Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioral / Systems / Cognitive Respiratory Rhythm Entrainment by Somatic Afferent Stimulation

Respiratory and locomotor patterns are coupled during locomotion. The objectives of this study were to (1) demonstrate that respiratory rhythms are entrained by sensory input from somatic afferents, (2) establish whether the parabrachial nucleus mediates entrainment, (3) examine responses of single respiratory neurons in the ventral respiratory group (VRG) to somatic afferent stimulation, and (4) use a computational model of the pontomedullary respiratory network (Rybak et al., 2004a,b) to suggest neuronal mechanisms for entrainment. We used an in situ preparation in young rats that retained pontomedullary respiratory circuits and spinal pathways transmitting somatosensory input. We demonstrate that rhythmic stimulation of somatic afferents entrains respiratory rhythm on a 1:1 basis (1:1), increasing breathing frequency up to 1.4 –2.2 times greater than spontaneous frequency. Stable entrainment occurred only when stimuli were delivered during expiration. Reversible blockade of the lateral parabrachial nucleus eliminated entrainment. Somatic afferent stimulation produced significant increases in the firing rate of augmenting expiratory (E2) neurons but shortened the firing duration of postinspiratory (post-I) neurons. A computational model reproduced 1:1 entrainment and other experimental findings based on the assumption that the somatic afferents initiate early onset of inspiration via activation of medullary E2 neurons. The model also predicted that afferent stimulation evoked transient hyperpolarization of ramp-inspiratory (ramp-I) neurons. This was confirmed experimentally by intracellular recording from ramp-I neurons. Our experimental and modeling results demonstrate that an entrainment pathway from somatic afferents to the VRG via the lateral parabrachial nucleus causes resetting of respiratory rhythm through excitation of E2 and consequent inhibition of post-I neurons.
Joint Book Reading Makes for Success in Learning to Read: A Meta-Analysis on Intergenerational Transmission of Literacy

The current review is a quantitative meta-analysis of the available empirical evidence related to parent-preschooler reading and several outcome measures. In selecting the studies to be included in this meta-analysis, we focused on studies examining the frequency of book reading to preschoolers. The results support the hypothesis that parent-preschooler reading is related to outcome measures such as language growth, emergent literacy, and reading achievement. The overall effect size of d = . 59 indicates that book reading explains about 8% of the variance in the outcome measures. The results support the hypothesis that book reading, in particular, affects acquisition of the written language register. The effect of parent-preschooler reading is not dependent on the socioeconomic status of the families or on several methodological differences between the studies. However, the effect seems to become smaller as soon as children become conventional readers and are able to read on their own.
Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net

In this paper we propose a novel deep neural network that is able to jointly reason about 3D detection, tracking and motion forecasting given data captured by a 3D sensor. By jointly reasoning about these tasks, our holistic approach is more robust to occlusion as well as sparse data at range. Our approach performs 3D convolutions across space and time over a bird's eye view representation of the 3D world, which is very efficient in terms of both memory and computation. Our experiments on a new very large scale dataset captured in several north american cities, show that we can outperform the state-of-the-art by a large margin. Importantly, by sharing computation we can perform all tasks in as little as 30 ms.
Sensitivity Analysis and Calibration of Hydrological Modeling of the Watershed Northeast Brazil

Mathematical models of the quantity and quality of water in hydrographic basins enable simulation of a wide variety of processes, including the production of water and sediments, and the dynamics of point and nonpoint sources of pollution. These models have become increasingly complex, requiring large amounts of input data, which can increase the uncertainty of the results of simulations. For this reason, it is essential to perform calibration and validation procedures. The objective of this work was to conduct sensitivity analysis and calibration of a distributed hydrological model (SWAT) applied to the flows of water in the watershed of the Poxim River. Satisfactory performance of the model was indicated by the values obtained for the Nash-Sutcliffe efficiency coefficient (0.77), the percent bias (5.05), the root mean square error (0.48), and the ratio of the RMSE to the standard deviation of the observations (RSR) (0.49). The set of parameters identified here could be used for the simulation and evaluation of other scenarios.
Meaning guides attention in real-world scene images: Evidence from eye movements and meaning maps

We compared the influences of meaning and salience on attentional guidance in scene images. Meaning was captured by “meaning maps” representing the spatial distribution of semantic information in scenes. Meaning maps were coded in a format that could be directly compared to maps of image salience generated from image features. We investigated the degree to which meaning versus image salience predicted human viewers’ spatial distribution of attention over scenes, with attention operationalized as duration-weighted fixation density. The results showed that both meaning and salience predicted the distribution of attention, but that when the correlation between meaning and salience was statistically controlled, meaning accounted for unique variance in attention but salience did not. This pattern was observed for early as well as late fixations, for fixations following short as well as long saccades, and for fixations including or excluding the centers of the scenes. The results strongly suggest that meaning guides attention in real world scenes. We discuss the results from the perspective of a cognitive relevance theory of attentional guidance in scenes.
New insights on facultative parthenogenesis in pythons

