38,138 research outputs found
Size of hippocampal pyramidal neurons in schizophrenia
Background Meta-analyses of
hippocampal size have indicated thatthis
structure is smaller in schizophrenia.This
could reflect a reductioninthe size of
constituent neurons or a reduced number
of neurons.
Aims To measure the size of
hippocampalpyramidalneuronsinthe hippocampalpyramidalneurons inthe
brains of peoplewith andwithout
schizophrenia.
Method Pyramidalneuron size in
hippocampal subfieldswas estimated
stereologically fromsections taken at
5mmintervals throughoutthewhole
length of right and left hippocampi from
andleft the brains of13 peoplewith schizophrenia
and16 controls.Resultswere assessed
using repeated-measures analysis of
covariance looking for amain effectof
diagnosis and gender, andinteractions of
and interactions thesewith side.
Results Wewere unable to detect
significantdifferences related to diagnosis,
gender or side for any hippocampal
subfield for this series of cases.
Conclusions For this series of brains,
hippocampal cell size is unchangedin
schizophrenia
An enhanced SWAT wetland module to quantify hydraulic interactions between riparian depressional wetlands, rivers and aquifers
This study develops a modified version of the Soil and Water Assessment Tool (SWAT) designed to better represent riparian depressional wetlands (SWATrw). It replaces existing unidirectional hydrological interactions between a wetland and a river/aquifer with a more robust bidirectional approach based on hydraulic principles. SWATrw incorporates a more flexible wetland morphometric formula and a connecting channel concept to model wetland-river interactions. SWAT and SWATrw were tested for the Barak-Kushiyara River Basin (Bangladesh and India). Although the two models showed small differences in simulated stream flow, SWATrw outperformed SWAT in reproducing river stages and the pre-monsoon river-spills into riparian wetlands. SWATrw showed that the observed presence of dry season water in the wetland was due to reduced seepage to the local groundwater table whilst continuous seepage simulated by SWAT resulted in the wetland drying out completely. The new model therefore more closely simulates the hydrological interactions between wetlands, rivers and groundwater
Hydrological impacts of climate change on rice cultivated riparian wetlands in the Upper Meghna River Basin (Bangladesh and India)
Riparian depressional wetlands (haors) in the Upper Meghna River Basin of Bangladesh are invaluable agricultural resources. They are completely flooded between June and November and planted with Boro rice when floodwater recedes in December. However, early harvest period (April/May) floods frequently damage ripening rice. A calibrated/validated Soil and Water Assessment Tool for riparian wetland (SWATrw) model is perturbed with bias free (using an improved quantile mapping approach) climate projections from 17 general circulation models (GCMs) for the period 2031–2050. Projected mean annual rainfall increases (200–500 mm or 7–10%). However, during the harvest period lower rainfall (21–75%) and higher evapotranspiration (1–8%) reduces river discharge (5–18%) and wetland inundation (inundation fraction declines of 0.005–0.14). Flooding risk for Boro rice consequently declines (rationalized flood risk reductions of 0.02–0.12). However, the loss of cultivable land (15.3%) to increases in permanent haor inundation represents a major threat to regional food security
Hypoxia Inducible Factor-Stabilizing Bioactive Glasses for Directing Mesenchymal Stem Cell Behavior.
Uptake of systematic reviews and meta-analyses based on individual participant data in clinical practice guidelines: descriptive study.
To establish the extent to which systematic reviews and meta-analyses of individual participant data (IPD) are being used to inform the recommendations included in published clinical guidelines
Evaluation of Decentralized Event-Triggered Control Strategies for Cyber-Physical Systems
Energy constraint long-range wireless sensor/ actuator based solutions are theoretically the perfect choice to support the next generation of city-scale cyber-physical systems. Traditional systems adopt periodic control which increases network congestion and actuations while burdens the energy consumption. Recent control theory studies overcome these problems by introducing aperiodic strategies, such as event trigger control. In spite of the potential savings, these strategies assume actuator continuous listening while ignoring the sensing energy costs. In this paper, we fill this gap, by enabling sensing and actuator listening duty-cycling and proposing two innovative MAC protocols for three decentralized event trigger contro l approaches. A laboratory experimental testbed, which emulates a smart water network, was modelled and extended to evaluate the impact of system parameters and the performance of each approach. Experimental results reveal the predominance of the decentralized event-triggered control against the classic periodic control either in terms of communication or actuation by promising significant system lifetime extension
Learning SO(3) Equivariant Representations with Spherical CNNs
We address the problem of 3D rotation equivariance in convolutional neural
networks. 3D rotations have been a challenging nuisance in 3D classification
tasks requiring higher capacity and extended data augmentation in order to
tackle it. We model 3D data with multi-valued spherical functions and we
propose a novel spherical convolutional network that implements exact
convolutions on the sphere by realizing them in the spherical harmonic domain.
