Real-time detection of uncalibrated sensors using Neural Networks

Nowadays, sensors play a major role in several contexts like science, industry and daily life which benefit of their use. However, the retrieved information must be reliable. Anomalies in the behavior of sensors can give rise to critical consequences such as ruining a scientific project or jeopardizing the quality of the production in industrial production lines. One of the more subtle kind of anomalies are uncalibrations. An uncalibration is said to take place when the sensor is not adjusted or standardized by calibration according to a ground truth value. In this work, an online machine-learning based uncalibration detector for temperature, humidity and pressure sensors was developed. This solution integrates an Artificial Neural Network as main component which learns from the behavior of the sensors under calibrated conditions. Then, after trained and deployed, it detects uncalibrations once they take place. The obtained results show that the proposed solution is able to detect uncalibrations for deviation values of 0.25 degrees, 1% RH and 1.5 Pa, respectively. This solution can be adapted to different contexts by means of transfer learning, whose application allows for the addition of new sensors, the deployment into new environments and the retraining of the model with minimum amounts of data

Molecular detection of mycobacterium tuberculosis in oral mucosa from patients with presumptive tuberculosis

Funding: This research was funded by a Strategic Award grant from the European and Developing Countries Clinical Trials Partnership (grant DRIA2014-309) and its cofounders, the Medical Research Council UK, and Institutode Salud Carlos III (ISCIII), Spain (PI116/01912); and from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement no. 823854 (INNOVA4TB).Tuberculosis (TB) diagnosis is increasingly based on the detection of Mycobacterium tuberculosis complex (MTBC) DNA in sputum using molecular diagnostic tests as the first test for diagnosis. However, sputum can be difficult to obtain in children, patients without productive cough, and the elderly and approaches testing non-sputum samples are needed. We evaluated whether TB can be detected from the oral mucosa of patients with TB. Adults with presumptive TB were examined using culture, Xpert MTB/RIF, smear microscopy and X-Rays. Oral mucosa swabs collected on PrimeStore-MTM, stored at room temperature if tested within 30 days or at −20 °C if examined at a later time. RT-PCR was performed to detect M. tuberculosis DNA. Eighty patients had bacteriologically-confirmed TB, 34 had bacteriologically-negative TB (negative tests but abnormal X-rays) and 152 were considered not to have TB (not TB). Oral swabs RT-PCR were positive in 29/80 (36.3%) bacteriologically-confirmed, 9/34 (26.5%) bacteriologically-negative and 29/152 (19.1%) not TB. The yield varied among samples stored for less and more than 30 days (p = 0.013) from 61% (11/18) and 29% (18/62) among bacteriologically confirmed, and 30.8% (4/13) and 23.8% (5/21) among bacteriologically-negative participants. Among not TB patients, the specificity was 80.9% (123/152), being 78.3% (18/23) among samples stored less than 30 days and 81.4% (105/129) among samples stored for more than 30 days (p = 0.46). The detection of M. tuberculosis in oral mucosa samples is feasible, but storage conditions may affect the yield.Publisher PDFPeer reviewe

The biology and behavior of the longhorned beetle, Dectes texanus on sunflower and soybean

The biology and behavior of the longhorned beetle Dectes texanus LeConte (Coleoptera: Cerambycidae) was studied on two host plants that suffer economic losses from this pest; sunflower, Helianthus annuus, and soybean, Glycines max. Reciprocal crosses of D. texanus collected from the two plants all produced viable progeny, indicating that conspecific insects attack both crops. Pupae from soybean stalks weighed about 40% less than those from sunflower, and adults fed on soybean lived a mean of 23 days, compared to a mean of 53 days (males) and 76 days (females) for those fed sunflower. A female's larval host plant had no effect on her tendency to ovipuncture plants of either type in a greenhouse trial. A field-tested population collected exclusively from sunflower contained three types of females in similar proportions: those that laid eggs only on sunflower, those that laid only on soybean, and those that laid equally on both host plants. Females in field trials fed more on the plant they had fed on in the laboratory, but soybean-fed females fed more on soybean than did sunflower-fed females. Females fed soybean also made more ovipunctures on soybean plants in field trials than sunflower-fed females, but their responses to sunflower plants were similar. Females displayed higher total ovipositional activity when they encountered sunflower first in the field, and lower total activity when they encountered soybean first. Feeding scores were significantly correlated with ovipunctures and eggs on both plant types. We conclude that sunflower is the preferred host plant, although females will accept soybean when it is the only available food. The results suggest that D. texanus is still in the initial stages of a host range expansion with female host selection behavior demonstrating both genetic influences and phenotypic flexibility. Sunflower represents a nutritionally superior, ancestral host plant and relatively high fitness costs are still associated with utilization of the novel host plant, soybean, costs that may be offset by benefits such as reduced intraspecific competition. These potential benefits and their consequent implications for D. texanus host range evolution are hypothesized and discussed

