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This paper studies single-peaked domains where the designer is uncertain about the underlying alignment according to which the domain is single-peaked. The underlying alignment is common knowledge amongst agents, but preferences are private knowledge. Thus, the state of the world has both a public and private element, with the designer uninformed of both. I first posit a relevant solution concept called implementation in mixed information equilibria, which requires Nash implementation in the public information and dominant strategy implementation in the private information given the public information. I then identify necessary and sufficient conditions for social choice rules (SCRs) to be implementable. The characterization is used to identify unanimous and anonymous implementable SCRs for different forms of designer uncertainty, which basically boils down to picking the right SCRs from the large class identified by Moulin (Public Choice 35(4):437–455, 1980), and hence this result can be seen as identifying which of Moulin’s SCRs are robust to designer uncertainty.

In recent work, we provide computational arguments for expanding the class of proper cones recognized by conic optimization solvers, to permit simpler, smaller, more natural conic formulations. We define an exotic cone as a proper cone for which we can implement a small set of tractable (i.e. fast, numerically stable, analytic) oracles for a logarithmically homogeneous self-concordant barrier for the cone or for its dual cone. Our extensible, open-source conic interior point solver, Hypatia, allows modeling and solving any conic problem over a Cartesian product of exotic cones. In this paper, we introduce Hypatia’s interior point algorithm, which generalizes that of Skajaa and Ye (Math. Program. 150(2):391–422, 2015) by handling exotic cones without tractable primal oracles. To improve iteration count and solve time in practice, we propose four enhancements to the interior point stepping procedure of Skajaa and Ye: (1) loosening the central path proximity conditions, (2) adjusting the directions using a third order directional derivative barrier oracle, (3) performing a backtracking search on a curve, and (4) combining the prediction and centering directions. We implement 23 useful exotic cones in Hypatia. We summarize the complexity of computing oracles for these cones and show that our new third order oracle is not a bottleneck. From 37 applied examples, we generate a diverse benchmark set of 379 problems. Our computational testing shows that each stepping enhancement improves Hypatia’s iteration count and solve time. Altogether, the enhancements reduce the geometric means of iteration count and solve time by over 80% and 70% respectively.

The Domain Name System (DNS) does not provide query privacy. Query obfuscation schemes have been proposed to overcome this limitation, but, so far, they have not been evaluated in a realistic setting. In this paper we evaluate the security of a random set range query scheme in a real-world web surfing scenario. We demonstrate that the scheme does not sufficiently obfuscate characteristic query patterns, which can be used by an adversary to determine the visited websites. We also illustrate how to thwart the attack and discuss practical challenges. Our results suggest that previously published evaluations of range queries may give a false sense of the attainable security, because they do not account for any interdependencies between queries.

The Domain Name System (DNS) does not provide query privacy. Query obfuscation schemes have been proposed to overcome this limitation, but, so far, they have not been evaluated in a realistic setting. In this paper we evaluate the security of a random set range query scheme in a real-world web surfing scenario. We demonstrate that the scheme does not sufficiently obfuscate characteristic query patterns, which can be used by an adversary to determine the visited websites. We also illustrate how to thwart the attack and discuss practical challenges. Our results suggest that previously published evaluations of range queries may give a false sense of the attainable security, because they do not account for any interdependencies between queries.

In this paper, the theoretical convergence rate of the Sinc indefinite integration combined with the double-exponential (DE) transformation is given for a class of functions for which the single-exponential (SE) transformation is suitable. Although the DE transformation is considered as an enhanced version of the SE transformation for Sinc-related methods, the function space for which the DE transformation is suitable is smaller than that for SE, and therefore, there exist some examples such that the DE transformation is not better than the SE transformation. Even in such cases, however, some numerical observations in the literature suggest that there is almost no difference in the convergence rates of SE and DE. In fact, recently, the observations have been theoretically explained for two explicit approximation formulas: the Sinc quadrature and the Sinc approximation. The conclusion is that in such cases, the DE’s rate is slightly lower, but almost the same as that of the SE. The contribution of this study is the derivation of the same conclusion for the Sinc indefinite integration. Numerical examples that support the theoretical result are also provided.

The Domain Name System (DNS) does not provide query privacy. Query obfuscation schemes have been proposed to overcome this limitation, but, so far, they have not been evaluated in a realistic setting. In this paper we evaluate the security of a random set range query scheme in a real-world web surfing scenario. We demonstrate that the scheme does not sufficiently obfuscate characteristic query patterns, which can be used by an adversary to determine the visited websites. We also illustrate how to thwart the attack and discuss practical challenges. Our results suggest that previously published evaluations of range queries may give a false sense of the attainable security, because they do not account for any interdependencies between queries.

The Domain Name System (DNS) does not provide query privacy. Query obfuscation schemes have been proposed to overcome this limitation, but, so far, they have not been evaluated in a realistic setting. In this paper we evaluate the security of a random set range query scheme in a real-world web surfing scenario. We demonstrate that the scheme does not sufficiently obfuscate characteristic query patterns, which can be used by an adversary to determine the visited websites. We also illustrate how to thwart the attack and discuss practical challenges. Our results suggest that previously published evaluations of range queries may give a false sense of the attainable security, because they do not account for any interdependencies between queries.

