Showing papers by "Jožef Stefan Institute published in 2018"

Scalar leptoquarks from grand unified theories to accommodate the B -physics anomalies

Abstract: We address the $B$-physics anomalies within a two scalar leptoquark model. The low-energy flavor structure of our setup originates from two $SU(5)$ operators that relate Yukawa couplings of the two leptoquarks. The proposed scenario has a UV completion, can accommodate all measured lepton flavor universality ratios in $B$-meson decays, is consistent with related flavor observables, and is compatible with direct searches at the LHC. We provide prospects for future discoveries of the two light leptoquarks at the LHC and predict several yet-to-be-measured flavor observables.

Closing the window on single leptoquark solutions to the B-physics anomalies

Abstract: We examine various scenarios in which the Standard Model is extended by a light leptoquark state to solve for one or both B-physics anomalies, viz. $$ {R}_{D^{\left(*\right)}}^{\exp }>{R}_{D^{\left(*\right)}}^{\mathrm{SM}} $$ or/and $$ {R}_{K^{\left(*\right)}}^{\exp }>{R}_{K^{\left(*\right)}}^{\mathrm{SM}} $$ . To do so we combine the constraints arising both from the low-energy observables and from direct searches at the LHC. We find that none of the scalar leptoquarks of mass mLQ ≃ 1 TeV can alone accommodate the above mentioned anomalies. The only single leptoquark scenario which can provide a viable solution for mLQ ≃ 1÷2 TeV is a vector leptoquark, known as U1, which we re-examine in its minimal form (letting only left-handed couplings to have non-zero values). We find that the limits deduced from direct searches are complementary to the low-energy physics constraints. In particular, we find a rather stable lower bound on the lepton flavor violating b → sl 1 ± l 2 ∓ modes, such as ℬ(B → Kμτ). Improving the experimental upper bound on ℬ(B → Kμτ) by two orders of magnitude could compromise the viability of the minimal U1 model as well.

Closing the window on single leptoquark solutions to the $B$-physics anomalies

Abstract: We examine various scenarios in which the Standard Model is extended by a light leptoquark state to solve for one or both $B$-physics anomalies, viz. $R_{D^{(\ast)}}^\mathrm{exp}> R_{D^{(\ast)}}^\mathrm{SM}$ or/and $R_{K^{(\ast)}}^\mathrm{exp}< R_{K^{(\ast)}}^\mathrm{SM}$. To do so we combine the constraints arising both from the low-energy observables and from direct searches at the LHC. We find that none of the scalar leptoquarks of mass $m_\mathrm{LQ} \simeq 1$ TeV can alone accommodate the above mentioned anomalies. The only single leptoquark scenario which can provide a viable solution for $m_\mathrm{LQ} \simeq 1÷2$ TeV is a vector leptoquark, known as $U_1$, which we re-examine in its minimal form (letting only left-handed couplings to have non-zero values). We find that the limits deduced from direct searches are complementary to the low-energy physics constraints. In particular, we find a rather stable lower bound on the lepton flavor violating $b\to s\ell_1^\pm\ell_2^\mp$ modes, such as $\mathcal{B}(B\to K\mu\tau)$. Improving the experimental upper bound on $\mathcal{B}(B\to K\mu\tau)$ by two orders of magnitude could compromise the viability of the minimal $U_1$ model as well.

Observation of two types of fractional excitation in the Kitaev honeycomb magnet

Abstract: Quantum spin liquid is a disordered but highly entangled magnetic state with fractional spin excitations1. The ground state of an exactly solved Kitaev honeycomb model is perhaps its clearest example2. Under a magnetic field, a spin flip in this model fractionalizes into two types of anyon, a quasiparticle with more complex exchange statistics than standard fermions or bosons: a pair of gauge fluxes and a Majorana fermion2,3. Here, we demonstrate this kind of fractionalization in the Kitaev paramagnetic state of the honeycomb magnet α-RuCl3. The spin excitation gap determined by nuclear magnetic resonance consists of the predicted Majorana fermion contribution following the cube of the applied magnetic field2,4,5, and a finite zero-field contribution matching the predicted size of the gauge flux gap2,6. The observed fractionalization into gapped anyons survives in a broad range of temperatures and magnetic fields, which establishes α-RuCl3 as a unique platform for future investigations of anyons.