The role of statins on helicobacter pylori eradication: Results from the european registry on the management of h. pylori (hp-eureg)

Statins could increase the effectiveness of Helicobacter pylori eradication therapies due to their anti-inflammatory effect. The aim of this study was to analyze the impact of this therapeutic association in real life. This is a multicenter, prospective, non-interventional study aimed at evaluating the management of H. pylori by European gastroenterologists. Patients were registered in an e-CRF by AEG-REDCap from 2013 to 2020. The association between statin use and H. pylori eradication effectiveness was evaluated through multivariate analysis. Overall, 9988 and 705 patients received empirical and culture-guided treatment, respectively. Overall, statin use was associated with higher effectiveness in the empirical group (OR = 1.3; 95%CI = 1.1-1.5), but no association was found with first-line treatment effectiveness (N = 7738); as an exception, statin use was specifically associated with lower effectiveness of standard triple therapy (OR = 0.76; 95%CI = 0.59-0.99). In the rescue therapy empirical group (N = 2228), statins were associated with higher overall effectiveness (OR = 1.9; 95%CI = 1.4-2.6). However, sub-analyses by treatment schemes only confirmed this association for the single-capsule bismuth quadruple therapy (OR = 2.8; 95%CI = 1.3-5.7). No consistent association was found between statin use and H. pylori therapy effectiveness. Therefore, the addition of statins to the usual H. pylori treatment cannot be currently recommended to improve cure rates. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Fish Farms at Sea: The Ground Truth from Google Earth

In the face of global overfishing of wild-caught seafood, ocean fish farming has augmented the supply of fresh fish to western markets and become one of the fastest growing global industries. Accurate reporting of quantities of wild-caught fish has been problematic and we questioned whether similar discrepancies in data exist in statistics for farmed fish production. In the Mediterranean Sea, ocean fish farming is prevalent and stationary cages can be seen off the coasts of 16 countries using satellite imagery available through Google Earth. Using this tool, we demonstrate here that a few trained scientists now have the capacity to ground truth farmed fish production data reported by the Mediterranean countries. With Google Earth, we could examine 91% of the Mediterranean coast and count 248 tuna cages (circular cages >40 m diameter) and 20,976 other fish cages within 10 km offshore, the majority of which were off Greece (49%) and Turkey (31%). Combining satellite imagery with assumptions about cage volume, fish density, harvest rates, and seasonal capacity, we make a conservative approximation of ocean-farmed finfish production for 16 Mediterranean countries. Our overall estimate of 225,736 t of farmed finfish (not including tuna) in the Mediterranean Sea in 2006 is only slightly more than the United Nations Food and Agriculture Organization reports. The results demonstrate the reliability of recent FAO farmed fish production statistics for the Mediterranean as well as the promise of Google Earth to collect and ground truth data

Search for R-parity violating supersymmetry via the LLE couplings lambda_{121}, lambda_{122} or lambda_{133} in ppbar collisions at sqrt(s)=1.96 TeV

A search for gaugino pair production with a trilepton signature in the framework of R-parity violating supersymmetry via the couplings lambda_121, lambda_122, or lambda_133 is presented. The data, corresponding to an integrated luminosity of L~360/pb, were collected from April 2002 to August 2004 with the D0 detector at the Fermilab Tevatron Collider, at a center-of-mass energy of sqrt(s)=1.96 TeV. This analysis considers final states with three charged leptons with the flavor combinations eel, mumul, and eetau (l=e or mu). No evidence for supersymmetry is found and limits at the 95% confidence level are set on the gaugino pair production cross section and lower bounds on the masses of the lightest neutralino and chargino are derived in two supersymmetric models.Comment: 9 pages, 4 figures (fig2 includes 3 subfigures

