Content Based Image Retrieval by Convolutional Neural Networks

Hamreras S., Benítez-Rochel R., Boucheham B., Molina-Cabello M.A., López-Rubio E. (2019) Content Based Image Retrieval by Convolutional Neural Networks. In: Ferrández Vicente J., Álvarez-Sánchez J., de la Paz López F., Toledo Moreo J., Adeli H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science, vol 11487. Springer.In this paper, we present a Convolutional Neural Network (CNN) for feature extraction in Content based Image Retrieval (CBIR). The proposed CNN aims at reducing the semantic gap between low level and high-level features. Thus, improving retrieval results. Our CNN is the result of a transfer learning technique using Alexnet pretrained network. It learns how to extract representative features from a learning database and then uses this knowledge in query feature extraction. Experimentations performed on Wang (Corel 1K) database show a significant improvement in terms of precision over the state of the art classic approaches.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Strain response of stretchable micro-electrodes: Controlling sensitivity with serpentine designs and encapsulation

The functionality of flexible electronics relies on stable performance of thin film micro-electrodes. This letter investigates the behavior of gold thin films on polyimide, a prevalent combination in flexible devices. The dynamic behavior of gold micro-electrodes has been studied by subjecting them to stress while monitoring their resistance in situ. The shape of the electrodes was systematically varied to examine resistive strain sensitivity, while an additional encapsulation was applied to characterize multilayer behavior. The realized designs show remarkable tolerance to repetitive strain, demonstrating that curvature and encapsulation are excellent approaches for minimizing resistive strain sensitivity to enable durable flexible electronics

A robust and forward-Looking industrial production indicator

Against the backdrop of growing criticism of the index of industrial production, which provides information only about the past and sometimes fl uctuates wildly, this article seeks to provide a more robust and forward-looking economic indicator of industrial growth. Such an indicator, based on past IIP numbers, can also serve as a benchmark for future IIP numbers when they are released. Using data on the IIP's three sub-series - manufacturing, mining, and electricity - it seeks to isolate the "noise" from the "signal" in two steps, enabling predictions for the two past months and four months into the future using the latest available IIP numbers in any given month

AI-Based Sustainable and Intelligent Offloading Framework for IIoT in Collaborative Cloud-Fog Environments

The cloud paradigm is one of the most trending areas in today’s era due to its rich profusion of services. However, it fails to serve the latency-sensitive Industrial Internet of Things (IIoT) applications associated with automotives, robotics, oil and gas, smart communications, Industry 5.0, etc. Hence, to strengthen the capabilities of IIoT, fog computing has emerged as a promising solution for latency-aware IIoT tasks. However, the resource-constrained nature of fog nodes puts forth another substantial issue of offloading decisions in resource management. Therefore, we propose an Artificial Intelligence (AI)-enabled intelligent and sustainable framework for an optimized multi-layered integrated cloud fog-based environment where real-time offloading decisions are accomplished as per the demand of IIoT applications and analyzed by a fuzzy based offloading controller. Moreover, an AI based Whale Optimization Algorithm (WOA) has been incorporated into a framework that promises to search for the best possible resources and make accurate decisions to ameliorate various Quality-of-Service (QoS) parameters. The experimental results show an escalation in makespan time up to 37.17%, energy consumption up to 27.32%, and execution cost up to 13.36% in comparison to benchmark offloading and allocation schemes

YALE OBSERVATION SCALE AS A PREDICTOR OF BACTEREMIA AND FINAL OUTCOME IN 3-36 MONTHS OLD FEBRILE CHILDREN ADMITTED IN TERTIARY HEALTH CENTRES: A HOSPITAL-BASED CROSS-SECTIONAL STUDY

ABSTRACTObjectives: The objective of the study was to assess predictability of bacteremia in febrile children in the age group of 3-36 months by application ofYale observation scale (YOS) and to predict clinical course during hospital stay and final outcome by YOS.Methods: A hospital-based cross-sectional study was carried out at Kasturba Medical College, Mangalore, Karnataka, for a period of 2 years(September 2013-September, 2015) in 100 febrile children in the age group of 3-36 months with probable infectious etiology admitted in ward/PICU.Children with any non-infectious causes of fever (vaccination, autoimmune, and immunodeficiency disorder) were excluded from the study. Caseswere selected by simple random sampling. The primary study outcome was bacteremia based on positivity on blood culture and sensitivity sampledrawn at admission. Secondary outcomes are clinical course in the hospital, use of antibiotics, need for mechanical ventilation, hospital stay, andmortality.Results: 100 cases were included in the study out of which 18 cases were bacteremic with a mean YOS of 26 (non-bacteremic - 11), mean hospitalstay 19.5 days (non-bacteremic - 12 days). All 18 bacteremic children had YOS ≥20, but YOS ≥20 had 8 false positives cases. There was no significantinterobserver variability in YOS assessment (Cronbach's alpha - 0.993 showing good correlation with intraclass correlation coefficient - 0.986).Higher YOS scores had good sensitivity, specificity, positive and negative likelihood ratios, and area under curve for prediction of bacteremia atYOS >20 (100%, 90.2%, 10.2, 0.00, and 0.970), need for mechanical ventilation at YOS >21 (100%, 91.7%, 12.04, 0.00, and 0.969), need for scaling upantibiotics at YOS >21 (70.4%, 94.4%, 12.5, 0.31, and 0.822), and mortality at YOS >21 (90.9%, 85.4%, 6.2, 0.106, 0.878).Conclusion: YOS is a good tool to rule out bacteremia and to prognosticate the clinical course at the first visit. This simple scale can be of value inmonitoring admitted patients for deteriorating clinical state and for assessing the need for referral to higher centers for further management.Keywords: Yale observation scale, Bacteremia, Febrile patients