Resulting filters have local symmetry and are localized by enforcing smooth
spectra. We apply a novel pooling on the spectral domain and our operations are
independent of the underlying spherical resolution throughout the network. We
show that networks with much lower capacity and without requiring data
augmentation can exhibit performance comparable to the state of the art in
standard retrieval and classification benchmarks.Comment: Camera-ready. Accepted to ECCV'18 as oral presentatio
An algorithm for diagnosing IgE-mediated food allergy in study participants who do not undergo food challenge.
BACKGROUND: Food allergy diagnosis in clinical studies can be challenging. Oral food challenges (OFC) are time-consuming, carry some risk and may, therefore, not be acceptable to all study participants. OBJECTIVE: To design and evaluate an algorithm for detecting IgE-mediated food allergy in clinical study participants who do not undergo OFC. METHODS: An algorithm for trial participants in the Barrier Enhancement for Eczema Prevention (BEEP) study who were unwilling or unable to attend OFC was developed. BEEP is a pragmatic, multi-centre, randomized-controlled trial of daily emollient for the first year of life for primary prevention of eczema and food allergy in high-risk infants (ISRCTN21528841). We built on the European iFAAM consensus guidance to develop a novel food allergy diagnosis algorithm using available information on previous allergenic food ingestion, food reaction(s) and sensitization status. This was implemented by a panel of food allergy experts blind to treatment allocation and OFC outcome. We then evaluated the algorithm's performance in both BEEP and Enquiring About Tolerance (EAT) study participants who did undergo OFC. RESULTS: In 31/69 (45%) BEEP and 44/55 (80%) EAT study control group participants who had an OFC the panel felt confident enough to categorize children as "probable food allergy" or "probable no food allergy". Algorithm-derived panel decisions showed high sensitivity 94% (95%CI 68, 100) BEEP; 90% (95%CI 72, 97) EAT and moderate specificity 67% (95%CI 39, 87) BEEP; 67% (95%CI 39, 87) EAT. Sensitivity and specificity were similar when all BEEP and EAT participants with OFC outcome were included. CONCLUSION: We describe a new algorithm with high sensitivity for IgE-mediated food allergy in clinical study participants who do not undergo OFC. CLINICAL RELEVANCE: This may be a useful tool for excluding food allergy in future clinical studies where OFC is not conducted
Common carp (Cyprinus carpio L.) alters its feeding niche in response to changing food resources: direct observations in simulated ponds
We used customized fish tanks as model fish ponds to observe grazing, swimming, and conspecific social behavior of common carp (Cyprinus carpio) under variable food-resource conditions to assess alterations in feeding niche. Different food and feeding situations were created by using only pond water or pond water plus pond bottom sediment or pond water plus pond bottom sediment and artificial feeding. All tanks were fertilized twice, prior to stocking and 2 weeks later after starting the experiment to stimulate natural food production. Common carp preferred artificial feed over benthic macroinvertebrates, followed by zooplankton. Common carp did not prefer any group of phytoplankton in any treatment. Common carp was mainly benthic in habitat choice, feeding on benthic macroinvertebrates when only plankton and benthic macroinvertebrates were available in the system. In the absence of benthic macroinvertebrates, their feeding niche shifted from near the bottom of the tanks to the water column where they spent 85% of the total time and fed principally on zooplankton. Common carp readily switched to artificial feed when available, which led to better growth. Common carp preferred to graze individually. Behavioral observations of common carp in tanks yielded new information that assists our understanding of their ecological niche. This knowledge could be potentially used to further the development of common carp aquaculture
Coupled-cluster theory of a gas of strongly-interacting fermions in the dilute limit
We study the ground-state properties of a dilute gas of strongly-interacting
fermions in the framework of the coupled-cluster expansion (CCE). We
demonstrate that properties such as universality, opening of a gap in the
excitation spectrum and applicability of s-wave approximations appear naturally
in the CCE approach. In the zero-density limit, we show that the ground-state
energy density depends on only one parameter which in turn may depend at most
on the spatial dimensionality of the system.Comment: 7 figure
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