Background Measurements in the Gran Sasso Underground Laboratory

The gamma background flux below 3000 keV in the Laboratori Nazionali del Gran Sasso (LNGS), Italy, has been measured using a 3" diameter NaI(Tl) detector at different underground positions: In hall A, hall B, the interferometer tunnel, and inside the Large Volume Detector (LVD). The integrated flux is 0.3--0.4 s$^{-1}$cm$^{-2}$ at the first three locations, and is lower by two orders of magnitude inside LVD. With the help of Monte Carlo simulations for every location, the contribution of the individual primordial isotopes to the background has been determined. Using an 11" diameter NaI(Tl) detector, the background neutron flux in the LNGS interferometer tunnel has been estimated. Within the uncertainties, the result agrees with those from other neutron measurements in the main halls.Comment: 6 pages, 6 figures, accepted versio

Mitigating discriminatory biases in success prediction models for venture capitals

The fairness of machine learning-based decision support systems has become a critical issue, also in the field of predicting the success of venture capital investment startups. Inappropriate allocation of venture capital, fueled by discriminatory biases, can lead to missed investment opportunities and poor investment decisions. Despite numerous studies that have addressed the prevalence of biases in venture capital allocation and decision support models, few have addressed the importance of incorporating fairness into the modeling process. In this study, we leverage invariant feature representation learning to develop a startup success prediction model using Crunchbase data, while satisfying group fairness. Our results show that discriminatory bias can be significantly reduced with minimal impact on model performance. Additionally, we demonstrate the versatility of our approach by mitigating multiple biases simultaneously. This work highlights the significance of addressing fairness in decisionsupport models to ensure equitable outcomes in venture capital investments

Making it into a successful series a funding : an analysis of Crunchbase and LinkedIn data

Startups are a key force driving economic development, and the success of these high-risk ventures can bring huge profits to venture capital firms. The ability to predict the success of startups is a major advantage for investors to outperform their competitors. In this study, we explore the potential of using publicly available LinkedIn profiles as an alternative and complementary data source to Crunchbase for predicting startup success. We provide a comprehensive review of the existing literature on the factors that influence startup success to create a large set of features for predictive modeling. We train two models for predicting startup success employing light gradient boosting that use LinkedIn data as a standalone and as a complementary data source, and compare them to baseline models based on Crunchbase data. We show that using LinkedIn as a complementary data source yields the best result with a mean area under the curve (AUC) value of 84%. We also provide a thorough analysis of what types of information contribute most to modeling startup success using the Shapley value method. Our models and analysis can be used to develop a decision support system to facilitate startup screening and the due diligence process for venture capital firms

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Prenatal exposures and exposomics of asthma

This review examines the causal investigation of preclinical development of childhood asthma using exposomic tools. We examine the current state of knowledge regarding early-life exposure to non-biogenic indoor air pollution and the developmental modulation of the immune system. We examine how metabolomics technologies could aid not only in the biomarker identification of a particular asthma phenotype, but also the mechanisms underlying the immunopathologic process. Within such a framework, we propose alternate components of exposomic investigation of asthma in which, the exposome represents a reiterative investigative process of targeted biomarker identification, validation through computational systems biology and physical sampling of environmental medi

Transient RNA structures underlie highly pathogenic avian influenza virus genesis

Highly pathogenic avian influenza viruses (HPAIVs) cause severe disease and high fatality in poultry1. They emerge exclusively from H5 and H7 low pathogenic avian influenza viruses (LPAIVs)2. Although insertion of a furin-cleavable multibasic cleavage site (MBCS) in the hemagglutinin gene was identified decades ago as the genetic basis for LPAIV-to-HPAIV transition3,4, the exact mechanisms underlying said insertion have remained unknown. Here we used an innovative combination of bioinformatic models to predict RNA structures forming around the influenza virus RNA polymerase during replication, and circular sequencing5 to reliably detect nucleotide insertions. We show that transient H5 hemagglutinin RNA structures predicted to trap the polymerase on purine-rich sequences drive nucleotide insertions characteristic of MBCSs, providing the first strong empirical evidence of RNA structure involvement in MBCS acquisition. Insertion frequencies at the H5 cleavage site were strongly affected by substitutions in flanking genomic regions altering predicted transient RNA structures. Introduction of H5-like cleavage site sequences and structures into an H6 hemagglutinin resulted in MBCS-yielding insertions never observed before in H6 viruses. Our results demonstrate that nucleotide insertions that underlie H5 HPAIV emergence result from a previously unknown RNA-structure-driven diversity-generating mechanism, which could be shared with other RNA viruses