This paper analyses the extended urbanization of oil production in Siberia in order to test Neil Brenner and Christian Schmid’s theory of planetary urbanization. According to these authors, the intensification of the urban process triggered by the consolidation of global neoliberalism since the early 1990s, has transformed the planet into a situation of total urbanization. In their view, this planetary condition can be measured by the incorporation of former remote wilderness such as the Amazon, the oceans, the deserts or Siberia within urban circuits of production (which they label under the notion of extended urbanization). In this article we test if Brenner and Schmid’s hypothesis applies to the Siberian case. With that goal, we develop a diachronic historic and cartographic analysis which shows first the incorporation of Siberia to the Russian Empire, second the consolidation of East Asia-Russia commercial circuits, and third the conceptualization of Siberia as primarily an area for resource extraction. Such analysis leads us to define three historic spatial regimes for the whole Siberia, the last of which we study in relation to the notion of planetary urbanization. Our study compares the geographies of oil production in the region first during the Soviet period, and then, following Brenner and Schmid’s chronology, after the 1990s. The article concludes that the latter phase certainly implies an unprecedented intensification of extended urbanization and the incorporation of Siberia into trans-scalar global circuits of production. Finally, in order to analyse the relation between this process and the consolidation of neoliberalism we develop a synchronic study and mapping of the operations of two oil companies: a public one, NOC ROSNEFT, and a private one, LUKOIL. We conclude that both are similarly invested in creating the trans-scalar geographies of uneven development that characterize neoliberalism.

This paper introduces a new Runge–Kutta (RK) integration-based adaptive controller by considering control law as an ODE for nonlinear MIMO systems. It is aimed to derive a novel adaptive controller by regarding the control law as an ODE with limited information about control law structure. Adaptive parameters are adjusted via an RK predictive system model where Levenberg–Marquardt (LM) technique is deployed. The adjustment mechanism enables to utilize RK both in adaptive controller and system model. The performance evaluation has been delved into on Van de Vusse (VdV) system for diverse situations, and reasonable results have been acquired for introduced adaptation mechanism.

The microscopic dynamics of particle collisions is imprinted into the statistical properties of asymptotic energy flux, much like the dynamics of inflation is imprinted into the cosmic microwave background. This energy flux is characterized by correlation functions E n → 1 ⋯ E n → k $$ \left\langle \mathcal{E}\left({\overrightarrow{n}}_1\right)\cdots \mathcal{E}\left({\overrightarrow{n}}_k\right)\right\rangle $$ of energy flow operators E n → $$ \mathcal{E}\left(\overrightarrow{n}\right) $$ . There has been significant recent progress in studying energy flux, including the calculation of multi-point correlation functions and their direct measurement inside high-energy jets at the Large Hadron Collider (LHC). In this paper, we build on these advances by defining a notion of “celestial non-gaussianity” as a ratio of the three-point function to a product of two-point functions. We show that this celestial non-gaussianity is under perturbative control within jets at the LHC, allowing us to cleanly access the non-gaussian interactions of quarks and gluons. We find good agreement between perturbative calculations of the non-gaussianity and a charged-particle-based analysis using CMS Open Data, and we observe a strong non-gaussianity peaked in the “flattened triangle” regime. The ability to robustly study three-point correlations is a significant step in advancing our understanding of jet substructure at the LHC. We anticipate that the celestial non-gaussianity, and its generalizations, will play an important role in the development of higher-order parton showers simulations and in the hunt for ever more subtle signals of potential new physics within jets.

Current and future experiments at the high-intensity frontier are expected to produce an enormous amount of data that needs to be collected and stored for offline analysis. Thanks to the continuous progress in computing and networking technology, it is now possible to replace the standard ‘triggered’ data acquisition systems with a new, simplified and outperforming scheme. ‘Streaming readout’ (SRO) DAQ aims to replace the hardware-based trigger with a much more powerful and flexible software-based one, that considers the whole detector information for efficient real-time data tagging and selection. Considering the crucial role of DAQ in an experiment, validation with on-field tests is required to demonstrate SRO performance. In this paper, we report results of the on-beam validation of the Jefferson Lab SRO framework. We exposed different detectors (PbWO-based electromagnetic calorimeters and a plastic scintillator hodoscope) to the Hall-D electron-positron secondary beam and to the Hall-B production electron beam, with increasingly complex experimental conditions. By comparing the data collected with the SRO system against the traditional DAQ, we demonstrate that the SRO performs as expected. Furthermore, we provide evidence of its superiority in implementing sophisticated AI-supported algorithms for real-time data analysis and reconstruction.

A search for long-lived particles decaying into muon pairs is performed using proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment at the LHC in 2017 and 2018, corresponding to an integrated luminosity of 101 fb−1. The data sets used in this search were collected with a dedicated dimuon trigger stream with low transverse momentum thresholds, recorded at high rate by retaining a reduced amount of information, in order to explore otherwise inaccessible phase space at low dimuon mass and nonzero displacement from the primary interaction vertex. No significant excess of events beyond the standard model expectation is found. Upper limits on branching fractions at 95% confidence level are set on a wide range of mass and lifetime hypotheses in beyond the standard model frameworks with the Higgs boson decaying into a pair of long-lived dark photons, or with a long-lived scalar resonance arising from a decay of a b hadron. The limits are the most stringent to date for substantial regions of the parameter space. These results can be also used to constrain models of displaced dimuons that are not explicitly considered in this paper.

