A machine learning approach to estimating preterm infants survival: development of the Preterm Infants Survival Assessment (PISA) predictor

Estimation of mortality risk of very preterm neonates is carried out in clinical and research settings. We aimed at elaborating a prediction tool using machine learning methods. We developed models on a cohort of 23747 neonates <30 weeks gestational age, or <1501 g birth weight, enrolled in the Italian Neonatal Network in 2008–2014 (development set), using 12 easily collected perinatal variables. We used a cohort from 2015–2016 (N = 5810) as a test set. Among several machine learning methods we chose artificial Neural Networks (NN). The resulting predictor was compared with logistic regression models. In the test cohort, NN had a slightly better discrimination than logistic regression (P < 0.002). The differences were greater in subgroups of neonates (at various gestational age or birth weight intervals, singletons). Using a cutoff of death probability of 0.5, logistic regression misclassified 67/5810 neonates (1.2 percent) more than NN. In conclusion our study – the largest published so far – shows that even in this very simplified scenario, using only limited information available up to 5 minutes after birth, a NN approach had a small but significant advantage over current approaches. The software implementing the predictor is made freely available to the community

A deep learning approach to organic pollutants classification using voltammetry

This paper proposes a deep leaning technique for accurate detection and reliable classification of organic pollutants in water. The pollutants are detected by means of cyclic voltammetry characterizations made by using low-cost disposable screen-printed electrodes. The paper demonstrates the possibility of strongly improving the detection of such platforms by modifying them with nanomaterials. The classification is addressed by using a deep learning approach with convolutional neural networks. To this end, the results of the voltammetry analysis are transformed into equivalent RGB images by means of Gramian angular field transformations. The proposed technique is applied to the detection and classification of hydroquinone and benzoquinone, which are particularly challenging since these two pollutants have a similar electroactivity and thus the voltammetry curves exhibit overlapping peaks. The modification of electrodes by carbon nanotubes improves the sensitivity of a factor of about x25, whereas the convolution neural network after Gramian transformation correctly classifies 100% of the experiments

Expression and Modulation of the Intermediate- Conductance Ca2+-Activated K+ Channel in Glioblastoma GL-15 Cells

We report here the expression and properties of the intermediate-conductance Ca2+-activated K+ (IKCa) channel in the GL-15 human glioblastoma cell line. Macroscopi

The Geothermal Power Plants of Amiata Volcano, Italy: Impacts on Freshwater Aquifers, Seismicity and Air

Production of geothermal energy for electricity at Amiata Volcano uses flash-type power plants with cooling towers that evaporate much of the geothermal fluid to the atmosphere to condense the geothermal vapour extracted. Because the flash occurs also within the geothermal reservoir, it causes a significant depressurization within it that, in turns, results in a drop of the water table inside the volcano between 200 and 300 m. The flow rates of natural springs around the volcano have also substantially decreased or ceased since the start of geothermal energy exploitation. Continuous recording of aquifer conditions shows substantial increases in salinity (>20%) and temperature (>2°C) as the water table falls below about 755–750 m asl. In addition to hydrologic impacts, there are also a large numbers of induced earthquakes, among which the ML 3.9, April 1, 2000 earthquake that generated significant damage in the old villages and rural houses. Relevant impacts on air quality occur when emissions are considered on a per-MW basis. For example, CO2+CH4 emissions at Amiata are comparable to those of gas-fired power plants, while the acid-rain potential is about twice that of coal-fired power plants. Also, a significant emission of primary and secondary fine particles is associated with the cooling towers. These particles contain heavy metals and are enriched in sodium, vanadium, zinc, phosphorous, sulphur, tantalium, caesium, thallium, thorium, uranium, and arsenic relative to comparable aerosols collected in Florence and Arezzo. Measurements have shown that mercury emitted at Amiata comprises 42% of the mercury emitted from all Italian industries, while an additional comparable amount is emitted from the other geothermal power plants of Tuscany. We believe that the use of air coolers in place of the evaporative cooling towers, as suggested in 2010 by the local government of Tuscany, could have and can now drastically reduced the environmental impact on freshwater and air. On the opposite side of the coin, air-coolers would increase the amount of reinjection, increasing the risk of induced seismicity. We conclude that the use of deep borehole heat exchangers could perhaps be the only viable solution to the current geothermal energy environmental impacts

Smart environments and context-awareness for lifestyle management in a healthy active ageing framework

