Adaptive path planning for fusing rapidly exploring random trees and deep reinforcement learning in an agriculture dynamic environment UAVs

Unmanned aerial vehicles (UAV) are a suitable solution for monitoring growing cultures due to the possibility of covering a large area and the necessity of periodic monitoring. In inspection and monitoring tasks, the UAV must find an optimal or near-optimal collision-free route given initial and target positions. In this sense, path-planning strategies are crucial, especially online path planning that can represent the robot’s operational environment or for control purposes. Therefore, this paper proposes an online adaptive path-planning solution based on the fusion of rapidly exploring random trees (RRT) and deep reinforcement learning (DRL) algorithms applied to the generation and control of the UAV autonomous trajectory during an olive-growing fly traps inspection task. The main objective of this proposal is to provide a reliable route for the UAV to reach the inspection points in the tree space to capture an image of the trap autonomously, avoiding possible obstacles present in the environment. The proposed framework was tested in a simulated environment using Gazebo and ROS. The results showed that the proposed solution accomplished the trial for environments up to 300 m3 and with 10 dynamic objects.The authors would like to thank the following Brazilian Agencies CEFET-RJ, CAPES, CNPq, and FAPERJ. The authors also want to thank the Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança–IPB (UIDB/05757/2020 and UIDP/05757/2020), the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI, and Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) and IPB, Portugal. This work was carried out under the Project “OleaChain: Competências para a sustentabilidade e inovação da cadeia de valor do olival tradicional no Norte Interior de Portugal” (NORTE-06-3559-FSE-000188), an operation to hire highly qualified human resources, funded by NORTE 2020 through the European Social Fund (ESF).info:eu-repo/semantics/publishedVersio

Cooperative heterogeneous robots for autonomous insects trap monitoring system in a precision agriculture scenario

The recent advances in precision agriculture are due to the emergence of modern robotics systems. For instance, unmanned aerial systems (UASs) give new possibilities that advance the solution of existing problems in this area in many different aspects. The reason is due to these platforms’ ability to perform activities at varying levels of complexity. Therefore, this research presents a multiple-cooperative robot solution for UAS and unmanned ground vehicle (UGV) systems for their joint inspection of olive grove inspect traps. This work evaluated the UAS and UGV vision-based navigation based on a yellow fly trap fixed in the trees to provide visual position data using the You Only Look Once (YOLO) algorithms. The experimental setup evaluated the fuzzy control algorithm applied to the UAS to make it reach the trap efficiently. Experimental tests were conducted in a realistic simulation environment using a robot operating system (ROS) and CoppeliaSim platforms to verify the methodology’s performance, and all tests considered specific real-world environmental conditions. A search and landing algorithm based on augmented reality tag (AR-Tag) visual processing was evaluated to allow for the return and landing of the UAS to the UGV base. The outcomes obtained in this work demonstrate the robustness and feasibility of the multiple-cooperative robot architecture for UGVs and UASs applied in the olive inspection scenario.The authors would like to thank the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). In addition, the authors would like to thank the following Brazilian Agencies CEFET-RJ, CAPES, CNPq, and FAPERJ. In addition, the authors also want to thank the Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Braganca (IPB) - Campus de Santa Apolonia, Portugal, Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC), Portugal, INESC Technology and Science - Porto, Portugal and Universidade de Trás-os-Montes e Alto Douro - Vila Real, Portugal. This work was carried out under the Project “OleaChain: Competências para a sustentabilidade e inovação da cadeia de valor do olival tradicional no Norte Interior de Portugal” (NORTE-06-3559-FSE-000188), an operation used to hire highly qualified human resources, funded by NORTE 2020 through the European Social Fund (ESF).info:eu-repo/semantics/publishedVersio

Long-term melatonin treatment reduces ovarian mass and enhances tissue antioxidant defenses during ovulation in the rat

