression of immediate early gene Arc/Arg3.1 was shown to be higher in AU rats in accordance with its role in spatial memory consolidation. On the basis of these results, a model of successful cognitive aging with a critical role for mGluR5, Homer 1 proteins and downstream signalling pathways is proposed here

The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign - I. Overview and classification of candidates selected by two techniques

The primary goals of the STRong lensing Insights into the Dark Energy Survey (STRIDES) collaboration are to measure the dark energy equation of state parameter and the free streaming length of dark matter. To this aim, STRIDES is discovering strongly lensed quasars in the imaging data of the Dark Energy Survey and following them up to measure time delays, high resolution imaging, and spectroscopy sufficient to construct accurate lens models. In this paper, we first present forecasts for STRIDES. Then, we describe the STRIDES classification scheme, and give an overview of the Fall 2016 follow-up campaign. We continue by detailing the results of two selection methods, the Outlier Selection Technique and a morphological algorithm, and presenting lens models of a system, which could possibly be a lensed quasar in an unusual configuration. We conclude with the summary statistics of the Fall 2016 campaign. Including searches presented in companion papers (Anguita et al.; Ostrovski et al.), STRIDES followed up 117 targets identifying 7 new strongly lensed systems, and 7 nearly identical quasars (NIQs), which could be confirmed as lenses by the detection of the lens galaxy. 76 candidates were rejected and 27 remain otherwise inconclusive, for a success rate in the range 6-35\%. This rate is comparable to that of previous searches like SQLS even though the parent dataset of STRIDES is purely photometric and our selection of candidates cannot rely on spectroscopic information