Improving Indoor Localization Using Convolutional Neural Networks on Computationally Restricted Devices

Abstract: Indoor localization is one of the key enablers for various application and service areas that rely on precise locations of people, goods, and assets, ranging from home automation and assisted living to increased automation of production and logistic processes and wireless network optimization. Existing solutions provide various levels of precision, which also depends on the complexity of the indoor radio environment. In this paper, we propose two methods for reducing the localization error in indoor non-line-of-sight (NLoS) conditions using raw channel impulse response (CIR) information obtained from ultra-wide band radios requiring no prior knowledge about the radio environment. The methods are based on NLoS channel classification and ranging error regression models, both using convolutional neural networks (CNNs) and implemented in the TensorFlow computational framework. We first show that NLoS channel classification using raw CIR data outperforms existing approaches that are based on derived input signal features. We further demonstrate that the predicted NLoS channel state and predicted ranging error information, used in combination with least squares (LS) and weighted LS location estimation algorithms, significantly improve indoor localization performance. We also evaluate the computational performance and suitability of the proposed CNN-based algorithms on various computing platforms with a wide range of different capabilities and show that in a distributed localization system, they can also be used on computationally restricted devices.

Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign

Abstract: We present the results and the findings of the Second VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects. The campaign was organized as part of the fifth edition of the VarDial workshop, collocated with COLING’2018. This year, the campaign included five shared tasks, including two task re-runs – Arabic Dialect Identification (ADI) and German Dialect Identification (GDI) –, and three new tasks – Morphosyntactic Tagging of Tweets (MTT), Discriminating between Dutch and Flemish in Subtitles (DFS), and Indo-Aryan Language Identification (ILI). A total of 24 teams submitted runs across the five shared tasks, and contributed 22 system description papers, which were included in the VarDial workshop proceedings and are referred to in this report.

Spin-Orbit Coupling and Electronic Correlations in Sr 2 RuO 4

Abstract: We investigate the interplay of spin-orbit coupling (SOC) and electronic correlations in ${\mathrm{Sr}}_{2}{\mathrm{RuO}}_{4}$ using dynamical mean-field theory. We find that SOC does not affect the correlation-induced renormalizations, which validates Hund's metal picture of ruthenates even in the presence of the sizable SOC relevant to these materials. Nonetheless, SOC is found to change significantly the electronic structure at $k$ points where a degeneracy applies in its absence. We explain why these two observations are consistent with one another and calculate the effects of SOC on the correlated electronic structure. The magnitude of these effects is found to depend on the energy of the quasiparticle state under consideration, leading us to introduce the notion of an energy-dependent quasiparticle spin-orbit coupling ${\ensuremath{\lambda}}^{*}(\ensuremath{\omega})$. This notion is generally applicable to all materials in which both the spin-orbit coupling and electronic correlations are sizable.

Robotic assembly solution by human-in-the-loop teaching method based on real-time stiffness modulation

Abstract: We propose a novel human-in-the-loop approach for teaching robots how to solve assembly tasks in unpredictable and unstructured environments. In the proposed method the human sensorimotor system is integrated into the robot control loop though a teleoperation setup. The approach combines a 3-DoF end-effector force feedback with an interface for modulation of the robot end-effector stiffness. When operating in unpredictable and unstructured environments, modulation of limb impedance is essential in terms of successful task execution, stability and safety. We developed a novel hand-held stiffness control interface that is controlled by the motion of the human finger. A teaching approach was then used to achieve autonomous robot operation. In the experiments, we analysed and solved two part-assembly tasks: sliding a bolt fitting inside a groove and driving a self-tapping screw into a material of unknown properties. We experimentally compared the proposed method to complementary robot learning methods and analysed the potential benefits of direct stiffness modulation in the force-feedback teleoperation.