Melatonin regulates the reproductive cycle, energy metabolism and may also act as a potential antioxidant indoleamine. The present study was undertaken to investigate whether long-term melatonin treatment can induce reproductive alterations and if it can protect ovarian tissue against lipid peroxidation during ovulation. Twenty-four adult female Wistar rats, 60 days old (± 250-260 g), were randomly divided into two equal groups. The control group received 0.3 mL 0.9% NaCl + 0.04 mL 95% ethanol as vehicle, and the melatonin-treated group received vehicle + melatonin (100 µg·100 g body weight-1·day-1) both intraperitoneally daily for 60 days. All animals were killed by decapitation during the morning estrus at 4:00 am. Body weight gain and body mass index were reduced by melatonin after 10 days of treatment (P < 0.05). Also, a marked loss of appetite was observed with a fall in food intake, energy intake (melatonin 51.41 ± 1.28 vs control 57.35 ± 1.34 kcal/day) and glucose levels (melatonin 80.3 ± 4.49 vs control 103.5 ± 5.47 mg/dL) towards the end of treatment. Melatonin itself and changes in energy balance promoted reductions in ovarian mass (20.2%) and estrous cycle remained extensive (26.7%), arresting at diestrus. Regarding the oxidative profile, lipid hydroperoxide levels decreased after melatonin treatment (6.9%) and total antioxidant substances were enhanced within the ovaries (23.9%). Additionally, melatonin increased superoxide dismutase (21.3%), catalase (23.6%) and glutathione-reductase (14.8%) activities and the reducing power (10.2% GSH/GSSG ratio). We suggest that melatonin alters ovarian mass and estrous cyclicity and protects the ovaries by increasing superoxide dismutase, catalase and glutathione-reductase activities.21722

Assessing associations between the AURKAHMMR-TPX2-TUBG1 functional module and breast cancer risk in BRCA1/2 mutation carriers

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood appr

Risk factors associated with Toxoplasma gondii infection in dairy cattle, state of Rio de Janeiro

Toxoplasmosis is one of the most common parasitic zoonoses throughout the world. Infection in man and animals varies in different geographical areas influenced by many environmental conditions. Seroprevalence of Toxoplasma gondii infection in cattle in Brazil ranges from 1.03 to 71%. A cross-sectional survey was carried out in 58 out of 453 farms in the South Fluminense Paraiba Valley, State of Rio de Janeiro, Brazil. Over 3-year-old cattle (n=589) from dairy herds were selected for blood collection and detection of anti-T. gondii antibodies by indirect immunofluorescence reaction (IFA) with initial titration of 1:16; titers &gt; 64 were considered positive. Univariate analysis of risk factors showed that cats in contact with cattle, cats in contact with drinking water, and number of cats were associated with T. gondii seroprevalence. Logistic regression revealed a two-fold increased risk for infection of cattle (p=0.0138) through larger number of cats (&gt;3) compared with low numbers of cats (1-2) on the farm. In contrast, the presence of chickens was considered a protective factor (p=0.025).</jats:p

Search for black holes and other new phenomena in high-multiplicity final states in proton-proton collisions at root s=13 TeV

Peer reviewe

Measurement of the cross section for isolated-photon plus jet production in pp collisions at √s=13 TeV using the ATLAS detector

The dynamics of isolated-photon production in association with a jet in proton–proton collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset with an integrated luminosity of 3.2 fb−1. Photons are required to have transverse energies above 125 GeV. Jets are identified using the anti- algorithm with radius parameter and required to have transverse momenta above 100 GeV. Measurements of isolated-photon plus jet cross sections are presented as functions of the leading-photon transverse energy, the leading-jet transverse momentum, the azimuthal angular separation between the photon and the jet, the photon–jet invariant mass and the scattering angle in the photon–jet centre-of-mass system. Tree-level plus parton-shower predictions from Sherpa and Pythia as well as next-to-leading-order QCD predictions from Jetphox and Sherpa are compared to the measurements

Search for high-mass diphoton resonances in proton-proton collisions at 13 TeV and combination with 8 TeV search

Peer reviewe

Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

Peer reviewe

A search for resonances decaying into a Higgs boson and a new particle X in the XH → qqbb final state with the ATLAS detector

A search for heavy resonances decaying into a Higgs boson (H) and a new particle (X) is reported, utilizing 36.1 fb−1 of proton–proton collision data at collected during 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider. The particle X is assumed to decay to a pair of light quarks, and the fully hadronic final state is analysed. The search considers the regime of high XH resonance masses, where the X and H bosons are both highly Lorentz-boosted and are each reconstructed using a single jet with large radius parameter. A two-dimensional phase space of XH mass versus X mass is scanned for evidence of a signal, over a range of XH resonance mass values between 1 TeV and 4 TeV, and for X particles with masses from 50 GeV to 1000 GeV. All search results are consistent with the expectations for the background due to Standard Model processes, and 95% CL upper limits are set, as a function of XH and X masses, on the production cross-section of the resonance