Hybrid spintronic materials from conducting polymers with molecular quantum bits

Hybrid materials consisting of organic semiconductors and molecular quantum bits promise to provide a novel platform for quantum spintronic applications. However, investigations of such materials, elucidating both the electrical and quantum dynamical properties of the same material have never been reported. Here the preparation of hybrid materials consisting of conducting polymers and molecular quantum bits is reported. Organic field‐effect transistor measurements demonstrate that the favorable electrical properties are preserved in the presence of the qubits. Chemical doping introduces charge carriers into the material, and variable‐temperature charge transport measurements reveal the existence of mobile charge carriers at temperatures as low as 15 K. Importantly, quantum coherence of the qubit is shown to be preserved up to temperatures of at least 30 K, that is, in the presence of mobile charge carriers. These results pave the way for employing such hybrid materials in novel molecular quantum spintronic architectures.European Union's Horizon 2020 Research and Innovation ProgrammeCenter for Integrated Quantum Science and Technology (IQST)Carl Zeiss FoundationProjekt DEA

TRPA1 Is a Polyunsaturated Fatty Acid Sensor in Mammals

Fatty acids can act as important signaling molecules regulating diverse physiological processes. Our understanding, however, of fatty acid signaling mechanisms and receptor targets remains incomplete. Here we show that Transient Receptor Potential Ankyrin 1 (TRPA1), a cation channel expressed in sensory neurons and gut tissues, functions as a sensor of polyunsaturated fatty acids (PUFAs) in vitro and in vivo. PUFAs, containing at least 18 carbon atoms and three unsaturated bonds, activate TRPA1 to excite primary sensory neurons and enteroendocrine cells. Moreover, behavioral aversion to PUFAs is absent in TRPA1-null mice. Further, sustained or repeated agonism with PUFAs leads to TRPA1 desensitization. PUFAs activate TRPA1 non-covalently and independently of known ligand binding domains located in the N-terminus and 5th transmembrane region. PUFA sensitivity is restricted to mammalian (rodent and human) TRPA1 channels, as the drosophila and zebrafish TRPA1 orthologs do not respond to DHA. We propose that PUFA-sensing by mammalian TRPA1 may regulate pain and gastrointestinal functions

Stability subtypes of callous–unemotional traits and conduct disorder symptoms and their correlates

Callous unemotional traits and conduct disorder symptoms tend to co-occur across development, with existing evidence pointing to individual differences in the co-development of these problems. The current study identified groups of at risk adolescents showing stable (i.e., high on both conduct disorder and callous-unemotional symptoms, high only on either callous-unemotional or conduct disorder symptoms) or increasing conduct disorder and callous-unemotional symptoms. Data were collected from a sample of 2038 community adolescents between 15 and 18 years (1070 females, Mage = 16) of age. A longitudinal design was followed in that adolescent reports were collected at two time points, one year apart. Increases in conduct disorder symptoms and callous-unemotional traits were accompanied by increases in anxiety, depressive symptoms, narcissism, proactive and reactive aggression and decreases in self-esteem. Furthermore, adolescents with high and stable conduct disorder symptoms and callous-unemotional traits were consistently at high risk for individual, behavioral and contextual problems. In contrast, youth high on callous-unemotional traits without conduct disorder symptoms remained at low-risk for anxiety, depressive symptoms, narcissism, and aggression, pointing to a potential protective function of pure callous-unemotional traits against the development of psychopathological problems

Immunovirological response to combined antiretroviral therapy and drug resistance patterns in children: 1- and 2-year outcomes in rural Uganda

Children living with HIV continue to be in urgent need of combined antiretroviral therapy (ART). Strategies to scale up and improve pediatric HIV care in resource-poor regions, especially in sub-Saharan Africa, require further research from these settings. We describe treatment outcomes in children treated in rural Uganda after 1 and 2 years of ART start