In vertebrates, facultative parthenogenesis (i.e. asexual reproduction by a sexually reproducing species) has been documented in four diverse taxonomic groups, namely sharks, birds, lizards, and snakes. With a single exception, the mode is terminal fusion automixis, where the second polar body fuses with the nucleus of the gamete, restoring diploidy and triggering cell division. The deviating case involves a report of a captive Burmese python (Python bivittatus), a giant Asiatic species common in zoological gardens and the pet trade. Although terminal fusion automixis produces half-clones of the mother, under this unique case in P. bivittatus, the foetuses were reported as full clones. This conclusion is an apparent anomaly with respect to the mechanism of facultative parthenogenesis reported in all other snakes. In the present study, using genotyping methods, we analyze facultative parthenogenesis in two other species of pythonids and report results that challenge the abovementioned conclusions regarding clonality. Specifically, we report new findings comparable to those reported in other primitive snakes (namely boids), which support the hypothesis of terminal fusion automixis as the mode of facultative parthenogenesis. Furthermore, in light of our new data, we re-examine the previous report of facultative parthenogenesis in the Burmese python and suggest an intriguing alternative explanation for the earlier findings. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 112, 461–468.
How to overcome health-compromising behaviors: The health action process approach

Health-compromising behaviors such as cigarette smoking and poor dietary habits are difficult to change. Most social-cognitive theories assume that the intention to change is the best predictor of actual change, but people often do not behave in accordance with their intentions. Unforeseen barriers emerge, or people give in to temptations. Therefore, intentions should be supplemented by more proximal predictors that might facilitate the translation of intentions into action. Some self-regulatory mediators have been identified, such as perceived self-efficacy and strategic planning. They help to bridge the intention-behavior gap. The Health Action Process Approach (HAPA) suggests a distinction between (1) a preintentional motivation process that leads to a behavioral intention and (2) a postintentional volition process that facilitates the adoption and maintenance of health behaviors. In this article, two studies are reported that examine mediators between intentions and two behaviors. One behavior is smok.
Perceptions of Safe Water and Accessibility by Rural Farming Communities Residing Along the Fringes of the Okavango Delta , Botswana

Globally, access to safe water for domestic use is a key social development indicator promoting health and enhancing national development. About 1 in 10 people are without access to safe water with Sub Saharan Africa facing greater challenges. Botswana, a semi-arid country, is not an exception to these challenges. Existing research has focused on water supply issues, physico-chemical properties and the effects of human activities on water quality but with little attention given to the community residents’ perceptions on accessibility of safe water. The study objective is to assess the community perceptions of safe water and accessibility amongst rural farmers of Ngamiland district. This is a descriptive cross-sectional study that uses data from socio-economic survey (SES) conducted between July and August of 2010, Participatory Rural Appraisal (PRA) workshop reports from 2010-2012 and unobtrusive field observations by authors to assess the flood recession “molapo” farming communities’ perceptions of safe water and accessibility. A total of 161 farmers from Tubu, Xobe, and Shorobe that participated in the SES Survey are the ones being assessed in the current study. In order to investigate factors influencing safe water access, binary logistic regression model was fitted to some socio-economic and environmental variables. Results were reported using descriptive frequencies. Almost 80% of rural farming participants’ perceived water from all sources, improved and unimproved to be safe and adequate. Perceptions of water accessibility, availability and safety changed with 2010 showing satisfaction and 2012 dissatisfaction with these aspects. There is a significantly strong relationship between source of domestic water and communities (The contingency coefficient, r =0.707, p< 0.05). Number of people in a household is a significant predictor of access to safe water (p < 0.05). People who hold the view that molapo farming has potential to cause water borne disease and that molapo farming can be potential health hazard are, respectively, 1.25 and 1.71 times more likely to access safe water than those holding contrary views. Results further reveal that those who think that drinking water directly from a stream /river can cause diarrheal diseases are less likely to access safe water (OR= 0.542). Rural farmers largely perceive the water they use for domestic purposes to be safe regardless of whether source is improved or unimproved, adequate and accessible. Farmers do not seem to link drinking water directly from unimproved sources as a potential cause of diarrheal diseases. Additionally, they do not think improved sources such as taps and communal standpipes help with accessibility to safe water probably because of their frequent malfunction and dryness. Public education is encouraged to promote community awareness of contamination of all water sources whether improved and/ or non-improved.
Shrimp ponds lead to massive loss of soil carbon and greenhouse gas emissions in northeastern Brazilian mangroves

