Vibrational spectroscopy coupled to a multivariate analysis tiered approach for argentinean honey provenance confirmation

In the present work, the provenance discrimination of Argentinian honeys was used as case study to compare the capabilities of three spectroscopic techniques as fast screening platforms for honey authentication purposes. Multifloral honeys were collected among three main honey-producing regions of Argentina over four harvesting seasons. Each sample was fingerprinted by FT-MIR, NIR and FT-Raman spectroscopy. The spectroscopic platforms were compared on the basis of the classification performance achieved under a supervised chemometric approach. Furthermore, low- mid- and high-level data fusion were attempted in order to enhance the classification results. Finally, the best-performing solution underwent to SIMCA modelling with the purpose of reproducing a food authentication scenario. All the developed classification models underwent to a “year-by-year” validation strategy, enabling a sound assessment of their long-term robustness and excluding any issue of model overfitting. Excellent classification scores were achieved by all the technologies and nearly perfect classification was provided by FT-MIR. All the data fusion strategies provided satisfying outcomes, with the mid- and high-level approaches outperforming the low-level data fusion. However, no significant advantage over the FT-MIR alone was obtained. SIMCA modelling of FT-MIR data produced highly sensitive and specific models and an overall prediction ability improvement was achieved when more harvesting seasons were used for the model calibration (86.7% sensitivity and 91.1% specificity). The results obtained in the present work suggested the major potential of FT-MIR for fingerprinting-based honey authentication and demonstrated that accuracy levels that may be commercially useful can be reached. On the other hand, the combination of multiple vibrational spectroscopic fingerprints represents a choice that should be carefully evaluated from a cost/benefit standpoint within the industrial context

Relaxation of natural selection in the evolution of the giant lungfish genomes

Nonadaptive hypotheses on the evolution of eukaryotic genome size predict an expansion when the process of purifying selection becomes weak. Accordingly, species with huge genomes, such as lungfish, are expected to show a genome-wide relaxation signature of selection compared with other organisms. However, few studies have empirically tested this prediction using genomic data in a comparative framework. Here, we show that 1) the newly assembled transcriptome of the Australian lungfish, Neoceratodus forsteri, is characterized by an excess of pervasive transcription, or transcriptional leakage, possibly due to suboptimal transcriptional control, and 2) a significant relaxation signature in coding genes in lungfish species compared with other vertebrates. Based on these observations, we propose that the largest known animal genomes evolved in a nearly neutral scenario where genome expansion is less efficiently constraine

The Triggerless Data Acquisition System of the XENONnT Experiment

The XENONnT detector uses the latest and largest liquid xenon-based timeprojection chamber (TPC) operated by the XENON Collaboration, aimed atdetecting Weakly Interacting Massive Particles and conducting other rare eventsearches. The XENONnT data acquisition (DAQ) system constitutes an upgraded andexpanded version of the XENON1T DAQ system. For its operation, it reliespredominantly on commercially available hardware accompanied by open-source andcustom-developed software. The three constituent subsystems of the XENONnTdetector, the TPC (main detector), muon veto, and the newly introduced neutronveto, are integrated into a single DAQ, and can be operated both independentlyand as a unified system. In total, the DAQ digitizes the signals of 698photomultiplier tubes (PMTs), of which 253 from the top PMT array of the TPCare digitized twice, at $\times10$ and $\times0.5$ gain. The DAQ for the mostpart is a triggerless system, reading out and storing every signal that exceedsthe digitization thresholds. Custom-developed software is used to process theacquired data, making it available within $\mathcal{O}\left(10\text{ s}\right)$for live data quality monitoring and online analyses. The entire system withall the three subsystems was successfully commissioned and has been operatingcontinuously, comfortably withstanding readout rates that exceed $\sim500$ MB/sduring calibration. Livetime during normal operation exceeds $99\%$ and is$\sim90\%$ during most high-rate calibrations. The combined DAQ system hascollected more than 2 PB of both calibration and science data during thecommissioning of XENONnT and the first science run.<br

Searching for Heavy Dark Matter near the Planck Mass with XENON1T

Multiple viable theoretical models predict heavy dark matter particles with a mass close to the Planck mass, a range relatively unexplored by current experimental measurements. We use 219.4 days of data collected with the XENON1T experiment to conduct a blind search for signals from multiply interacting massive particles (MIMPs). Their unique track signature allows a targeted analysis with only 0.05 expected background events from muons. Following unblinding, we observe no signal candidate events. This Letter places strong constraints on spin-independent interactions of dark matter particles with a mass between 1×10$^{12}$ and 2×10$^{17}$  GeV/c$^2$. In addition, we present the first exclusion limits on spin-dependent MIMP-neutron and MIMP-proton cross sections for dark matter particles with masses close to the Planck scale

