Immersive $$360^{\circ }$$ video user experience: impact of different variables in the sense of presence and cybersickness

Universal Access in the Information Society - Virtual Reality (VR) has been recently gaining interest from researchers and companies, contributing to the development of the associated technologies...     

A Nanostructuring Method to Decouple Electrical and Thermal Transport through the Formation of Electrically Triggered Conductive Nanofilaments

Transforming thermal energy into electric energy and vice versa needs the decoupling of electrical transport from thermal transport. An innovative strategy is proposed by forming/disrupting electrically triggered conductive nanofilaments within semiconducting thin films to switch thermoelectric properties between two states without further material modification and manufacturing processes. It can also controllably adjust the degree of decoupling, providing a potential resolution and performance adjustability for heat/coldness control or power consumption reduction on demand.     

Convolutional neural networks for computer vision-based detection and recognition of dumpsters

Neural Computing and Applications - In this paper, we propose a twofold methodology for visual detection and recognition of different types of city dumpsters, with minimal human labeling of the...     

Improving deep learning performance with missing values via deletion and compensation

Neural Computing and Applications - Missing values in a dataset is one of the most common difficulties in real applications. Many different techniques based on machine learning have been proposed...     

Forecasting hourly $${\hbox {NO}_{2}}$$ concentrations by ensembling neural networks and mesoscale models

In the framework of extreme pollution concentrations being more and more frequent in many cities nowadays, air quality forecasting is crucial to protect public health through the anticipation of unpopular measures like traffic restrictions. In this work, we develop the core of a 48 h ahead forecasting system which is being deployed for the city of Madrid. To this end, we investigate the predictive power of a set of neural network models, including several families of deep networks, applied to the task of predicting nitrogen dioxide concentrations in an urban environment. Careful feature engineering on a set of related magnitudes as meteorology and traffic has proven useful, and we have coupled these neural models with mesoscale numerical pollution forecasts, which improve precision by up to 10%. The experiments show that some neural networks and ensembles consistently outperform the reference models, particularly improving the Naive model’s results from around (20%) up to (57%) for longer forecasting horizons. However, results also reveal that deeper networks are not particularly better than shallow ones in this setting.

     

Convolutional neural networks for segmenting xylem vessels in stained cross-sectional images

Xylem is a vascular tissue that conducts sap (water and dissolved minerals) from the roots to the rest of the plant while providing physical support and resources. Sap is conducted within dead hollow cells (called vessels in flowering plants) arranged to form long pipes. Once formed, vessels do not change their structure and last from years to millennia. Vessels’ configuration (size, abundance, and spatial pattern) constitutes a record of the plant–environment relationship, and therefore, a tool for monitoring responses at the plant and ecosystem level. This information can be extracted through quantitative anatomy; however, the effort to identify and measure hundreds of thousands of conductive cells is an inconvenience to the progress needed to have solid assessments of the anatomical–environment relationship. In this paper, we propose an automatic methodology based on convolutional neural networks to segment xylem vessels. It includes a post-processing stage based on the use of redundant information to improve the performance of the outcome and make it useful in different sample configurations. Three different neural networks were tested obtaining similar results (pixel accuracy about 90%), which indicates that the methodology can be effectively used for segmentation of xylem vessels into images with non-homogeneous variations of illumination. The development of accurate automatic tools using CNNs would reduce the entry barriers associated with quantitative xylem anatomy expanding the use of this technique by the scientific community.

     

A cooperative protocol for pervasive underwater acoustic networks

Wireless Networks - The novel Underwater Wireless Sensor Network (UWSN) can contribute to monitor and explore aquatic environments. But, communicating in these environments is still hard and has...     

Comparison of the effects of dietary sunflower oil and virgin olive oil on rat exocrine pancreatic secretion <Emphasis Type="Italic">in vivo</Emphasis>

The aim of this study was to investigate the functional consequences in vivo of adapting the rat exocrine pancreas to different dietary fats. Weanling rats were fed diets containing 10 wt% virgin olive oil or sunflower oil for 8 wk. We then examined resting and cholecystokinin-octapeptide (CCK-8)-stimulated pancreatic secretion in the anesthetized animals. To confirm a direct influence of the type of fat upon the gland, the FA composition of pancreatic membranes as well as tissue protein and amylase content were determined in separate rats. The membrane FA profile was profoundly altered by the diets, reflecting the type of dietary fat given, although this was not paralleled by variations in the pancreatic content of protein or amylase. Nevertheless, dietary intake of oils evoked different effects on in vivo secretory activity. Resting flow rate and amylase output were significantly (P<0.05) enhanced by sunflower oil feeding. Time course changes in response to CCK-8 infusion also showed a different pattern in each group. Secretion of fluid, protein, and amylase increased markedly in all animals, reaching a maximum within 20–40 min of infusion that was followed by a dramatic decline in both groups. In the sunflower oil group, this resulted in values reaching the resting level as soon as 60 min after CCK-8 infusion was begun. However, after the initial decline, olive oil group values showed a prolonged plateau elevation above the baseline (P<0.05) that was maintained for at least the infusion time. In addition, a positive correlation between flow rate and both protein concentration and amylase activity existed in the olive oil group, but not in the sunflower oil group. The precise mechanism by which these effects are produced remains to be elucidated.     

Similarity of Cuticular Lipids Between a Caterpillar and Its Host Plant: A Way to Make Prey Undetectable for Predatory Ants?

Ithomiine butterflies (Nymphalidae) have long-lived, aposematic, chemically protected adults. However, little is known about the defense mechanisms in larvae and other juvenile stages. We showed that larvae Mechanitis polymnia are defended from ants by a chemical similarity between their cuticular lipids and those of the host plant, Solanum tabacifolium (Solanaceae). This is a novel defense mechanism in phytophagous insects. A field survey during one season showed that larval survivorship was up to 80%, which is high when compared with other juvenile stages. In a laboratory bioassay, live larvae on their host plant were not attacked by the predatory ant Camponotus crassus (Formicidae). Two experiments showed that the similarity between the cuticular lipids of M. polymnia and S. tabacifolium protected the larvae from C. crassus: (a) when the caterpillar was switched from a host plant to a non-host plant, the predation rate increased, and (b) when a palatable larva (Spodoptera frugiperda, Noctuidae) was coated with the cuticular lipids of M. polymnia and placed on S. tabacifolium leaves, it no longer experienced a high predation rate. This defensive mechanism can be defined as chemical camouflage, and may have a double adaptive advantage, namely, protection against predation and a reduction in the cost of sequestering toxic compounds from the host plant.