Background subtraction by combining Temporal and Spatio-Temporal histograms in the presence of camera movement

Background subtraction is the classical approach to differentiate moving objects in a scene from the static background when the camera is fixed. If the fixed camera assumption does not hold, a frame registration step is followed by the background subtraction. However, this registration step cannot perfectly compensate camera motion, thus errors like translations of pixels from their true registered position occur. In this paper, we overcome these errors with a simple, but effective background subtraction algorithm that combines Temporal and Spatio-Temporal approaches. The former models the temporal intensity distribution of each individual pixel. The latter classifies foreground and background pixels, taking into account the intensity distribution of each pixels' neighborhood. The experimental results show that our algorithm outperforms the state-of-the-art systems in the presence of jitter, in spite of its simplicity

Backward-Simulation Particle Smoother with a hybrid state for 3D vehicle trajectory, class and dimension simultaneous estimation

The estimation of the 3D trajectory, the class and the dimensions of a vehicle represents three relevant tasks for traffic monitoring. They are usually performed by separate sub-systems and only few existing algorithms cope with the three tasks at the same time. However, if these tasks are integrated, the trajectory estimation enforces the classification with temporal consistency, and at the same time, the estimation of the vehicle class and dimensions can be used to increase the trajectory estimate accuracy. In this work, we propose an algorithm to estimate the 3D trajectory, the class and the dimensions of vehicles simultaneously by means of a Backward-Simulation Particle Smoother whose state contains both continuous (vehicle pose and dimensions), and discrete (vehicle class) quantities. To integrate the class estimate in the Particle Smoother we model the class prediction as a Markov Chain. We performed experimental tests on both simulated and real datasets; they show that the pose and dimension estimation reaches centimeter-accuracy and the classification accuracy is higher than 95

Single-incision laparoscopic adnexectomy in an obese patient with previous laparotomies

No case of single-incision laparoscopic surgery in obese patients who had previously undergone multiple midline vertical laparotomies has been described in the literature to date. Hence we report the first case of single-port laparoscopic salpingo-oophorectomy in an obese patient who was affected by a left adnexal mass and who had previously undergone 3 midline vertical laparotomies

Evaluation of plant derivatives of Meliaceae family as a source of nitrogen for trees

Soil application of fresh organic matter is a way to increase soil organic matter and provide nutrients to trees. The effect of application of organic matter depends on the interaction among soil, root and microbial biomass. The aim of this research was to evaluate the potential release of N for hybrid GF677 (P. persica x P. dulcis) uptake, of 6 neemcakes available on the Italian market compared with fresh leaves of Melia azedarach, an ornamental tree that grows in the area of investigation. The release of N, and consequently root uptake was related to C:N ratio, the lower the ratio the higher the N concentration in plant tissues and plant growth. Using the 15N isotope technique, we found that up to 30% of the N applied with fresh Melia leaves, was accumulated in the tree, however the mineral N concentration in soil and plant and plant growth was not affected by the application of plant derivatives

Essential oil phytocomplex activity, a review with a focus on multivariate analysis for a network pharmacology-informed phytogenomic approach

Thanks to omic disciplines and a systems biology approach, the study of essential oils and phytocomplexes has been lately rolling on a faster track. While metabolomic fingerprinting can provide an effective strategy to characterize essential oil contents, network pharmacology is revealing itself as an adequate, holistic platform to study the collective effects of herbal products and their multi-component and multi-target mediated mechanisms. Multivariate analysis can be applied to analyze the effects of essential oils, possibly overcoming the reductionist limits of bioactivity-guided fractionation and purification of single components. Thanks to the fast evolution of bioinformatics and database availability, disease-target networks relevant to a growing number of phytocomplexes are being developed. With the same potential actionability of pharmacogenomic data, phytogenomics could be performed based on relevant disease-target networks to inform and personalize phytocomplex therapeutic application

Sars‐cov‐2 and public transport in Italy

Although direct contact is considered the main mode of transmission of SARS‐CoV‐2, environmental factors play an important role. In this study, we evaluated the presence of SARS‐ CoV‐2 on bus and train surfaces. From the buses, we took samples from the following areas: handrails used to enter or exit the bus, stop request buttons and handles next to the seats. From the trains, the sampled surfaces were handrails used to enter or exit the train, door open/close buttons, handles next to the seats, tables and toilet handles. SARS‐CoV‐2 was detected on 10.7% of the tested surfaces overall, 19.3% of bus surfaces and 2% of train surfaces (p < 0.0001). On the buses, the most contaminated surfaces were the handles near the seats (12.8%), followed by door open/close buttons (12.5%) and handrails (10.5%). Of the five analyzed transport companies, bus companies were the most contaminated, in particular, companies C (40%) and B (23.3%). A greater number of positive samples were found among those taken at 10:00 a.m. and 10:55 a.m. (45% and 40%, respectively). The presence of the virus on many bus surfaces highlights how the sanitation systems on public transport currently in use are not sufficient to limit the spread of SARS‐CoV‐2

An effective 6DoF motion model for 3D-6DoF Monte Carlo Localization

This paper deals with the probabilistic 6DoF motion model of a wheeled road vehicle. It allows to correctly model the error introduced by dead reckoning. Furthermore, to stress the importance of an appropriate motion model, i.e., that different models are not equally good, we show that another model, which was previously developed, does not allow a correct representation of the uncertainty, therefore misguiding 3D-6DoF Monte Carlo Localization. We also present some field experiments to demonstrate that our model allow a consistent determination of the 6DoF vehicle pose