Abstract Mangroves of the semiarid Caatinga region of northeastern Brazil are being rapidly converted to shrimp pond aquaculture. To determine ecosystem carbon stocks and potential greenhouse gas emissions from this widespread land use, we measured carbon stocks of eight mangrove forests and three shrimp ponds in the Acaraú and Jaguaribe watersheds in Ceará state, Brazil. The shrimp ponds were paired with adjacent intact mangroves to ascertain carbon losses and potential emissions from land conversion. The mean total ecosystem carbon stock of mangroves in this semiarid tropical landscape was 413 ± 94 Mg C/ha. There were highly significant differences in the ecosystem carbon stocks between the two sampled estuaries suggesting caution when extrapolating carbon stock across different estuaries even in the same landscape. Conversion of mangroves to shrimp ponds resulted in losses of 58%–82% of the ecosystem carbon stocks. The mean potential emissions arising from mangrove conversion to shrimp ponds was 1,390 Mg CO2e/ha. Carbon losses were largely from soils which accounted for 81% of the total emission. Losses from soils >100 cm in depth accounted for 33% of the total ecosystem carbon loss. Soil carbon losses from shrimp pond conversion are equivalent to about 182 years of soil carbon accumulation. Losses from mangrove conversion are about 10‐fold greater than emissions from conversion of upland tropical dry forest in the Brazilian Caatinga underscoring the potential value for their inclusion in climate change mitigation activities.
Deep Hybrid Real and Synthetic Training for Intrinsic Decomposition

Intrinsic image decomposition is the process of separating the reflectance and shading layers of an image, which is a challenging and underdetermined problem. In this paper, we propose to systematically address this problem using a deep convolutional neural network (CNN). Although deep learning (DL) has been recently used to handle this application, the current DL methods train the network only on synthetic images as obtaining ground truth reflectance and shading for real images is difficult. Therefore, these methods fail to produce reasonable results on real images and often perform worse than the non-DL techniques. We overcome this limitation by proposing a novel hybrid approach to train our network on both synthetic and real images. Specifically, in addition to directly supervising the network using synthetic images, we train the network by enforcing it to produce the same reflectance for a pair of images of the same real-world scene with different illuminations. Furthermore, we improve the results by incorporating a bilateral solver layer into our system during both training and test stages. Experimental results show that our approach produces better results than the state-of-the-art DL and non-DL methods on various synthetic and real datasets both visually and numerically.
Dense registration of fi ngerprints

Dense registration of different impressions of the same finger is beneficial to various fingerprint matching methods. This is a challenging problem due to elastic distortion of finger skin and sparsity of distinctive features (namely minutiae) in fingerprints. Most existing fingerprint registration algorithms produce only correspondences between minutiae, which are not sufficient for dense registration of fingerprints. In this paper, we proposed a novel dense fingerprint registration algorithm, which consists of a composite initial registration step and a dual-resolution block-based registration step. The dualresolution block-based registration is approached in an energy minimization framework which consists of local search, energy function construction and global optimization. In local search step, a candidate set of transformations of every input image block are found using image correlation w.r. t. the corresponding reference image block. In energy function construction, two factors are considered: (1) the similarity between the transformed input block and the corresponding reference block, and (2) the compatibility between transformations of neighboring input blocks. In global optimization, a region growing style algorithm is proposed to minimize the energy function. Experimental results on three databases containing many distorted fingerprints, namely FVC2004 DB1, Tsinghua Distorted Fingerprint database and NIST SD27 latent fingerprint database, show that the proposed algorithm not only produces more accurate registration results but also improves the matching performance by fusion of minutiae matching and image correlation. & 2016 Elsevier Ltd. All rights reserved.
The Impact of Historical Land-Use Changes on the Near-Surface Atmospheric Conditions on the Swiss Plateau

The effects of historical land-use changes on the Swiss Plateau on the near-surface atmospheric conditions of typical summer days in July were investigated in a case study. A mesoscale dynamical nonhydrostatic model with a horizontal resolution of 1 km 2 was used. Two simulations of historical (around 1850) and present conditions as well as six sensitivity experiments were conducted in order to assess the importance of changes in the physiological, morphological, and soil properties. The modeled daily average
Effects of soil fumigants on methanotrophic activity

