Miracle-dz/UniFAR-FTUs huggingface dataset:
New methodologies to evaluate the consistency of emoji sentiment lexica and alternatives to generate them in a fully automatic unsupervised

Sentiment analysis aims at detecting sentiment polarities in unstructured Internet information. A relevant part of this information for that purpose, emojis, whose use in Twitter has grown considerably in these years, deserves attention. However, every time a new version of Unicode is released, finding out the sentiment users wish to express with a new emoji is challenging. In [KNSSM15], an Emoji Sentiment Ranking lexicon from manual annotations of messages in different languages was presented. The quality of these annotations affects directly the quality of possible generated emoji sentiment lexica (high quality corresponds to high self-agreement and inter-agreement). In many cases, the creators of the datasets do not provide any quality metrics, so it is necessary to use another strategy to detect this issue. Therefore, we propose an automatic approach to identify and manage inconsistent manual sentiment annotations. Then, relying on a new approach to generate emoji sentiment lexica of good quality, we compare two such lexica with lexica created from manually annotated datasets with poor and high qualities. Copyright c © 2018 held by the author(s). Copying permitted for private and academic purposes. In: S. Wijeratne, E. Kiciman, H. Saggion, A. Sheth (eds.): Proceedings of the 1st International Workshop on Emoji Understanding and Applications in Social Media (Emoji2018), Stanford, CA, USA, 25-JUN-2018, published at http://ceur-ws.org
Role of hyperfine interaction for cavity-mediated coupling between spin qubits

We consider two qubits interacting by means of an optical cavity, where each qubit is represented by a single electron spin confined to a quantum dot. It is known that electron spins in III-V semiconductor quantum dots are affected by the decoherence due to the hyperfine interaction with nuclear spins. Here we show that the interaction between two qubits is influenced by the Overhauser field as well. Starting from an unpolarizied nuclear ensemble, we investigate the dependance of the fidelities for two-qubit gates on the Overhauser field. We include the hyperfine interaction perturbatively to second order in our analytical results, and to arbitrary precision numerically.
Integrating Online Learning and Adaptive Control in Queueing Systems with Uncertain Payoffs

We study task assignment in online service platforms where un-labeled clients arrive according to a stochastic process and each client brings a random number of tasks. As tasks are assigned to servers, they produce client/server-dependent random payoffs. The goal of the system operator is to maximize the expected payoff per unit time subject to the servers' capacity constraints. However, both the statistics of the dynamic client population and the client-specific payoff vectors are unknown to the operator. Thus, the operator must design task-assignment policies that integrate adaptive control (of the queueing system) with online learning (of the clients' payoff vectors). A key challenge in such integration is how to account for the nontrivial closed-loop interactions between the queueing process and the learning process, which may significantly degrade system performance. We propose a new utility-guided online learning and task assignment algorithm that seamlessly integrates learning with control to address such difficulty. Our analysis shows that, compared to an oracle that knows all client dynamics and payoff vectors beforehand, the gap of the expected payoff per unit time of our proposed algorithm in a finite $T$ horizon is bounded by $\beta_{1}/V+\beta_{2}\sqrt{\log N/N}+\beta_{3}N(V+1)/T$, where $V$ is a tuning parameter of the algorithm, and $\beta_{1}, \beta_{2}, \beta_{3}$ only depend on arrival/service rates and the number of client classes/servers. Through simulations, we show that our proposed algorithm significantly outperforms a myopic matching policy and a standard queue-length based policy that does not explicitly address the closed-loop interactions between queueing and learning.
Stochastic boundedness of state trajectories of stable LTI systems in the presence of non-vanishing stochastic perturbation

This paper studies stochastic boundedness of trajectories of a non-vanishing stochastically perturbed stable linear time-invariant system. First, two definitions on stochastic boundedness are presented, then, the boundedness is analyzed via Lyapunov theory. A theorem is proposed, which shows that under a condition on the Lipchitz constant of the perturbation kernel, the trajectories remain stochastically bounded, and the bounds are calculated. Also, the limiting behaviour of the trajectories is studied. At the end, an illustrative example is presented, which shows the effectiveness of the proposed theory.
Denoising-based Vector AMP