Lake Chalco lies south of the Basin of Mexico and has been the subject of studies related to Late Quaternary climate variability. In 2016, the International Continental Scientific Drilling Program “MexiDrill Project” recovered a 520-m sediment record from Lake Chalco. Magnetic susceptibility measurements revealed substantial changes in sediment physical properties between 343 and 285 m depth, suggesting changes in composition associated with fluctuations in the depositional environment. We targeted sediments in the 343–285 m interval for high-resolution facies analysis, to develop a model of Lake Chalco formation. We identified three facies associations, using sediment composition, texture, mineralogy and micro-morphological characteristics: (1) detrital facies, consisting of laminated silt, massive sand, stratified silty sand, clast-supported gravel and matrix-supported gravel; (2) biogenic facies, which include diatom ooze and bivalve coquina; and (3) volcaniclastic facies, represented by clast-supported pumice deposits. We propose that formation of Lake Chalco occurred in four stages, which we identified by changes in sediment characteristics. The first stage was an alluvial delta environment, in which debris and hyper-concentrated flows were the main sediment transport agents. The second was characterized by turbulent flows in a fluvial deltaic environment, which alternated with laminar flows associated with floodplains. The third stage was a time of fluvio-lacustrine transition in the basin, with formation of the previously identified Paleo-Chalco-I Lake, in response to wet conditions. During the fourth stage, a deep eutrophic lake formed (Paleo-Chalco-II), with an origin that appears to have been related to regional volcanism. Our working age-depth model indicates establishment of the lake at ca. 400 ± 46 ka. This paper presents the only available record of the transition from alluvial to lacustrine sedimentation of Lake Chalco. Our results allow us t

Linear regression is a fundamental modeling tool in statistics and related fields. In this paper, we study an important variant of linear regression in which the predictor-response pairs are partially mismatched. We use an optimization formulation to simultaneously learn the underlying regression coefficients and the permutation corresponding to the mismatches. The combinatorial structure of the problem leads to computational challenges. We propose and study a simple greedy local search algorithm for this optimization problem that enjoys strong theoretical guarantees and appealing computational performance. We prove that under a suitable scaling of the number of mismatched pairs compared to the number of samples and features, and certain assumptions on problem data; our local search algorithm converges to a nearly-optimal solution at a linear rate. In particular, in the noiseless case, our algorithm converges to the global optimal solution with a linear convergence rate. Based on this result, we prove an upper bound for the estimation error of the parameter. We also propose an approximate local search step that allows us to scale our approach to much larger instances. We conduct numerical experiments to gather further insights into our theoretical results, and show promising performance gains compared to existing approaches.

Metrics of model goodness-of-fit, model comparison, and model parameter estimation are the main categories of statistical problems in science. Bayesian and frequentist methods that address these questions often rely on a likelihood function, which is the key ingredient in order to assess the plausibility of model parameters given observed data. In some complex systems or experimental setups, predicting the outcome of a model cannot be done analytically, and Monte Carlo techniques are used. In this paper, we present a new analytic likelihood that takes into account Monte Carlo uncertainties, appropriate for use in the large and small sample size limits. Our formulation performs better than semi-analytic methods, prevents strong claims on biased statements, and provides improved coverage properties compared to available methods.

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 $$\times $$ × 6 $$\times $$ × 6 m $$^3$$ 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.

Expansion planning models are tools frequently employed to analyze the transition to a carbon-neutral power system. Such models provide estimates for an optimal technology mix and optimal operating decisions, but they are also often used to obtain prices and subsequently calculate profits. This paper analyzes the impact of modeling assumptions on convexity for power system outcomes and, in particular, on investment cost recovery. Through a case study, we find that although there is a long-term equilibrium for producers under convex models, introducing realistic constraints, such as non-convexities/lumpiness of investments, inelastic demand or unit commitment constraints, leads to profitability challenges. We furthermore demonstrate that considering only short-term marginal costs in market-clearing may potentially create a significant missing-money problem caused by a missing-market problem and dual degeneracy in a 100 percent renewable system.

This paper generalizes classical spin geometry to the setting of weighted manifolds (manifolds with density) and provides applications to the Ricci flow. Spectral properties of the naturally associated weighted Dirac operator, introduced by Perelman, and its relationship with the weighted scalar curvature are investigated. Further, a generalization of the ADM mass for weighted asymptotically Euclidean (AE) manifolds is defined; on manifolds with nonnegative weighted scalar curvature, it satisfies a weighted Witten formula and thereby a positive weighted mass theorem. Finally, on such manifolds, Ricci flow is the gradient flow of said weighted ADM mass, for a natural choice of weight function. This yields a monotonicity formula for the weighted spinorial Dirichlet energy of a weighted Witten spinor along Ricci flow.

The 2nd International Workshop on Human Behavior Understanding (HBU'11) focuses on inducing behavioral change via computer systems that can analyse human behavior and communicate persuasive messages accordingly. While analysis techniques that involve pattern recognition, signal processing and machine learning are very relevant to this aim, the underlying psychological and sociological aspects of inducing behavioral change cannot be neglected. This paper provides a framework for assessing the impact of social factors for these applications, and discusses the role of social mediation of behaviors and attitudes. © 2012 Springer-Verlag.