Negative impacts on methane (CH4) oxidation capacity have already been observed for a variety of agronomic practices, but the effect of soil fumigation on CH4 oxidation has not been investigated. Fumigation is a common practice in agricultural crop and nursery seedling protection. Soils from various agricultural experiment stations, forest nurseries, and a landfill were evaluated for effects of 1,3-dichloropropene (1,3-D), methyl isothiocyanate (MITC), and chloropicrin (CP) on CH4 oxidation capacities. All three fumigants significantly reduced CH4 oxidation rates in historically non-fumigated soils (450%). 1,3-D enhanced CH4 oxidation in 3 out of 5 previously fumigated soils and MITC increased CH4 oxidation rates in all historically MITC-fumigated soils compared to controls. CP universally decreased oxidation capacity regardless of fumigation history. These results support the conclusion that CH4 oxidation effects are fumigant specific and that prior fumigation history plays a vital role in determining the impact on CH4 oxidizer community functionality, which may have implications on the global CH4 cycle. Published by Elsevier Ltd.
Deriving Global OH Abundance and Atmospheric Lifetimes for Long‐Lived Gases: A Search for CH3CCl3 Alternatives

An accurate estimate of global hydroxyl radical (OH) abundance is important for projections of air quality, climate, and stratospheric ozone recovery. As the atmospheric mixing ratios of methyl chloroform (CH3CCl3) (MCF), the commonly used OH reference gas, approaches zero, it is important to find alternative approaches to infer atmospheric OH abundance and variability. The lack of global bottom‐up emission inventories is the primary obstacle in choosing a MCF alternative. We illustrate that global emissions of long‐lived trace gases can be inferred from their observed mixing ratio differences between the Northern Hemisphere (NH) and Southern Hemisphere (SH), given realistic estimates of their NH‐SH exchange time, the emission partitioning between the two hemispheres, and the NH versus SH OH abundance ratio. Using the observed long‐term trend and emissions derived from the measured hemispheric gradient, the combination of HFC‐32 (CH2F2), HFC‐134a (CH2FCF3, HFC‐152a (CH3CHF2), and HCFC‐22 (CHClF2), instead of a single gas, will be useful as a MCF alternative to infer global and hemispheric OH abundance and trace gas lifetimes. The primary assumption on which this multispecies approach relies is that the OH lifetimes can be estimated by scaling the thermal reaction rates of a reference gas at 272 K on global and hemispheric scales. Thus, the derived hemispheric and global OH estimates are forced to reconcile the observed trends and gradient for all four compounds simultaneously. However, currently, observations of these gases from the surface networks do not provide more accurate OH abundance estimate than that from MCF.
Long term effect of a school based intervention to prevent chronic diseases in Tunisia, 2009–2015

Background & Objectives We aimed to evaluate the long term effect of school based intervention to prevent non- communicable disease risk factors. Methods It was a quasi experimental study conducted during the period of 2009–2015. We involved school children aged from 11 to 16 years old. For the assessment of the program's effectiveness, subjects in both groups were examined at baseline, at the end of the 3-year intervention period and at the follow-up, one year after program's cessation. Results In the intervention group, the prevalence of school children who reported to be eating 5 fruits and vegetable sdaily increased significantly from 30.0% at pre-assessment to 33.2% at post-assessment, one year after (p=0.02, p=0.41 respectively). For the control group, this prevalence had significantly decreased from 40.2% at baseline to 35.0% at post-intervention, at the follow up, this proportion increased to 44.5%(p=0.001, p<10−3 respectively). Concerning smoking habits, we observed a decreasing trend in the intervention group from 5.7% at pre-assessment, to 4.8% at post-assessment and to 3.4% at the follow-up (p=0.19 and p=0.25 respectively). There was also a significant decrease in school children who did recommended physical activity in the same group. Conclusion The present work showed that interventions promoting healthy lifestyles should be maintained. Developing countries should be encouraged and supported to design, conduct, and evaluate robust preventive interventions.
Three‐dimensional digitization of the arid land plant Haloxylon ammodendron using a consumer‐grade camera

Abstract Plant structural parameters are important for ecological studies and for monitoring the environment. Terrestrial laser scanning has become a widely accepted technique for acquiring accurate high‐density three‐dimensional information about plant surfaces; however, this instrument is expensive, technically challenging to operate, heavy, and difficult to transport to hard‐to‐reach areas such as dense forests and undeveloped areas without easy vehicle access. Using Haloxylon ammodendron, a plant widely distributed in arid lands, as an example, we used a consumer‐grade handheld camera to take a series of overlapping images of this plant. Computer vision and photogrammetric software were used to reconstruct highly detailed three‐dimensional data of the plant surface. This surface data was compared to the point cloud of the plant acquired from concomitant terrestrial laser scanning. We demonstrated that the accuracy and degree of completeness of the image‐derived point clouds are comparable to that of laser scanning. Plant structural parameters (such as tree height and crown width) and three‐dimensional models extracted from the point clouds also agree well with a relative difference of less than 5%. Our case study shows that a common camera and image processing software can be an affordable, highly portable, and viable option for acquiring accurate and detailed high‐density and high‐resolution three‐dimensional information about plant structure in the environment. This digitization technique can record the plant and its surrounding environment effectively and efficiently, and it can be applied to many ecological fields and studies.