Comparing genomic expression patterns across plant species reveals highly diverged transcriptional dynamics in response to salt stress

BackgroundRice and barley are both members of Poaceae (grass family) but have a marked difference in salt tolerance. The molecular mechanism underlying this difference was previously unexplored. This study employs a comparative genomics approach to identify analogous and contrasting gene expression patterns between rice and barley.ResultsA hierarchical clustering approach identified several interesting expression trajectories among rice and barley genotypes. There were no major conserved expression patterns between the two species in response to salt stress. A wheat salt-stress dataset was queried for comparison with rice and barley. Roughly one-third of the salt-stress responses of barley were conserved with wheat while overlap between wheat and rice was minimal. These results demonstrate that, at transcriptome level, rice is strikingly different compared to the more closely related barley and wheat. This apparent lack of analogous transcriptional programs in response to salt stress is further highlighted through close examination of genes associated with root growth and development.ConclusionThe analysis provides support for the hypothesis that conservation of transcriptional signatures in response to environmental cues depends on the genetic similarity among the genotypes within a species, and on the phylogenetic distance between the species

Beneficial Effect of Oryzanol on Transient Middle Artery Occlusion Induced Ischemic Stroke in Atherosclerotic Rats. Improvement in Behavioural and Biochemical Parameters

The present study was designed to determine the beneficial effect of oryzanol treatment in the ischemic stroke in atherosclerotic rats. Atherosclerosis was induced in rats using high fat diet (containing 20% ground nut oil, 0.5% cholesterol, 1% cholic acid) for 32 days. Ischemic stroke was induced in the atherosclerotic rat (AT rats) on 33rd day using tMCAO model. In the oryzanol treatment group, oryzanol (100 mg/kg, po) was administered on the very first day (day rats were fed with high fat diet), ischemic stroke was induced on 33rd day and oryzanol treatment was continued after the induction of ischemia from 34th day to 40th day. The neurological score was determined for 7days with gap of 24 hrs between the testing procedure. Rats were sacrificed followed by the blood collection and excision of whole brain for the determination of various parameters including brain damage (infarct volume, brain hemisphere weight difference, and Na+-K+-ATPase activity) and oxidative stress parameter (SOD activity, reduced GSH level, MDA level, nitrite level and LDH level). It was observed that ischemia-reperfusion (IR rats) in atherosclerotic rats increased the neurological score, increase in infarct volume, brain hemisphere weight difference and reduced activity of Na+-K+-ATPase. Further IR rats showed the decreased activity of SOD activity and GSH, whereas the level of MDA, nitrite and LDH activity was found to be increased in the atherosclerotic-IR rats. Further it was observed that the oryzanol treatment in the atherosclerotic counteracted the high fat induced rise in the TG, LDL, and VLDL level and increased the level of HDL in the treated animals. Further the administration of oryzanol improved the neurological score, reduce the infarct volume, brain hemisphere weight difference and improve the activity of Na+-K+-ATPase. Oryzanol treatment further improved the SOD activity, increased the level of GSH, reduced the level of MDA, nitrite and LDH activity in atherosclerotic-IR rat

Sb2Te3 and Bi2Te3 based thermopower wave sources

Exothermic chemical reactions from nitrocellulose are coupled onto Sb2Te3 (antimony telluride) and Bi2Te3 (bismuth telluride) layers to generate self-propagating oscillating thermopower waves. P-type Sb2Te3 and N-type Bi2Te3 are employed due to their large Seebeck coefficients, high electrical conductivities and their complementary semiconducting properties. Sources based on both materials exhibit high power to mass ratios: up to 0.6 kW kg-1 for Sb2Te3 and 1.0 kW kg-1 for Bi2Te3. Having both P- and N-type semiconductors in the system, the combination of the outputs can be used for generating sources with polarities alternating in time