Towards Enhancing Traffic Sign Recognition through Sliding Windows

Automatic Traffic Sign Detection and Recognition (TSDR) provides drivers with critical information on traffic signs, and it constitutes an enabling condition for autonomous driving. Misclassifying even a single sign may constitute a severe hazard, which negatively impacts the environment, infrastructures, and human lives. Therefore, a reliable TSDR mechanism is essential to attain a safe circulation of road vehicles. Traffic Sign Recognition (TSR) techniques that use Machine Learning (ML) algorithms have been proposed, but no agreement on a preferred ML algorithm nor perfect classification capabilities were always achieved by any existing solutions. Consequently, our study employs ML-based classifiers to build a TSR system that analyzes a sliding window of frames sampled by sensors on a vehicle. Such TSR processes the most recent frame and past frames sampled by sensors through (i) Long Short-Term Memory (LSTM) networks and (ii) Stacking Meta-Learners, which allow for efficiently combining base-learning classification episodes into a unified and improved meta-level classification. Experimental results by using publicly available datasets show that Stacking Meta-Learners dramatically reduce misclassifications of signs and achieved perfect classification on all three considered datasets. This shows the potential of our novel approach based on sliding windows to be used as an efficient solution for TSR

Native mass spectrometry of human carbonic anhydrase I and its inhibitor complexes

Abstract: Native mass spectrometry is a potent technique to study and characterize biomacromolecules in their native state. Here, we have applied this method to explore the solution chemistry of human carbonic anhydrase I (hCA I) and its interactions with four different inhibitors, namely three sulfonamide inhibitors (AAZ, MZA, SLC-0111) and the dithiocarbamate derivative of morpholine (DTC). Through high-resolution ESI-Q-TOF measurements, the native state of hCA I and the binding of the above inhibitors were characterized in the molecular detail. Native mass spectrometry was also exploited to assess the direct competition in solution among the various inhibitors in relation to their affinity constants. Additional studies were conducted on the interaction of hCA I with the metallodrug auranofin, under various solution and instrumental conditions. Auranofin is a selective reagent for solvent-accessible free cysteine residues, and its reactivity was analyzed also in the presence of CA inhibitors. Overall, our investigation reveals that native mass spectrometry represents an excellent tool to characterize the solution behavior of carbonic anhydrase. Graphic abstract: [Figure not available: see fulltext.]

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Effect of valsartan and ramipril on atrial fibrillation recurrence and P-wave dispersion in hypertensive patients with recurrent symptomatic lone atrial fibrillation

This study compared the effect of antihypertensive treatment with valsartan or ramipril on atrial fibrillation (AF) recurrence, on P-wave dispersion, (PWD) and on serum procollagen type I carboxy terminal peptide (PIP).A total of 369 mild hypertensive (systolic blood pressure (SBP) >140 and/or 90 < diastolic blood pressure (DBP) < 110 mm Hg) outpatients in sinus rhythm but with at least two episodes of AF in the previous 6 months were randomized to valsartan (n = 122), ramipril (n = 124), or amlodipine (n = 123) for 1 year. Clinic blood pressure (BP) and a 24-h electrocardiogram (ECG) were evaluated monthly. Patients were asked to report any episode of symptomatic AF and to perform an ECG as early as possible. PWD and serum PIP levels were evaluated before and after each treatment period.SBP and DBP were significantly reduced by the three treatments (P < 0.001). A total of 46 (47.4\%) patients treated with amlodipine had a recurrence of AF as did 26 (27.9\%) patients treated with ramipril (P < 0.01 vs. amlodipine) and 16 (16.1\%) patients treated with valsartan (P < 0.01 vs. amlodipine and P < 0.05 vs. ramipril). The Kaplan-Meyer analysis showed a significant reduction of AF episodes in the valsartan group (P = 0.005 log-rank test) as well as in the ramipril group (P = 0.021), even if at a lesser degree. PWD values were significantly reduced by ramipril (-4.2 ms, P < 0.05) and even more by valsartan (-11.2 ms, P < 0.01), the difference being significant (P < 0.01). Serum PIP levels were reduced by ramipril (-49.7 microg, P < 0.001) and valsartan (-49.3 microg, P < 0.001).Despite similar BP lowering, valsartan and ramipril were more effective than amlodipine in preventing new episodes of AF, but the effect of valsartan was greater than that of ramipril. This could be related to the greater PWD reduction observed with valsartan

Structural Phase Transition at High Temperatures in Solid Molecular Hydrogen and Deuterium

We study the effect of temperature up to 1000K on the structure of dense molecular para-hydrogen and ortho-deuterium, using the path-integral Monte Carlo method. We find a structural phase transition from orientationally disordered hexagonal close packed (hcp) to an orthorhombic structure of Cmca symmetry before melting. The transition is basically induced by thermal fluctuations, but quantum fluctuations of protons (deuterons) are important in determining the transition temperature through effectively hardening the intermolecular interaction. We estimate the phase line between hcp and Cmca phases as well as the melting line of the Cmca solid.Comment: 8 pages, 7 figures; accepted in Phys. Rev.