A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers.

Abstract: The adoption of advanced Internet of Things (IoT) technologies has impressively improved in recent years by placing such services at the extreme Edge of the network. There are, however, specific Quality of Service (QoS) trade-offs that must be considered, particularly in situations when workloads vary over time or when IoT devices are dynamically changing their geographic position. This article proposes an innovative capillary computing architecture, which benefits from mainstream Fog and Cloud computing approaches and relies on a set of new services, including an Edge/Fog/Cloud Monitoring System and a Capillary Container Orchestrator. All necessary Microservices are implemented as Docker containers, and their orchestration is performed from the Edge computing nodes up to Fog and Cloud servers in the geographic vicinity of moving IoT devices. A car equipped with a Motorhome Artificial Intelligence Communication Hardware (MACH) system as an Edge node connected to several Fog and Cloud computing servers was used for testing. Compared to using a fixed centralized Cloud provider, the service response time provided by our proposed capillary computing architecture was almost four times faster according to the 99th percentile value along with a significantly smaller standard deviation, which represents a high QoS.

Topological Function Optimization for Continuous Shape Matching

Abstract: We present a novel approach for optimizing real-valued functions based on a wide range of topological criteria. In particular, we show how to modify a given function in order to remove topological noise and to exhibit prescribed topological features. Our method is based on using the previously-proposed persistence diagrams associated with real-valued functions, and on the analysis of the derivatives of these diagrams with respect to changes in the function values. This analysis allows us to use continuous optimization techniques to modify a given function, while optimizing an energy based purely on the values in the persistence diagrams. We also present a procedure for aligning persistence diagrams of functions on different domains, without requiring a mapping between them. Finally, we demonstrate the utility of these constructions in the context of the functional map framework, by first giving a characterization of functional maps that are associated with continuous point-to-point correspondences, directly in the functional domain, and then by presenting an optimization scheme that helps to promote the continuity of functional maps, when expressed in the reduced basis, without imposing any restrictions on metric distortion. We demonstrate that our approach is efficient and can lead to improvement in the accuracy of maps computed in practice.

Volume Law and Quantum Criticality in the Entanglement Entropy of Excited Eigenstates of the Quantum Ising Model

Abstract: Much has been learned about universal properties of entanglement entropies in ground states of quantum many-body lattice systems. Here we unveil universal properties of the average bipartite entanglement entropy of eigenstates of the paradigmatic quantum Ising model in one dimension. The leading term exhibits a volume-law scaling that we argue is universal for translationally invariant quadratic models. The subleading term is constant at the critical field for the quantum phase transition and vanishes otherwise (in the thermodynamic limit); i.e., the critical field can be identified from subleading corrections to the average (over all eigenstates) entanglement entropy.

Keung-Senjanović process at the LHC: From lepton number violation to displaced vertices to invisible decays

Abstract: In the context of left-right symmetry, we revisit the Keung-Senjanovi\ifmmode \acute{c}\else \'{c}\fi{} production of right-handed ${W}_{R}$ bosons and heavy neutrinos $N$ at high energy colliders. We develop a multibinned sensitivity measure and use it to estimate the sensitivity for the entire range of $N$ masses, spanning the standard and merged prompt signals, displaced vertices and the invisible $N$ region. The estimated sensitivity of the LHC with 300/fb integrated luminosity ranges from 5 to beyond 7 TeV, while the future 33(100) TeV collider's reach with 3/ab extends to 12(26) TeV.

The creation of electric wind due to the electrohydrodynamic force

Abstract: Understanding the interactions between ionized matter and neutral particles is a prerequisite for discovering their impact on natural phenomena. One such phenomenon is the electric wind, which supposedly occurs due to the charged particle-neutral coupling in systems of weakly ionized gases, but this mechanism remains unclear. Here, we report direct evidence that electric wind is caused by an electrohydrodynamic force generated by the charged particle drag as a result of the momentum transfer from electrons/ions to neutrals. The model experiment is based on a pulsed plasma jet as a source of weakly ionized gases generated in the helium gas at atmospheric pressure using Schlieren photography. Studying the helium gas flow trajectories at different discharge parameters allows one to distinguish between the effects of streamer propagation or space charge drift causing the electric wind as well as to determine the role of electrons and (positive) ions in wind generation.