Long-lived particles are predicted in extensions of the Standard Model that involve relatively light but very weakly interacting sectors. In this paper we consider the possibility that some of these particles are produced in atmospheric cosmic ray showers, and their decay intercepted by neutrino detectors such as IceCube or Super-Kamiokande. We present the methodology and evaluate the sensitivity of these searches in various scenarios, including extensions with heavy neutral leptons in models of massive neutrinos, models with an extra U(1) gauge symmetry, and a combination of both in a U(1)B−L model. Our results are shown as a function of the production rate and the lifetime of the corresponding long-lived particles.

Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper presents a novel technique for assessing and propagating LArTPC detector-related systematic uncertainties. The technique makes modifications to simulation waveforms based on a parameterization of observed differences in ionization signals from the TPC between data and simulation, while remaining insensitive to the details of the detector model. The modifications are then used to quantify the systematic differences in low- and high-level reconstructed quantities. This approach could be applied to future LArTPC detectors, such as those used in SBN and DUNE.

The Costas-array problem is a combinatorial constraint-satisfaction problem (CSP) that remains unsolved for many array sizes greater than 30. In order to reduce the time required to solve large instances, we present an Ant Colony Optimization algorithm called m-Dimensional Relative Ant Colony Optimization ( $$m$$ m DRACO) for combinatorial CSPs, focusing specifically on the Costas-array problem. This paper introduces the optimizations included in $$m$$ m DRACO, such as map-based association of pheromone with arbitrary-length component sequences and relative path storage. We assess the quality of the resulting $$m$$ m DRACO framework on the Costas-array problem by computing the efficiency of its processor utilization and comparing its run time to that of an ACO framework without the new optimizations. $$m$$ m DRACO gives promising results; it has efficiency greater than 0.5 and reduces time-to-first-solution for the $$m = 16$$ m = 16 Costas-array problem by a factor of over 300.

Data-driven decision-making has garnered growing interest as a result of the increasing availability of data in recent years. With that growth many opportunities and challenges have sprung up in the areas of predictive and prescriptive analytics. Often, optimization can play an important role in tackling these issues. In this paper, we review some recent advances that highlight the difference that optimization can make in data-driven decision-making. We discuss some of our contributions that aim to advance both predictive and prescriptive models. First, we describe how we can optimally estimate clustered models that result in improved predictions. Next, we consider how we can optimize over objective functions that arise from tree ensemble models in order to obtain better prescriptions. Finally, we discuss how we can learn optimal solutions directly from the data allowing for prescriptions without the need for predictions. For all these new methods, we stress the need for good performance but also the scalability to large heterogeneous datasets.

Discoveries of new phenomena often involve a dedicated search for a hypothetical physics signature. Recently, novel deep learning techniques have emerged for anomaly detection in the absence of a signal prior. However, by ignoring signal priors, the sensitivity of these approaches is significantly reduced. We present a new strategy dubbed Quasi Anomalous Knowledge (QUAK), whereby we introduce alternative signal priors that capture some of the salient features of new physics signatures, allowing for the recovery of sensitivity even when the alternative signal is incorrect. This approach can be applied to a broad range of physics models and neural network architectures. In this paper, we apply QUAK to anomaly detection of new physics events at the CERN Large Hadron Collider utilizing variational autoencoders with normalizing flow.

Multimarginal Optimal Transport (MOT) has attracted significant interest due to applications in machine learning, statistics, and the sciences. However, in most applications, the success of MOT is severely limited by a lack of efficient algorithms. Indeed, MOT in general requires exponential time in the number of marginals k and their support sizes n. This paper develops a general theory about what “structure” makes MOT solvable in $$\mathrm {poly}(n,k)$$ poly ( n , k ) time. We develop a unified algorithmic framework for solving MOT in $$\mathrm {poly}(n,k)$$ poly ( n , k ) time by characterizing the structure that different algorithms require in terms of simple variants of the dual feasibility oracle. This framework has several benefits. First, it enables us to show that the Sinkhorn algorithm, which is currently the most popular MOT algorithm, requires strictly more structure than other algorithms do to solve MOT in $$\mathrm {poly}(n,k)$$ poly ( n , k ) time. Second, our framework makes it much simpler to develop $$\mathrm {poly}(n,k)$$ poly ( n , k ) time algorithms for a given MOT problem. In particular, it is necessary and sufficient to (approximately) solve the dual feasibility oracle—which is much more amenable to standard algorithmic techniques. We illustrate this ease-of-use by developing $$\mathrm {poly}(n,k)$$ poly ( n , k ) -time algorithms for three general classes of MOT cost structures: (1) graphical structure; (2) set-optimization structure; and (3) low-rank plus sparse structure. For structure (1), we recover the known result that Sinkhorn has $$\mathrm {poly}(n,k)$$ poly ( n , k ) runtime; moreover, we provide the first $$\mathrm {poly}(n,k)$$ poly ( n , k ) time algorithms for computing solutions that are exact and sparse. For structures (2)-(3), we give the first $$\mathrm {poly}(n,k)$$ poly ( n , k ) time algorithms, even for approximate computation. Together, these three structures encompass many—if not most—current applications of M