Design and performance of the field cage for the XENONnT experiment

The precision in reconstructing events detected in a dual-phase time projection chamber depends on an homogeneous and well understood electric field within the liquid target. In the XENONnT TPC the field homogeneity is achieved through a double-array field cage, consisting of two nested arrays of field shaping rings connected by an easily accessible resistor chain. Rather than being connected to the gate electrode, the topmost field shaping ring is independently biased, adding a degree of freedom to tune the electric field during operation. Two-dimensional finite element simulations were used to optimize the field cage, as well as its operation. Simulation results were compared to $^{83m} Kr$ calibration data. This comparison indicates an accumulation of charge on the panels of the TPC which is constant over time, as no evolution of the reconstructed position distribution of events is observed. The simulated electric field was then used to correct the charge signal for the field dependence of the charge yield. This correction resolves the inconsistent measurement of the drift electron lifetime when using different calibrations sources and different field cage tuning voltages

Detector signal characterization with a Bayesian network in XENONnT

We developed a detector signal characterization model based on a Bayesian network trained on the waveform attributes generated by a dual-phase xenon time projection chamber. By performing inference on the model, we produced a quantitative metric of signal characterization and demonstrate that this metric can be used to determine whether a detector signal is sourced from a scintillation or an ionization process. We describe the method and its performance on electronic-recoil (ER) data taken during the first science run of the XENONnT dark matter experiment. We demonstrate the first use of a Bayesian network in a waveform-based analysis of detector signals. This method resulted in a 3% increase in ER event-selection efficiency with a simultaneously effective rejection of events outside of the region of interest. The findings of this analysis are consistent with the previous analysis from XENONnT, namely a background-only fit of the ER data

Search for events in XENON1T associated with Gravitational Waves

We perform a blind search for particle signals in the XENON1T dark matter detector that occur close in time to gravitational wave signals in the LIGO and Virgo observatories. No particle signal is observed in the nuclear recoil, electronic recoil, CE$\nu$NS, and S2-only channels within $\pm$ 500 seconds of observations of the gravitational wave signals GW170104, GW170729, GW170817, GW170818, and GW170823. We use this null result to constrain mono-energetic neutrinos and Beyond Standard Model particles emitted in the closest coalescence GW170817, a binary neutron star merger. We set new upper limits on the fluence (time-integrated flux) of coincident neutrinos down to 17 keV at 90% confidence level. Furthermore, we constrain the product of coincident fluence and cross section of Beyond Standard Model particles to be less than $10^{-29}$ cm$^2$/cm$^2$ in the [5.5-210] keV energy range at 90% confidence level

First Dark Matter Search with Nuclear Recoils from the XENONnT Experiment

We report on the first search for nuclear recoils from dark matter in the form of weakly interacting massive particles (WIMPs) with the XENONnT experiment, which is based on a two-phase time projection chamber with a sensitive liquid xenon mass of 5.9 ton. During the (1.09±0.03)  ton yr exposure used for this search, the intrinsic $^{85}$Kr and $^{222}$Rn concentrations in the liquid target are reduced to unprecedentedly low levels, giving an electronic recoil background rate of (15.8±1.3)  events/ton yr keV in the region of interest. A blind analysis of nuclear recoil events with energies between 3.3 and 60.5 keV finds no significant excess. This leads to a minimum upper limit on the spin-independent WIMP-nucleon cross section of 2.58×10$^{47}$  cm$^2$ for a WIMP mass of 28  GeV/c$^2$ at 90% confidence level. Limits for spin-dependent interactions are also provided. Both the limit and the sensitivity for the full range of WIMP masses analyzed here improve on previous results obtained with the XENON1T experiment for the same exposure

Searching for Heavy Dark Matter near the Planck Mass with XENON1T

Multiple viable theoretical models predict heavy dark matter particles with a mass close to the Planck mass, a range relatively unexplored by current experimental measurements. We use 219.4 days of data collected with the XENON1T experiment to conduct a blind search for signals from Multiply-Interacting Massive Particles (MIMPs). Their unique track signature allows a targeted analysis with only 0.05 expected background events from muons. Following unblinding, we observe no signal candidate events. This work places strong constraints on spin-independent interactions of dark matter particles with a mass between 1$\times$10$^{12}\,$GeV/c$^2$ and 2$\times$10$^{17}\,$GeV/c$^2$. In addition, we present the first exclusion limits on spin-dependent MIMP-neutron and MIMP-proton cross-sections for dark matter particles with masses close to the Planck scale.Comment: 7 pages, 6 figure