Continuous remote monitoring of COPD patients—justification and explanation of the requirements and a survey of the available technologies

Abstract: Remote patient monitoring should reduce mortality rates, improve care, and reduce costs. We present an overview of the available technologies for the remote monitoring of chronic obstructive pulmonary disease (COPD) patients, together with the most important medical information regarding COPD in a language that is adapted for engineers. Our aim is to bridge the gap between the technical and medical worlds and to facilitate and motivate future research in the field. We also present a justification, motivation, and explanation of how to monitor the most important parameters for COPD patients, together with pointers for the challenges that remain. Additionally, we propose and justify the importance of electrocardiograms (ECGs) and the arterial carbon dioxide partial pressure (PaCO2) as two crucial physiological parameters that have not been used so far to any great extent in the monitoring of COPD patients. We cover four possibilities for the remote monitoring of COPD patients: continuous monitoring during normal daily activities for the prediction and early detection of exacerbations and life-threatening events, monitoring during the home treatment of mild exacerbations, monitoring oxygen therapy applications, and monitoring exercise. We also present and discuss the current approaches to decision support at remote locations and list the normal and pathological values/ranges for all the relevant physiological parameters. The paper concludes with our insights into the future developments and remaining challenges for improvements to continuous remote monitoring systems. Graphical abstract ᅟ.

Selective imaging of cathepsin L in breast cancer by fluorescent activity-based probes

Abstract: Cysteine cathepsins normally function in the lysosomal degradation system where they are critical for the maintenance of cellular homeostasis and the MHC II immune response, and have been found to have major roles in several diseases and in tumor progression. Selective visualization of individual protease activity within a complex proteome is of major importance to establish their roles in both normal and tumor cells, thereby facilitating our understanding of the regulation of proteolytic networks. A generally accepted means to monitor protease activity is the use of small molecule substrates and activity-based probes. However, there are eleven human cysteine cathepsins, with a few of them displaying overlapping substrate specificity, making the development of small molecules that selectively target a single cathepsin very challenging. Here, we utilized HyCoSuL, a positional scanning substrate approach, to develop a highly-selective fluorogenic substrate and activity-based probe for monitoring cathepsin L activity in the breast cancer cell line MDA-MB-231. Use of this probe enabled us to distinguish the activity of cathepsin L from that of other cathepsins, particularly cathepsin B, which is abundant and ubiquitously expressed in normal and transformed cell types. We found that cathepsin L localization in MDA-MB-231 cells greatly overlaps with that of cathepsin B, however, several cathepsin L-rich lysosomes lacked cathepsin B activity. Overall, these studies demonstrate that HyCoSuL-derived small molecule probes are valuable tools to image cathepsin L activity in living cells. This approach thus enables evaluation of cathepsin L function in tumorigenesis and is applicable to other cysteine cathepsins.

Active nematic emulsions

Abstract: The formation of emulsions from multiple immiscible fluids is governed by classical concepts such as surface tension, differential chemical affinity and viscosity, and the action of surface-active agents. Much less is known about emulsification when one of the components is active and thus inherently not constrained by the laws of thermodynamic equilibrium. We demonstrate one such realization consisting in the encapsulation of an active liquid crystal (LC)–like gel, based on microtubules and kinesin molecular motors, into a thermotropic LC. These active nematic emulsions exhibit a variety of dynamic behaviors that arise from the cross-talk between topological defects separately residing in the active and passive components. Using numerical simulations, we show a feedback mechanism by which active flows continuously drive the passive defects that, in response, resolve the otherwise degenerated trajectories of the active defects. Our experiments show that the choice of surfactant, which stabilizes the active/passive interface, allows tuning the regularity of the self-sustained dynamic events. The hybrid active-passive system demonstrated here provides new perspectives for dynamic self-assembly driven by an active material but regulated by the equilibrium properties of the passive component.