The D-AMP methodology, recently proposed by Metzler, Malek i, and Baraniuk, allows one to plug in sophisticated denoisers like BM3D into the AMP algorithm to achieve stateof-the-art compressive image recovery. But AMP diverges with small deviations from the i.i. d. -Gaussian as sumption on the measurement matrix. Recently, the VAMP algorithm has been proposed to fix this problem. In this work, we show that the benefits of VAMP extend to D-VAMP. Consider the problem of recovering a (vectorized) image x0 ∈ R from compressive (i.e., M ≪ N ) noisy linear measurements y = Φx0 +w ∈ R M , (1) known as “compressive imaging. ” The “sparse” approach to th is problem exploits sparsity in the coefficients v0 , Ψx0 ∈ R N of an orthonormal wavelet transform Ψ. The idea is to rewrite (1) as y = Av0 +w for A , ΦΨ , (2) recover an estimatê v of v0 from y, and then construct the image estimate as x̂ = Ψ v̂. Although many algorithms have been proposed for sparse reco very of v0, a notable one is the approximate message passing (AMP) algorithm from [1]. It is computation ally efficient (i.e., one multiplication byA andA per iteration and relatively few iterations) and its perfor mance, whenM andN are large andΦ is zero-mean i.i. d. Gaussian, is rigorously characterized by a scalar state evo lution. A variant called “denoising-based AMP” (D-AMP) was recentl y proposed [2] fordirect recovery ofx0 from (1). It exploits the fact that, at iteration t, AMP constructs a pseudo-measurement of the form v0 + N (0, σ t I) with knownσ t , which is amenable to any image denoising algorithm. By plug gin in a state-of-the-art image denoiser like BM3D [3], D-AMP yields state-of-the-art compressive i maging. AMP and D-AMP, however, have a serious weakness: they diverg e under small deviations from the zero-mean i.i. d. Gaussian assumption on Φ, such as non-zero mean or mild ill-conditioning. A robust al ternative called “vector AMP” (VAMP) was recently proposed [4]. VAMP has similar comp lexity to AMP and a rigorous state evolution November 7, 2016 DRAFT
Dynamic consistency in incomplete information games with multiple priors

This paper generalizes the concept of Sequential Equilibrium to allow for ambiguous incomplete information about types or states. We characterize conditions that ensure existence of Sequential Equilibria under ambiguous incomplete information. Under these conditions players form subjective prior belief sets that satisfy a rectangularity condition which leads to dynamically consistent behavior. Furthermore, we give an example which shows that ambiguity can introduce new Sequential Equilibria.
Orthopaedic Surgery for Skeletal Metastases

Advances in oncological therapies have resulted in improved survival in patients with skeletal metastases. The resultant effect is that the skeletal metastases result in an increased incidence of pathological fracture and bone pain. This article focuses on the options available to the orthopaedic surgeon in the treatment of patients with skeletal metastases. It covers the controversial area of prophylactic fixation and the roles of conventional internal fixation, cement, arthroplasty and endoprosthetic replacement. The role of radiotherapy in the management of patients with surgically treated skeletal metastases is highlighted. Treatment for these patients is always individualised and should always be subject to a multidisciplinary approach. Despite the prognosis, satisfying results can be obtained that achieve the aims of palliative surgery, namely pain relief and maintenance of or improvement in function.
Process Mining as a Business Process Discovery Technique

Process Mining as a Business Process Discovery Technique Business Process Management (BPM) is an important aspect of organizations excellence and global competitiveness. The main indicator of an efficient BPM in place is the level of conformance of its implementation to its original process model. Some processes are implemented based on what IT people think rather than what process guidelines state. Process Mining is a promising technique for extracting a process model based on its real time behavior. In this research, an ITIL compliant Incident Management Process of a renowned Telecom provider was selected to construct its process model. Results of applying three mining algorithms showed that there are different process scenarios implemented by the process engine. This entails further investigation to identify the most credible scenario to the original business process requirements. This research is part of on-going research to compare the efficiency of process mining tools over formal inspection techniques as a process discovery approach.
Thermal conductivity measurements via time-domain thermoreflectance for the characterization of radiation induced damage