Fragmentation is a common feature of rockfall that exerts a strong control on the trajectories of the generated blocks, the impact energies, and the runout. In this paper, we present a set of four real-scale rockfall tests aimed at studying the fragmentation of the rocky blocks, from the global design of the field procedure to the data analysis and the main results. A total of 124 limestone, dacite, or granite blocks ranging between 0.2 and 5 m3 were dropped from different heights (8.5 to 23.6 m) onto four slopes with different shapes (single or double bench) and slope angles (42º to 71º). The characteristics of the blocks, in particular the size, surface texture and joint condition, were measured before the drops. The trajectories of the blocks and both the initial and the impact velocities were tracked and recorded by means of three high-speed video cameras. A total of 200 block-to-ground impacts have been studied. On average, 40% of the blocks broke upon impact on the slope or on the ground, making it necessary to measure the fragments. The initial and final sizes of the blocks/fragments were measured by hand with tape, though photogrammetric techniques (UAV and terrestrial) were also used for comparison purposes. The information gathered during the field tests provides a deep insight into the fragmentation processes. On the one hand, the high-resolution slow-motion videos help to describe when and how the block breakage takes place and the spatial distribution of the pieces. On the other hand, it is possible to compute the block trajectories, the velocities, and the energy losses using videogrammetry. The results include, for instance, a block average fragmentation of 54% and 14% for the limestone and granitoids, respectively; the systematic inventory of the size fragments, which may be used for fitting the power law distributions; and after each breakage, the total angle of aperture occupied by the fragments has been measured, with values in the range

Cryptocurrencies have the potential to become a disruptive innovation because they define a new paradigm: the decentralization of trust in secure electronic transactions without the need for a central control authority. Cryptocurrencies arouse interest in society because they reformulate the generation and transference of money. The aim of this paper is to investigate the role of the disruptive innovation of cryptocurrencies in the acceptance and trust perceived by users with regard to the monetary transactions generated in e-commerce. This paper defines a model using constructs from the technology acceptance model, trust and perceived risk. This model is evaluated using partial least squares analysis. The findings affirm that perceived trust, perceived risk, and perceived ease of use are not strong predictors of the intention to use cryptocurrencies and that the strength of their effects on the intention to use is determined by the perceived usefulness of adopting the mentioned disruptive innovation. This preliminary study makes a significant contribution to consumer behaviour research by analysing a cryptocurrency acceptance model for C2C e-commerce. The theoretical and practical contributions are detailed in the final section of the paper.

Geomechanics classifications are used to perform a preliminary assessment of rock slope stability for different purposes in civil and mining engineering. Among all existing rock mass classifications, slope mass rating (SMR) is one of the most commonly used for slopes. Although SMR is a geomechanics classification applied worldwide, often some misapprehensions and inaccuracies are made when professionally and scientifically used. Nearly all these miscalculations involve the influence of slope geometry and the dip and direction of the discontinuities. These problems can be overcome by a systematic assessment of SMR, which allows users to understand and visualize the relative orientation between discontinuities and slope. To fulfil this purpose, a complete and detailed definition of the angular relationships between discontinuities and slope are included in this paper, clarifying the assessment of the SMR parameters. Additionally, a Matlab-based open-source software for SMR (SMRTool) calculation is presented, avoiding miscalculations by automating the calculations and showing the graphical representation of slope and discontinuities. Finally, a general explanation of the method for the use of SMR is reviewed, stressing the common source of errors when applying this classification. The performance, benefits and usefulness of SMRTool are also illustrated in this paper through a specific case study.

Electric Field Assisted Capillarity is a novel one-step process suitable for the fabrication of hollow polymer microstructures. The process, demonstrated to work experimentally on a microscale using Polydimethylsiloxane (PDMS), makes use of both the electrohydrodynamics of polymers subject to an applied voltage and the capillary force on the polymers caused by a low contact angle on a heavily wetted surface. Results of two-dimensional numerical simulations of the process are discussed in this paper for the special case of production of microfluidic channels. The paper investigates the effects of altering key parameters including the contact angle with the top mask, the polymer thickness and air gap, the permittivity of the polymer, the applied voltage and geometrical variations on the final morphology of the microstructure. The results from these simulations demonstrate that the capillary force caused by the contact angle has the greatest effect on the final shape of the polymer microstructures.

Cryptocurrencies have the potential to become a disruptive innovation because they define a new paradigm: the decentralization of trust in secure electronic transactions without the need for a central control authority. Cryptocurrencies arouse interest in society because they reformulate the generation and transference of money. The aim of this paper is to investigate the role of the disruptive innovation of cryptocurrencies in the acceptance and trust perceived by users with regard to the monetary transactions generated in e-commerce. This paper defines a model using constructs from the technology acceptance model, trust and perceived risk. This model is evaluated using partial least squares analysis. The findings affirm that perceived trust, perceived risk, and perceived ease of use are not strong predictors of the intention to use cryptocurrencies and that the strength of their effects on the intention to use is determined by the perceived usefulness of adopting the mentioned disruptive innovation. This preliminary study makes a significant contribution to consumer behaviour research by analysing a cryptocurrency acceptance model for C2C e-commerce. The theoretical and practical contributions are detailed in the final section of the paper.