An IAEA multi-technique X-ray spectrometry endstation at Elettra Sincrotrone Trieste: benchmarking results and interdisciplinary applications.

Abstract: The International Atomic Energy Agency (IAEA) jointly with the Elettra Sincrotrone Trieste (EST) operates a multipurpose X-ray spectrometry endstation at the X-ray Fluorescence beamline (10.1L). The facility has been available to external users since the beginning of 2015 through the peer-review process of EST. Using this collaboration framework, the IAEA supports and promotes synchrotron-radiation-based research and training activities for various research groups from the IAEA Member States, especially those who have limited previous experience and resources to access a synchrotron radiation facility. This paper aims to provide a broad overview about various analytical capabilities, intrinsic features and performance figures of the IAEA X-ray spectrometry endstation through the measured results. The IAEA–EST endstation works with monochromatic X-rays in the energy range 3.7–14 keV for the Elettra storage ring operating at 2.0 or 2.4 GeV electron energy. It offers a combination of different advanced analytical probes, e.g. X-ray reflectivity, X-ray absorption fine-structure measurements, grazing-incidence X-ray fluorescence measurements, using different excitation and detection geometries, and thereby supports a comprehensive characterization for different kinds of nanostructured and bulk materials.

Differential expression of microRNAs and other small RNAs in muscle tissue of patients with ALS and healthy age-matched controls.

Abstract: Amyotrophic lateral sclerosis is a late-onset disorder primarily affecting motor neurons and leading to progressive and lethal skeletal muscle atrophy. Small RNAs, including microRNAs (miRNAs), can serve as important regulators of gene expression and can act both globally and in a tissue-/cell-type-specific manner. In muscle, miRNAs called myomiRs govern important processes and are deregulated in various disorders. Several myomiRs have shown promise for therapeutic use in cellular and animal models of ALS; however, the exact miRNA species differentially expressed in muscle tissue of ALS patients remain unknown. Following small RNA-Seq, we compared the expression of small RNAs in muscle tissue of ALS patients and healthy age-matched controls. The identified snoRNAs, mtRNAs and other small RNAs provide possible molecular links between insulin signaling and ALS. Furthermore, the identified miRNAs are predicted to target proteins that are involved in both normal processes and various muscle disorders and indicate muscle tissue is undergoing active reinnervation/compensatory attempts thus providing targets for further research and therapy development in ALS.

Disease progression in Parkinson subtypes: the PPMI dataset

Abstract: Discrete patterns of progression have been suggested for patients with Parkinson disease and presenting tremor dominant (TD) or postural instability gait disorders (PIGD). However, longitudinal prospective assessments need to take into consideration the variability in clinical manifestations and the evidence that only 40% of initially classified PIGD remain in this subtype at subsequent visits. We analyzed clinical progression of PIGD compared to TD using longitudinal clinical data from the PPMI. Given the reported instability of such clinical classification, we only included patients who were reported as PIGD/TD at each visit during the 4-year observation. We used linear mixed-effects models to test differences in progression in these subgroups in 51 dependent variables. There were 254 patients with yearly assessment. The number of PIGD was 36/254 vs 144/254 TD. PIGD had more severe motor disease at baseline but progressed faster than TD only in three non-motor items of the MDS-UPDRS: cognitive impairment, hallucinations, and psychosis plus features of DDS. Our analysis also showed in PIGD faster increase in the average time with dyskinesia. PIGD are characterized by more severe disease manifestations at diagnosis and greater cognitive progression, more frequent hallucinations, psychosis as well as features of DDS than TD patients. We interpret these findings as expression of greater cortical and subcortical involvement in PIGD already at onset. Since PIGD/TD classification is very unstable at onset, our analysis based on stricter definition criteria provides important insight for clinical trial stratification and definition of related outcome measures.