The progressive build up of fission products inside different nuclear reactor components can lead to significant damage of the constituent materials. We demonstrate the use of time-domain thermoreflectance (TDTR), a nondestructive thermal measurement technique, to study the effects of radiation damage on material properties. We use TDTR to report on the thermal conductivity of optimized ZIRLO, a material used as fuel cladding in nuclear reactors. We find that the thermal conductivity of optimized ZIRLO is 10.7 ± 1.8 W m^−1 K^−1 at room temperature. Furthermore, we find that the thermal conductivities of copper–niobium nanostructured multilayers do not change with helium ion irradiation doses of 10^15 cm^−2 and ion energy of 200 keV, demonstrating the potential of heterogeneous multilayer materials for radiation tolerant coatings. Finally, we compare the effect of ion doses and ion beam energies on the measured thermal conductivity of bulk silicon. Our results demonstrate that TDTR can be used to quantify depth dependent damage.
Efficiently Verifiable Sufficient Conditions for Deadlock-freedom of Large Concurrent Programs ( Technical Report )

We present two polynomial-time algorithms for automatic verification of deadlock-freedom of large finite-state concurrent programs. We consider shared-memory concurrent programs in which a process can nondeterministically choose amongst several (enabled) actions at any step. Our algorithms are sound but incomplete: if they return a positive answer, then the program is indeed deadlock-free, while a negative answer conveys no information: the program might be deadlock free, but “fails” the test that our algorithms apply. Our algorithms apply to programs which are expressed in a particular syntactic form, in which variables are shared between pairs of processes, and the synchronization code for each pair of interacting processes is expressed separately from synchronization code for other (even intersecting) pairs of processes. The first algorithm is an improvement of the deadlock check of [2]. Its complexity is polynomial in all its parameters, as opposed to the exponential complexity of the deadlock check of [2]. It also scales well and can be applied to very large concurrent programs. The second algorithm involves a conceptually new construction of a global wait-for graph for all processes. Its running time is also polynomial in all its parameters, and it is more discriminating than the first algorithm. The algorithms apply to systems with similar and with dissimilar processes. We illustrate our algorithms by applying them to several examples of concurrent programs that implement mutual exclusion and priority queues. To the best of our knowledge, this is the first work that describes polynomially checkable conditions for assuring deadlock freedom of systems of similar and dissimilar processes.
Photoinduced pure spin-current injection in graphene with Rashba spin-orbit interaction

We propose a photoexcitation scheme for pure spin-current generation in graphene subject to a Rashba spin-orbit coupling. Although excitation using circularly polarized light does not result in optical orientation of spins in graphene unless an additional magnetic field is present, we show that excitation with linearly polarized light at normal incidence yields spin-current injection without magnetic field. Spins are polarized within the graphene plane and are displaced in opposite directions, with no net charge displacement. The direction of the spin current is determined by the linear polarization axis of the light, and the injection rate is proportional to the intensity. The technique is tunable via an applied bias voltage and is accessible over a wide frequency range. We predict a spin-current polarization as high as 75% for photon frequencies comparable to the Rashba frequency. Spin-current injection via optical methods removes the need for ferromagnetic contacts, which have been identified as a possible source of spin scattering in electrical spin injection in graphene.
AIRBORNE LIGHT DETECTION AND RANGING ( LIDAR ) DERIVED DEFORMATION FROM THE MW 6 . 0 24 AUGUST , 2014 SOUTH NAPA EARTHQUAKE ESTIMATED BY TWO AND THREE DIMENSIONAL POINT CLOUD CHANGE DETECTION TECHNIQUES

