Analyzing Digital Image by Deep Learning for Melanoma Diagnosis

Image classi cation is an important task in many medical applications, in order to achieve an adequate diagnostic of di erent le- sions. Melanoma is a frequent kind of skin cancer, which most of them can be detected by visual exploration. Heterogeneity and database size are the most important di culties to overcome in order to obtain a good classi cation performance. In this work, a deep learning based method for accurate classi cation of wound regions is proposed. Raw images are fed into a Convolutional Neural Network (CNN) producing a probability of being a melanoma or a non-melanoma. Alexnet and GoogLeNet were used due to their well-known e ectiveness. Moreover, data augmentation was used to increase the number of input images. Experiments show that the compared models can achieve high performance in terms of mean ac- curacy with very few data and without any preprocessing.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Unravelling the microphysics of polar mesospheric cloud formation

Polar mesospheric clouds are the highest water ice clouds occurring in the terrestrial atmosphere. They form in the polar summer mesopause, the coldest region in the atmosphere. It has long been assumed that these clouds form by heterogeneous nucleation on meteoric smoke particles which are the remnants of material ablated from meteoroids in the upper atmosphere. However, until now little was known about the properties of these nanometre-sized particles and application of the classical theory for heterogeneous ice nucleation was impacted by large uncertainties. In this work, we performed laboratory measurements on the heterogeneous ice formation process at mesopause conditions on small (r=1 to 3&thinsp;nm) iron silicate nanoparticles serving as meteoric smoke analogues. We observe that ice growth on these particles sets in for saturation ratios with respect to hexagonal ice below Sh=50, a value that is commonly exceeded during the polar mesospheric cloud season, affirming meteoric smoke particles as likely nuclei for heterogeneous ice formation in mesospheric clouds. We present a simple ice-activation model based on the Kelvin–Thomson equation that takes into account the water coverage of iron silicates of various compositions. The activation model reproduces the experimental data very well using bulk properties of compact amorphous solid water. This is in line with the finding from our previous study that ice formation on iron silicate nanoparticles occurs by condensation of amorphous solid water rather than by nucleation of crystalline ice at mesopause conditions. Using the activation model, we also show that for iron silicate particles with dry radius larger than r=0.6&thinsp;nm the nanoparticle charge has no significant effect on the ice-activation threshold.</p

Optical properties of meteoric smoke analogues

Accurate determination of the optical properties of analogues for meteoric smoke particles (MSPs), which are thought to be composed of iron-rich oxides or silicates, is important for their observation and characterization in the atmosphere. In this study, a photochemical aerosol flow system (PAFS) has been used to measure the optical extinction of iron oxide MSP analogues in the wavelength range 325–675 nm. The particles were made photochemically and agglomerate into fractal-like particles with sizes on the order of 100 nm. Analysis using transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS) suggested the particles were most likely maghemite-like (γ-Fe2O3) in composition, though a magnetite-like composition could not be completely ruled out. Assuming a maghemite-like composition, the optical extinction coefficients measured using the PAFS were combined with maghemite absorption coefficients measured using a complementary experimental system (the MICE-TRAPS) to derive complex refractive indices that reproduce both the measured absorption and extinction

Mechanisms underlying skeletal muscle insulin resistance induced by fatty acids: importance of the mitochondrial function

Insulin resistance condition is associated to the development of several syndromes, such as obesity, type 2 diabetes mellitus and metabolic syndrome. Although the factors linking insulin resistance to these syndromes are not precisely defined yet, evidence suggests that the elevated plasma free fatty acid (FFA) level plays an important role in the development of skeletal muscle insulin resistance. Accordantly, in vivo and in vitro exposure of skeletal muscle and myocytes to physiological concentrations of saturated fatty acids is associated with insulin resistance condition. Several mechanisms have been postulated to account for fatty acids-induced muscle insulin resistance, including Randle cycle, oxidative stress, inflammation and mitochondrial dysfunction. Here we reviewed experimental evidence supporting the involvement of each of these propositions in the development of skeletal muscle insulin resistance induced by saturated fatty acids and propose an integrative model placing mitochondrial dysfunction as an important and common factor to the other mechanisms

Fictitious play for cooperative action selection in robot teams

A game-theoretic distributed decision making approach is presented for the problem of control effort allocation in a robotic team based on a novel variant of fictitious play. The proposed learning process allows the robots to accomplish their objectives by coordinating their actions in order to efficiently complete their tasks. In particular, each robot of the team predicts the other robots' planned actions, while making decisions to maximise their own expected reward that depends on the reward for joint successful completion of the task. Action selection is interpreted as an n-player cooperative game. The approach presented can be seen as part of the Belief Desire Intention (BDI) framework, also can address the problem of cooperative, legal, safe, considerate and emphatic decisions by robots if their individual and group rewards are suitably defined. After theoretical analysis the performance of the proposed algorithm is tested on four simulation scenarios. The first one is a coordination game between two material handling robots, the second one is a warehouse patrolling task by a team of robots, the third one presents a coordination mechanism between two robots that carry a heavy object on a corridor and the fourth one is an example of coordination on a sensors network

Hospitalizations and Costs Incurred at the Facility Level After Scale-Up of Malaria Control: Pre-Post Comparisons From Two Hospitals in Zambia

There is little evidence on the impact of malaria control on the health system, particularly at the facility level. Using retrospective, longitudinal facility-level and patient record data from two hospitals in Zambia, we report a pre-post comparison of hospital admissions and outpatient visits for malaria and estimated costs incurred for malaria admissions before and after malaria control scale-up. The results show a substantial reduction in inpatient admissions and outpatient visits for malaria at both hospitals after the scale-up, and malaria cases accounted for a smaller proportion of total hospital visits over time. Hospital spending on malaria admissions also decreased. In one hospital, malaria accounted for 11% of total hospital spending before large-scale malaria control compared with \u3c 1% after malaria control. The findings demonstrate that facility-level resources are freed up as malaria is controlled, potentially making these resources available for other diseases and conditions

The impact of solar radiation on polar mesospheric ice particle formation

Mean temperatures in the polar summer mesopause can drop to 130&thinsp;K. The low temperatures in combination with water vapor mixing ratios of a few parts per million give rise to the formation of ice particles. These ice particles may be observed as polar mesospheric clouds. Mesospheric ice cloud formation is believed to initiate heterogeneously on small aerosol particles (r &lt; 2 nm) composed of recondensed meteoric material, so-called meteoric smoke particles (MSPs). Recently, we investigated the ice activation and growth behavior of MSP analogues under realistic mesopause conditions. Based on these measurements we presented a new activation model which largely reduced the uncertainties in describing ice particle formation. However, this activation model neglected the possibility that MSPs heat up in the low-density mesopause due to absorption of solar and terrestrial irradiation. Radiative heating of the particles may severely reduce their ice formation ability. In this study we expose MSP analogues (Fe2O3 and FexSi1 − xO3) to realistic mesopause temperatures and water vapor concentrations and investigate particle warming under the influence of variable intensities of visible light (405, 488, and 660&thinsp;nm). We show that Mie theory calculations using refractive indices of bulk material from the literature combined with an equilibrium temperature model presented in this work predict the particle warming very well. Additionally, we confirm that the absorption efficiency increases with the iron content of the MSP material. We apply our findings to mesopause conditions and conclude that the impact of solar and terrestrial radiation on ice particle formation is significantly lower than previously assumed.</p