Health trends of elderly in Europe motivate the need for technological solutions aimed at preventing the main causes of morbidity and premature mortality. In this framework, the DOREMI project addresses three important causes of morbidity and mortality in the elderly by devising an ICT-based home care services for aging people to contrast cognitive decline, sedentariness and unhealthy dietary habits. In this paper, we present the general architecture of DOREMI, focusing on its aspects of human activity recognition and reasoning

Enteroscopy in children and adults with inflammatory bowel disease

Inflammatory bowel disease (IBD) includes Crohn's disease (CD), ulcerative colitis and unclassified entities. CD commonly involves the terminal ileum and colon but at the time of diagnosis it can be confined to the small bowel (SB) in about 30% of the patients, especially in the young ones. Management of isolated SB-CD can be challenging and objective evaluation of the SB mucosa is essential in differentiating CD from other enteropathies to achieve therapeutic decisions and to plan the follow-up. The introduction of cross-sectional imaging techniques and capsule endoscopy (CE) have significantly expanded the ability to diagnose SB diseases providing a non-invasive test for the visualization of the entire SB mucosa. The main CE limitations are the low specificity, the lack of therapeutic capabilities and the impossibility to take biopsies. Device assisted enteroscopy (DAE) enables histological confirmation when traditional endoscopy, capsule endoscopy and cross-sectional imaging are inconclusive and also allows therapeutic interventions such as balloon stricture dilation, intralesional steroid injection, capsule retrieval and more recently stent insertion. In the current review we will discuss technical aspect, indications and safety profile of DAE in children and adults with IBD

Routing Aware Switch Hardware Customization for Networks on Chips

Networks on Chip (NoC) has been proposed as a scalable and reusable solution for interconnecting the ever- growing number of processor/memory cores on a single silicon die. As the hardware complexity of a NoC is significant, methods for designing a NoC with low hardware overhead, matching the application requirements are essential. In this work, we present a method for reducing the hardware complexity of the NoC by automatically configuring the architecture of the NoC switches to suit the application traffic characteristics. The crossbar matrix and the arbiters of each switch in the NoC design are customized to support the traffic flows utilizing that switch. This application- specific switch customization is integrated with an existing design flow, which automates NoC topology synthesis, mapping, RTL code and physical layout generation. Several experimental studies on NoC benchmark designs are carried out, which show that the proposed switch customization technique leads to large reduction in the NoC switch area (28% on average) and power consumption (21% on average). Moreover, the critical paths of the switches reduce significantly, thereby leading to a significant speed-up of the NoC design

Multispectral data by the new generation of high-resolution satellite sensors for mapping phytoplankton blooms in the Mar Piccolo of Taranto (Ionian Sea, southern Italy)

The HR (High-Resolution) EO (Earth Observation) satellite systems Landsat 8 OLI and Sentinel 2 were tested for mapping the frequent phytoplankton blooms and Chl a distributions in the sea basin of the Mar Piccolo of Taranto (Ionian Sea, southern Italy), using the sea truth calibration data acquired in 2013. The data were atmospherically corrected for accounting of the aerosol load on optically complexes waters (case II). Various blue-green and additional spectral indices ratios, were then satisfyingly tested for mapping the distribution of Chl a and differently sized phytoplankton populations through PLS (Partial Least Square regression) models, regressive statistical models and bio-optical algorithms. The PLS models demonstrated higher robustness for assessing the distribution of all the phytoplankton and Chl a except for those related to sub-surface micro-phytoplankton. The distributions obtained via a bio-optical approach (OC3 algorithm and full physically based inversion) showed a general agreement with the previous ones produced by statistical methods. The reflectance signals, captured by OLI and Sentinel 2 sensors in the visible and shorter wavelengths once atmospherically corrected, were found to be useful to map the coastal variability at detailed scale of Chl a and different phytoplankton populations, in the optically complexes waters of the Mar Piccolo

Predictive accuracy of progesterone receptor B in young women with atypical endometrial hyperplasia and early endometrial cancer treated with hysteroscopic resection plus LNG-IUD insertion

Immunohistochemical expression of the isoform B of progesterone receptor (PRB) has shown promising results in predicting the response of atypical endometrial hyperplasia (AEH) and early endometrial cancer (EEC) to conservative treatment. We aimed to calculate the accuracy of PRB as a predictive marker of conservative treatment outcome in AEH or EEC