Remote sensing via LiDAR (Light Detection And Ranging) has proven extremely useful in both Earth science and hazard related studies. Surveys taken before and after an earthquake for example, can provide decimeter-level, 3D near-field estimates of land deformation that offer better spatial coverage of the near field rupture zone than other geodetic methods (e.g., InSAR, GNSS, or alignment array). In this study, we compare and contrast estimates of deformation obtained from different pre and post-event airborne laser scanning (ALS) data sets of the 2014 South Napa Earthquake using two change detection algorithms, Iterative Control Point (ICP) and Particle Image Velocimetry (PIV). The ICP algorithm is a closest point based registration algorithm that can iteratively acquire three dimensional deformations from airborne LiDAR data sets. By employing a newly proposed partition scheme, “moving window,” to handle the large spatial scale point cloud over the earthquake rupture area, the ICP process applies a rigid registration of data sets within an overlapped window to enhance the change detection results of the local, spatially varying surface deformation near-fault. The other algorithm, PIV, is a well-established, two dimensional image co-registration and correlation technique developed in fluid mechanics research and later applied to geotechnical studies. Adapted here for an earthquake with little vertical movement, the 3D point cloud is interpolated into a 2D DTM image and horizontal deformation is determined by assessing the cross-correlation of interrogation areas within the images to find the most likely deformation between two areas. Both the PIV process and the ICP algorithm are further benefited by a presented, novel use of urban geodetic markers. Analogous to the persistent scatterer technique employed with differential radar observations, this new LiDAR application exploits a classified point cloud dataset to assist the change detection algorithms. Ground deformation results and statistics from these techniques are presented and discussed here with supplementary analyses of the differences between techniques and the effects of temporal spacing between LiDAR datasets. Results show that both change detection methods provide consistent near field deformation comparable to field observed offsets. The deformation can vary in quality but estimated standard deviations are always below thirty one centimeters. This variation in quality differentiates the methods and proves that factors such as geodetic markers and temporal spacing play major roles in the outcomes of ALS change detection surveys.
Exposure to xenobiotic chemicals disrupts metabolism , rhythmicity and cell proliferation in Drosophila melanogaster

Cao, H. 2018. Exposure to xenobiotic chemicals disrupts metabolism, rhythmicity and cell proliferation in Drosophila melanogaster. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1481. 50 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0391-8. Most species are constantly exposed to xenobiotic chemicals through multiple routes. Among all categories of xenobiotics, phthalates and bisphenols are two of the most widely used plasticizers and can be found in polyvinyl chloride (PVC) materials, medical devices and even drinking water. In paper I, we found that bis-(2-ethylhexyl) phthalate (DEHP) exposure caused a significant decrease in circulating carbohydrates and insulin-related genes. The MultidrugResistance like Protein 1 (MRP1, MRP in Drosophila) belongs to the ATP-binding cassette transporter family, and previous studies revealed the importance of MRP1 for transporting xenobiotics. However, the function of MRP1 in metabolism and other biological processes is still unclear. Therefore, in paper II, we showed that knocking down MRP expression in Malpighian tubules, the physiological equivalence of the vertebrate kidney, led to disrupted lipid homeostasis and oxidative resistance. In paper III and IV, we initially used whole transcriptome sequencing to assess the genetic interferences of exposure to Dibutyl Phthalate (DBP) and Bisphenol A Diglycidyl Ether (BADGE). The reproductive and developmental disruptions of DBP had been reported in many studies. However, the mechanism is still unclear. In paper III, we observed that DBP interfered with neuronal systems associated circadian genes, including in vrille (vri, human NFIL3), timeless (tim, human TIMELESS), period (per, human PER3) and Pigment-dispersing factor (Pdf). Furthermore, we demonstrated that the evolutionarily conserved gene, Hormone receptor-like in 38 (Hr38, human NR4A2) was involved in responding to DBP and regulated Pdf expression as a consequence. In paper IV, BADGE, a BPA-substitute, was tested for its disruptive effects on Drosophila. Based on the transcriptome sequencing, we found that several mitotic genes, including string (stg, human CDC25A), Cyclin B (CycB, human CCNB1), Cyclin E (CycE, human CCNE1), and pan gu (png, human NEK11), had detectable overexpression by BADGE exposure. Developmental exposure to BADGE induced a large increase of hemocytes in fly 3 instar larvae, while it did not damage the morphological structure of lymph gland and blood circulation. To summarize, our studies describe the potential disruptions of the industrial xenobiotics and provide the mechanistic hints for future investigations.
Later Pension, Poorer Health? Evidence from the New State Pension Age in the UK