Geomechanics classifications are used to perform a preliminary assessment of rock slope stability for different purposes in civil and mining engineering. Among all existing rock mass classifications, slope mass rating (SMR) is one of the most commonly used for slopes. Although SMR is a geomechanics classification applied worldwide, often some misapprehensions and inaccuracies are made when professionally and scientifically used. Nearly all these miscalculations involve the influence of slope geometry and the dip and direction of the discontinuities. These problems can be overcome by a systematic assessment of SMR, which allows users to understand and visualize the relative orientation between discontinuities and slope. To fulfil this purpose, a complete and detailed definition of the angular relationships between discontinuities and slope are included in this paper, clarifying the assessment of the SMR parameters. Additionally, a Matlab-based open-source software for SMR (SMRTool) calculation is presented, avoiding miscalculations by automating the calculations and showing the graphical representation of slope and discontinuities. Finally, a general explanation of the method for the use of SMR is reviewed, stressing the common source of errors when applying this classification. The performance, benefits and usefulness of SMRTool are also illustrated in this paper through a specific case study.

VerifyThis is a series of program verification competitions that emphasize the human aspect: participants tackle the verification of detailed behavioral properties—something that lies beyond the capabilities of fully automatic verification and requires instead human expertise to suitably encode programs, specifications, and invariants. This paper describes the 8th edition of VerifyThis, which took place at ETAPS 2019 in Prague. Thirteen teams entered the competition, which consisted of three verification challenges and spanned 2 days of work. This report analyzes how the participating teams fared on these challenges, reflects on what makes a verification challenge more or less suitable for the typical VerifyThis participants, and outlines the difficulties of comparing the work of teams using wildly different verification approaches in a competition focused on the human aspect.

Checking the consistency of a metamodel involves finding a valid metamodel instance that provably meets the set of constraints that are defined over the metamodel. These constraints are often specified in Object Constraint Language. Often, a metamodel is inconsistent due to conflicts among the constraints. Existing approaches and tools are typically incapable of pinpointing the conflicting constraints, and this makes it difficult for users to debug and fix their metamodels. In this paper, we present a formal approach for locating conflicting constraints in inconsistent metamodels. Our approach has four distinct features: (1) users can rank individual metamodel features using their own domain-specific knowledge, (2) we transform these ranked features to a weighted maximum satisfiability modulo theories problem and solve it to compute the set of maximum achievable features, (3) we pinpoint the conflicting constraints by solving the set cover problem using a novel algorithm, and (4) we have implemented our approach into a fully automated tool called MaxUSE. Our evaluation results, using our assembled set of benchmarks, demonstrate the scalability of our work and that it is capable of efficiently finding conflicting constraints.

VerifyThis is a series of program verification competitions that emphasize the human aspect: participants tackle the verification of detailed behavioral properties—something that lies beyond the capabilities of fully automatic verification and requires instead human expertise to suitably encode programs, specifications, and invariants. This paper describes the 8th edition of VerifyThis, which took place at ETAPS 2019 in Prague. Thirteen teams entered the competition, which consisted of three verification challenges and spanned 2 days of work. This report analyzes how the participating teams fared on these challenges, reflects on what makes a verification challenge more or less suitable for the typical VerifyThis participants, and outlines the difficulties of comparing the work of teams using wildly different verification approaches in a competition focused on the human aspect.

Checking the consistency of a metamodel involves finding a valid metamodel instance that provably meets the set of constraints that are defined over the metamodel. These constraints are often specified in Object Constraint Language. Often, a metamodel is inconsistent due to conflicts among the constraints. Existing approaches and tools are typically incapable of pinpointing the conflicting constraints, and this makes it difficult for users to debug and fix their metamodels. In this paper, we present a formal approach for locating conflicting constraints in inconsistent metamodels. Our approach has four distinct features: (1) users can rank individual metamodel features using their own domain-specific knowledge, (2) we transform these ranked features to a weighted maximum satisfiability modulo theories problem and solve it to compute the set of maximum achievable features, (3) we pinpoint the conflicting constraints by solving the set cover problem using a novel algorithm, and (4) we have implemented our approach into a fully automated tool called MaxUSE. Our evaluation results, using our assembled set of benchmarks, demonstrate the scalability of our work and that it is capable of efficiently finding conflicting constraints.

Given the importance of entry promotion to prompt economic growth and promote structural transformation, this paper investigates the regional determinants of firm entry in the 30 Iranian regions, considering four different sizes-micro, small, medium, and large-over 2000-2015. Using a new and unique database, we estimate different spatial econometric models, which take into account three types of spatial interaction effects. We find that firm entry is related to some regional characteristics, but the relationship is not homogeneous across firms of different size. We also find that most types of firms are influenced by the negative effect of economic sanctions during the sample period., Fil: Cheratian, Iman. Academic Center for Education, Culture, and Research (ACECR); Iran., Fil: Goltabar, Saleh. Academic Center for Education, Culture, and Research (ACECR); Iran., Fil: Calá, Carla Daniela. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina.

Recently, we showed how mechanical power (MP) was associated with patient–centered outcomes in two large prospective cohorts of critically ill patients under invasive ventilation [1]. Normalization of MP, e.g., to the predicted body weight (PBW), has been put forward [2]. One recent paper showed MP normalized to PBW to be a better predictor of mortality than the absolute MP, at least in ARDS patients [3]. We here report the results of a posthoc analysis of the datasets used in our abovementioned publication [1]. We tested the hypothesis that MP normalized to three common anthropometric indexes, i.e., PBW, body mass index (BMI), and body surface area (BSA) are better predictors of in–hospital mortality than absolute MP in critically ill patients under invasive ventilation.