Measurement of the B0_s semileptonic branching ratio to an orbitally excited D_s** state, Br(B0_s -> Ds1(2536) mu nu)

In a data sample of approximately 1.3 fb-1 collected with the D0 detector between 2002 and 2006, the orbitally excited charm state D_s1(2536) has been observed with a measured mass of 2535.7 +/- 0.6 (stat) +/- 0.5 (syst) MeV via the decay mode B0_s -> D_s1(2536) mu nu X. A first measurement is made of the branching ratio product Br(b(bar) -> D_s1(2536) mu nu X).Br(D_s1(2536)->D* K0_S). Assuming that D_s1(2536) production in semileptonic decay is entirely from B0_s, an extraction of the semileptonic branching ratio Br(B0_s -> D_s1(2536) mu nu X) is made.Comment: 7 pages, 2 figures, LaTeX, version with minor changes as accepted by Phys. Rev. Let

Simultaneous measurement of the ratio B(t->Wb)/B(t->Wq) and the top quark pair production cross section with the D0 detector at sqrt(s)=1.96 TeV

We present the first simultaneous measurement of the ratio of branching fractions, R=B(t->Wb)/B(t->Wq), with q being a d, s, or b quark, and the top quark pair production cross section sigma_ttbar in the lepton plus jets channel using 0.9 fb-1 of ppbar collision data at sqrt(s)=1.96 TeV collected with the D0 detector. We extract R and sigma_ttbar by analyzing samples of events with 0, 1 and >= 2 identified b jets. We measure R = 0.97 +0.09-0.08 (stat+syst) and sigma_ttbar = 8.18 +0.90-0.84 (stat+syst)} +/-0.50 (lumi) pb, in agreement with the standard model prediction.Comment: submitted to Phys.Rev.Letter

Deciphering the complex interplay between pancreatic cancer, diabetes mellitus subtypes and obesity/BMI through causal inference and mediation analyses.

OBJECTIVES: To characterise the association between type 2 diabetes mellitus (T2DM) subtypes (new-onset T2DM (NODM) or long-standing T2DM (LSDM)) and pancreatic cancer (PC) risk, to explore the direction of causation through Mendelian randomisation (MR) analysis and to assess the mediation role of body mass index (BMI). DESIGN: Information about T2DM and related factors was collected from 2018 PC cases and 1540 controls from the PanGenEU (European Study into Digestive Illnesses and Genetics) study. A subset of PC cases and controls had glycated haemoglobin, C-peptide and genotype data. Multivariate logistic regression models were applied to derive ORs and 95% CIs. T2DM and PC-related single nucleotide polymorphism (SNP) were used as instrumental variables (IVs) in bidirectional MR analysis to test for two-way causal associations between PC, NODM and LSDM. Indirect and direct effects of the BMI-T2DM-PC association were further explored using mediation analysis. RESULTS: T2DM was associated with an increased PC risk when compared with non-T2DM (OR=2.50; 95% CI: 2.05 to 3.05), the risk being greater for NODM (OR=6.39; 95% CI: 4.18 to 9.78) and insulin users (OR=3.69; 95% CI: 2.80 to 4.86). The causal association between T2DM (57-SNP IV) and PC was not statistically significant (ORLSDM=1.08, 95% CI: 0.86 to 1.29, ORNODM=1.06, 95% CI: 0.95 to 1.17). In contrast, there was a causal association between PC (40-SNP IV) and NODM (OR=2.85; 95% CI: 2.04 to 3.98), although genetic pleiotropy was present (MR-Egger: p value=0.03). Potential mediating effects of BMI (125-SNPs as IV), particularly in terms of weight loss, were evidenced on the NODM-PC association (indirect effect for BMI in previous years=0.55). CONCLUSION: Findings of this study do not support a causal effect of LSDM on PC, but suggest that PC causes NODM. The interplay between obesity, PC and T2DM is complex