This paper examines the health impact of UK pension reforms that increased women’s State Pension age for up to six years since 2010. Exploiting an 11% increase in employment caused by the reforms, we show that rising the State Pension age reduces physical and mental health among women from routine-manual occupations. We show robust evidence that a larger increase in the State Pension age leads to larger negative health effects, resulting in a widening gap in health between women from different occupations. Our results are consistent with a 27% fall in individual incomes for women in routine-manual occupations.
Identification of Bicycle Demand from Online Routing Requests

Governments at all levels aim to increase cycling and walking within the mix of transportation modes. Accurate estimation of existing and potential bicycle trips on different parts of a road network is necessary to determine for which segments an investment in improved bicycling infrastructure is most effective. This paper introduces the novel idea to estimate bicycle demand on road segments based on logged trip requests that users submitted to a Web based bicycle trip planner. As a first step in this research direction, this paper assesses the general suitability of logged trip data for modeling cycling demand. More specifically, this study analyzes logged trip origins and destinations from user requests collected over a one-year period. The requests were submitted to an online bicycle trip planner developed for Broward County, Florida. The study then compares (a) point positions of logged trip origins with origins of bicycle commute trips obtained from census data, and (b) trip length distributions of logged trips with trip lengths obtained from observed bicycling trips in street networks. Several basic spatial and temporal filters are introduced and applied on the logged trip data to identify requests that most likely represent an actual trip and therefore provide a potential resource to predict bicycle demand.
Biometric Authentication and Penetration of Smartphones

This study aims to examine the function and vulnerabilities of biometric systems integrated in smartphones, as well as techniques for circumventing the security of these systems. These techniques are then used against a selection of smartphones in order to gauge the resilience of their biometric security. The function, vulnerabilities, and techniques associated with these systems are compiled using a literature study of published papers and books on the subject. The performed experiments apply these techniques in the form of presentation attacks directed at the fingerprint-, faceand iris recognition systems of the examined smartphones. The result of the experiments showed significant differences between the different smartphones, where some exhibited flawless security and others showed significant security flaws. Both fingerprint and face recognition systems were successfully circumvented, while none of the iris recognition systems were breached. No clear link could be observed between the cost of the device and success rate of attacks, while only devices using the Android operating system were breached. The results undeniably showed that some smartphones are vulnerable to the employed techniques. It also showed that some of the tested devices had managed to implement measures to counteract the applied presentation attacks. The root cause of the vulnerabilities showcased in the experiment is due to the fact that biometric traits can be copied and reproduced, highlighting a basic flaw of such systems.
Entanglement purification with the exchange interaction

Entanglement purification allows the creation of qubit pairs of arbitrarily high fidelity with respect to a maximally entangled state, starting from a larger number of low-fidelity pairs. Purification requires quantum memory, a role for which electron spins are well suited. However, using existing recurrence protocols involving symmetric local two-qubit operations for spin qubits turns out to be rather unpractical. We present an efficient purification protocol requiring only a single pulsed Heisenberg- or XY-type exchange interaction between two qubit pairs. In contrast to known protocols, we allow for asymmetric bilateral two-qubit operations where the two communication parties operate differently on their qubits. In the optimal version of our protocol, the local two-qubit interactions in the case of Heisenberg exchange correspond to the $\sqrt{\mathrm{SWAP}}$ gate and its inverse.