Quantum states with geometric duals are known to satisfy a stricter set of entropy inequalities than those obeyed by general quantum systems. The set of allowed entropies derived using the Ryu-Takayanagi (RT) formula defines the Holographic Entropy Cone (HEC). These inequalities are no longer satisfied once general quantum corrections are included by employing the Quantum Extremal Surface (QES) prescription. Nevertheless, the structure of the QES formula allows for a controlled study of how quantum contributions from bulk entropies interplay with HEC inequalities. In this paper, we initiate an exploration of this problem by relating bulk entropy constraints to boundary entropy inequalities. In particular, we show that requiring the bulk entropies to satisfy the HEC implies that the boundary entropies also satisfy the HEC. Further, we also show that requiring the bulk entropies to obey monogamy of mutual information (MMI) implies the boundary entropies also obey MMI., US Department of Energy (Grants DE-SC0018944 and DE-SC0019127)

In this paper, we present an efficiency improvement for the algorithm called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, devised by Aldstadt and Getis (Geogr Anal 38(4):327-343, 2006). AMOEBA embeds a local spatial autocorrelation statistic in an iterative procedure in order to identify spatial clusters (ecotopes) of related spatial units. We provide an analysis of the computational complexity of the original AMOEBA and develop an alternative formulation that reduces computational time without losing optimality. Empirical evidence is provided using georeferenced socio-demographic data in Accra, Ghana. © 2010 Springer-Verlag.

We prove the linear stability of slowly rotating Kerr black holes as solutions of the Einstein vacuum equations: linearized perturbations of a Kerr metric decay at an inverse polynomial rate to a linearized Kerr metric plus a pure gauge term. We work in a natural wave map/DeTurck gauge and show that the pure gauge term can be taken to lie in a fixed 7-dimensional space with a simple geometric interpretation. Our proof rests on a robust general framework, based on recent advances in microlocal analysis and non-elliptic Fredholm theory, for the analysis of resolvents of operators on asymptotically flat spaces. With the mode stability of the Schwarzschild metric as well as of certain scalar and 1-form wave operators on the Schwarzschild spacetime as an input, we establish the linear stability of slowly rotating Kerr black holes using perturbative arguments; in particular, our proof does not make any use of special algebraic properties of the Kerr metric. The heart of the paper is a detailed description of the resolvent of the linearization of a suitable hyperbolic gauge-fixed Einstein operator at low energies. As in previous work by the second and third authors on the nonlinear stability of cosmological black holes, constraint damping plays an important role. Here, it eliminates certain pathological generalized zero energy states; it also ensures that solutions of our hyperbolic formulation of the linearized Einstein equations have the stated asymptotics and decay for general initial data and forcing terms, which is a useful feature in nonlinear and numerical applications., National Science Foundation (U.S.) (Grant DMS-1955614)

In hidden sector models, dark matter does not directly couple to the particle content of the Standard Model, strongly suppressing rates at direct detection experiments, while still allowing for large signals from annihilation. In this paper, we conduct an extensive study of hidden sector dark matter, covering a wide range of dark matter spins, mediator spins, interaction diagrams, and annihilation final states, in each case determining whether the annihilations are s-wave (thus enabling efficient annihilation in the universe today). We then go on to consider a variety of portal interactions that allow the hidden sector annihilation products to decay into the Standard Model. We broadly classify constraints from relic density requirements and dwarf spheroidal galaxy observations. In the scenario that the hidden sector was in equilibrium with the Standard Model in the early universe, we place a lower bound on the portal coupling, as well as on the dark matter’s elastic scattering cross section with nuclei. We apply our hidden sector results to the observed Galactic Center gamma-ray excess and the cosmic-ray antiproton excess. We find that both of these excesses can be simultaneously explained by a variety of hidden sector models, without any tension with constraints from observations of dwarf spheroidal galaxies., Department of Energy. Office of High Energy Physics (Contract DE-AC02-07CH11359; Grants E-SC00012567 and DE-SC0013999)

The project “Semantic Technologies for Situation Awareness” was concerned with detecting certain critical situations from data obtained by observing a complex hard- and software system, in order to trigger actions that allow this system to save energy. The general idea was to formalize situations as ontology-mediated queries, but in order to express the relevant situations, both the employed ontology language and the query language had to be extended. In this paper we sketch the general approach and then concentrate on reporting the formal results obtained for reasoning in these extensions, but do not describe the application that triggered these extensions in detail.

Given the importance of entry promotion to prompt economic growth and promote structural transformation, this paper investigates the regional determinants of firm entry in the 30 Iranian regions, considering four different sizes-micro, small, medium, and large-over 2000-2015. Using a new and unique database, we estimate different spatial econometric models, which take into account three types of spatial interaction effects. We find that firm entry is related to some regional characteristics, but the relationship is not homogeneous across firms of different size. We also find that most types of firms are influenced by the negative effect of economic sanctions during the sample period., Fil: Cheratian, Iman. Academic Center for Education, Culture, and Research (ACECR); Iran., Fil: Goltabar, Saleh. Academic Center for Education, Culture, and Research (ACECR); Iran., Fil: Calá, Carla Daniela. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina.

