Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping

Search for exotic resonances decaying into WZ/ZZ in pp collisions at √s=7 TeV

Journal of High Energy Physics 2013.2 (2013): 036 reproduced by permission of Scuola Internazionale Superiore di Studi Avanzati (SISSA)Artículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, el nombre del grupo de colaboración, si le hubiere, y los autores pertenecientes a la UAMA search for new exotic particles decaying to the VZ final state is performed, where V is either a W or a Z boson decaying into two overlapping jets and the Z decays into a pair of electrons, muons or neutrinos. The analysis uses a data sample of pp collisions corresponding to an integrated luminosity of 5 fb-1 collected by the CMS experiment at the LHC at √s=7 TeV in 2011. No significant excess is observed in the mass distribution of the VZ candidates compared with the background expectation from standard model processes. Model-dependent upper limits at the 95% confidence level are set on the product of the cross section times the branching fraction of hypothetical particles decaying to the VZ final state as a function of mass. Sequential standard model W′ bosons with masses between 700 and 940 GeV are excluded. In the Randall-Sundrum model for graviton resonances with a coupling parameter of 0.05, masses between 750 and 880 GeV are also exclude

Searches for long-lived charged particles in pp collisions at √s =7 and 8 TeV

Results of searches for heavy stable charged particles produced in pp collisions at √s =7 and 8 TeV are presented corresponding to an integrated luminosity of 5.0 fb⁻¹ and 18.8 fb⁻¹, respectively. Data collected with the CMS detector are used to study the momentum, energy deposition, and time-of-flight of signal candidates. Leptons with an electric charge between e/3 and 8e, as well as bound states that can undergo charge exchange with the detector material, are studied. Analysis results are presented for various combinations of signatures in the inner tracker only, inner tracker and muon detector, and muon detector only. Detector signatures utilized are long time-of-flight to the outer muon system and anomalously high (or low) energy deposition in the inner tracker. The data are consistent with the expected background, and upper limits are set on the production cross section of long-lived gluinos, scalar top quarks, and scalar τ leptons, as well as pair produced long-lived leptons. Corresponding lower mass limits, ranging up to 1322 GeV/c² for gluinos, are the most stringent to date

Juvenile hormone pathway in honey bee larvae:a source of possible signal molecules for the reproductive behavior of Varroa destructor

Abstract The parasitic mite Varroa destructor devastates honey bee (Apis mellifera) colonies around the world. Entering a brood cell shortly before capping, the Varroa mother feeds on the honey bee larvae. The hormones 20‐hydroxyecdysone (20E) and juvenile hormone (JH), acquired from the host, have been considered to play a key role in initiating Varroa’s reproductive cycle. This study focuses on differential expression of the genes involved in the biosynthesis of JH and ecdysone at six time points during the first 30 hr after cell capping in both drone and worker larvae of A. mellifera. This time frame, covering the conclusion of the honey bee brood cell invasion and the start of Varroa’s ovogenesis, is critical to the successful initiation of a reproductive cycle. Our findings support a later activation of the ecdysteroid cascade in honey bee drones compared to worker larvae, which could account for the increased egg production of Varroa in A. mellifera drone cells. The JH pathway was generally downregulated confirming its activity is antagonistic to the ecdysteroid pathway during the larva development. Nevertheless, the genes involved in JH synthesis revealed an increased expression in drones. The upregulation of jhamt gene involved in methyl farnesoate (MF) synthesis came into attention since the MF is not only a precursor of JH but it is also an insect pheromone in its own right as well as JH‐like hormone in Acari. This could indicate a possible kairomone effect of MF for attracting the mites into the drone brood cells, along with its potential involvement in ovogenesis after the cell capping, stimulating Varroa’s initiation of egg laying

Jet and underlying event properties as a function of charged-particle multiplicity in proton–proton collisions at √s = 7 TeV

Abstract Characteristics of multi-particle production in proton-proton collisions at √s = 7 TeV are studied as a function of the charged-particle multiplicity, N ch. The produced particles are separated into two classes: those belonging to jets and those belonging to the underlying event. Charged particles are measured with pseudorapidity |η|0.25 GeV/c. Jets are reconstructed from charged-particles only and required to have pT>5 GeV/c. The distributions of jet pT, average pT of charged particles belonging to the underlying event or to jets, jet rates, and jet shapes are presented as functions of Nch and compared to the predictions of the pythia and herwig event generators. Predictions without multi-parton interactions fail completely to describe the Nch-dependence observed in the data. For increasing Nch, pythia systematically predicts higher jet rates and harder pT spectra than seen in the data, whereas herwig shows the opposite trends. At the highest multiplicity, the data–model agreement is worse for most observables, indicating the need for further tuning and/or new model ingredients