This paper develops a network model of interbank lending, in which banks decide to extend credit to their potential borrowers. Borrowers are subject to shocks that may force them to default on their loans. In contrast to much of the previous literature on financial networks, we focus on how anticipation of future defaults may result in ex ante “credit freezes,” whereby banks refuse to extend credit to one another. We first characterize the terms of the interbank contracts and the patterns of interbank lending that emerge in equilibrium. We then study how shifts in the distribution of shocks can result in complex credit freezes that travel throughout the network. We use this framework to analyze the effects of various policy interventions on systemic credit freezes.

This paper reports on a search for an extension to the scalar sector of the standard model, where a new CP-even (odd) boson decays to a Z boson and a lighter CP-odd (even) boson, and the latter further decays to a b quark pair. The Z boson is reconstructed via its decays to electron or muon pairs. The analysed data were recorded in proton-proton collisions at a center-of-mass energy s$$ \sqrt{s} $$ = 13 TeV, collected by the CMS experiment at the LHC during 2016, corresponding to an integrated luminosity of 35.9 fb−1. Data and predictions from the standard model are in agreement within the uncertainties. Upper limits at 95% confidence level are set on the production cross section times branching fraction, with masses of the new bosons up to 1000 GeV. The results are interpreted in the context of the two-Higgs-doublet model.

If the evaporation of a black hole formed from a pure state is unitary, the entanglement entropy of the Hawking radiation should follow the Page curve, increasing from zero until near the halfway point of the evaporation, and then decreasing back to zero. The general argument for the Page curve is based on the assumption that the quantum state of the black hole plus radiation during the evaporation process is typical. In this paper, we show that the Page curve can result from a simple dynamical input in the evolution of the black hole, based on a recently proposed signature of quantum chaos, without resorting to typicality. Our argument is based on what we refer to as the “operator gas” approach, which allows one to understand the evolution of the microstate of the black hole from generic features of the Heisenberg evolution of operators. One key feature which leads to the Page curve is the possibility of dynamical processes where operators in the “gas” can “jump” outside the black hole, which we refer to as void formation processes. Such processes are initially exponentially suppressed, but dominate after a certain time scale, which can be used as a dynamical definition of the Page time. In the Hayden-Preskill protocol for young and old black holes, we show that void formation is also responsible for the transfer of information from the black hole to the radiation. We conjecture that void formation may provide a microscopic explanation for the recent semi-classical prescription of including islands in the calculation of the entanglement entropy of the radiation.

This work, using three-dimension proton exchange membrane fuel cell (PEMFC) model combined with theoretical analysis, is mainly to improve the performance of PEMFC through optimizations of fuel cell structure, adding rectangle blockages in the gas channel. Performance comparison, velocity distribution, interface reactant concentration difference, and pressure drop have been studied in the paper. The result shows that, longitudinal vortices would appear and the performance could be improved with the addition of blockages in the gas channel, especially at high current density with closer arrangement. According to field synergy principle, average mass transfer synergy angle could prove the superiority of optimized structure in the ability of mass transfer. Besides, a novel physical quantity, effective mass transfer coefficient, has been proposed. The effective mass transfer coefficient, is the ability of mass transfer in the direction of electrochemical reaction in PEMFC, which could also give mechanism explanation for the performance improvement.

For many years, Herlihy’s elegant computability-based Consensus Hierarchy has been our best explanation of the relative power of various objects. Since real multiprocessors allow the different instructions they support to be applied to any memory location, it makes sense to consider combining the instructions supported by different objects, rather than considering collections of different objects. Surprisingly, this causes Herlihy’s computability-based hierarchy to collapse. In this paper, we suggest an alternative: a complexity-based classification of the relative power of sets of multiprocessor synchronization instructions, captured by the minimum number of memory locations of unbounded size that are needed to solve obstruction-free consensus when using different sets of instructions.

For each partition $$\underline{p}$$ p ̲ of an integer $$N\ge 2$$ N ≥ 2 , consisting of r parts, an integrable hierarchy of Lax type Hamiltonian PDE has been constructed recently by some of us. In the present paper we show that any tau-function of the $$\underline{p}$$ p ̲ -reduced r-component KP hierarchy produces a solution of this integrable hierarchy. Along the way we provide an algorithm for the explicit construction of the generators of the corresponding classical $$\mathcal {W}$$ W -algebra $$\mathcal {W}(\mathfrak {gl}_N,\underline{p})$$ W ( gl N , p ̲ ) , and write down explicit formulas for evolution of these generators along the commuting Hamiltonian flows.

In the high energy limit of hadron collisions, the evolution of the gluon density in the longitudinal momentum fraction can be deduced from the Balitsky hierarchy of equations or, equivalently, from the nonlinear Jalilian–Marian–Iancu–McLerran–Weigert–Leonidov–Kovner (JIMWLK) equation. The solutions of the latter can be studied numerically by using its reformulation in terms of a Langevin equation. In this paper, we present a comprehensive study of systematic effects associated with the numerical framework, in particular the ones related to the inclusion of the running coupling. We consider three proposed ways in which the running of the coupling constant can be included: “square root” and “noise” prescriptions and the recent proposal by Hatta and Iancu. We implement them both in position and momentum spaces and we investigate and quantify the differences in the resulting evolved gluon distributions. We find that the systematic differences associated with the implementation technicalities can be of a similar magnitude as differences in running coupling prescriptions in some cases, or much smaller in other cases.