Miracle-dz/UniFAR-FTUs huggingface dataset:
Stringent Emission Control Policies Can Provide Large Improvements in Air Quality and Public Health in India

Exposure to high concentrations of ambient fine particulate matter (PM2.5) is a leading risk factor for public health in India causing a large burden of disease. Business‐as‐usual economic and industrial growth in India is predicted to increase emissions, worsen air quality, and increase the associated disease burden in future decades. Here we use a high‐resolution online‐coupled model to estimate the impacts of different air pollution control pathways on ambient PM2.5 concentrations and human health in India. We find that with no change in emissions, the disease burden from exposure to ambient PM2.5 in 2050 will increase by 75% relative to 2015, due to population aging and growth increasing the number of people susceptible to air pollution. We estimate that the International Energy Agencies New Policy Scenario (NPS) and Clean Air Scenario (CAS) in 2050 can reduce ambient PM2.5 concentrations below 2015 levels by 9% and 68%, respectively, offsetting 61,000 and 610,000 premature mortalities a year, which is 9% and 91% of the projected increase in premature mortalities due to population growth and aging. Throughout India, the CAS stands out as the most effective scenario to reduce ambient PM2.5 concentrations and the associated disease burden, reducing the 2050 mortality rate per 100,000 below 2015 control levels by 15%. However, even under such stringent emission control policies, population growth and aging results in premature mortality estimates from exposure to particulate air pollution to increase by 7% compared to 2015, highlighting the challenge facing efforts to improve public health in India.
Towards Automated Log Parsing for Large-Scale Log Data Analysis

Logs are widely used in system management for dependability assurance because they are often the only data available that record detailed system runtime behaviors in production. Because the size of logs is constantly increasing, developers (and operators) intend to automate their analysis by applying data mining methods, therefore structured input data (e.g., matrices) are required. This triggers a number of studies on log parsing that aims to transform free-text log messages into structured events. However, due to the lack of open-source implementations of these log parsers and benchmarks for performance comparison, developers are unlikely to be aware of the effectiveness of existing log parsers and their limitations when applying them into practice. They must often reimplement or redesign one, which is time-consuming and redundant. In this paper, we first present a characterization study of the current state of the art log parsers and evaluate their efficacy on five real-world datasets with over ten million log messages. We determine that, although the overall accuracy of these parsers is high, they are not robust across all datasets. When logs grow to a large scale (e.g., 200 million log messages), which is common in practice, these parsers are not efficient enough to handle such data on a single computer. To address the above limitations, we design and implement a parallel log parser (namely POP) on top of Spark, a large-scale data processing platform. Comprehensive experiments have been conducted to evaluate POP on both synthetic and real-world datasets. The evaluation results demonstrate the capability of POP in terms of accuracy, efficiency, and effectiveness on subsequent log mining tasks.
Acyclic Mechanism Design for Freight Consolidation

Freight consolidation is a logistics practice that improves the cost-effectiveness and efficiency of transportation operations, and also reduces energy consumption and carbon footprint. A “fair” shipping cost-sharing scheme is indispensable to help establish and sustain the cooperation of a group of suppliers in freight consolidation. In this paper, we design a truthful acyclic mechanism to solve the cost-sharing problem in a freight consolidation system with one consolidation center and one common destination. Applying the acyclic mechanism, the consolidation center decides which suppliers’ demands ship via the consolidation center and their corresponding cost shares based on their willingness to pay for the service. The proposed acyclic mechanism is designed based on bin packing solutions that are also strong Nash equilibria for a related noncooperative game. We study the budget-balance of the mechanism both theoretically and numerically. We prove a 2-budget-balance guarantee for the mechanism in general and better budget-balance guarantees under specific problem settings. Empirical tests on budget-balance show that our mechanism performs much better than the guaranteed budget-balance ratio. We also study the economic efficiency of our mechanism numerically to investigate its impact on social welfare under different conditions.
Bayesian Quantum Circuit

Parameterized quantum circuits (PQCs), as one of the most promising schemes to realize quantum machine learning algorithms on near-term quantum computers, have been designed to solve machine earning tasks with quantum advantages. In this paper, we explain why PQCs with different structures can achieve generative tasks in the discrete case from the perspective of probability estimation. Although different kinds of PQCs are proposed for generative tasks, the current methods often encounter the following three hurdles: (1) the mode contraction problem; (2) unexpected data are often generated with a high proportion; (3) target data cannot be sampled directly. For the purpose of tackling the above hurdles, we devise Bayesian quantum circuit (BQC) through introducing ancillary qubits to represent prior distributions. BQC advances both generative and semi-supervised quantum circuit learning tasks, where its effectiveness is validated by numerical simulations using the Rigetti Forest platform.
M ay 2 01 8 Quantum error correction decoheres noise

Stefanie Beale,1, ∗ Joel Wallman,2, † Mauricio Gutiérrez,3, 4 Kenneth R. Brown,5 and Raymond Laflamme1, 6 Institute for Quantum Computing and Department of Physics and Astronomy, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada Institute for Quantum Computing and Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada Department of Physics, College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, United Kingdom Escuela de Qúımica, Universidad de Costa Rica, San José, 2060 Costa Rica Department of Electrical and Computer Engineering, Chemistry, and Physics, Duke University, Durham, NC 27708 Perimeter Institute for Theoretical Physics, Waterloo N2L 2Y5 ON, Canada
Zebrafish as screening model for detecting toxicity and drugs efficacy

Embryonic and larval Danio rerio (zebrafish) is increasingly used as a toxicological model to conduct rapid in vivo tests and developmental toxicity assays; the zebrafish features high genetic homology to mammals, robust, phenotypes, highthroughput genetic and chemical screening have made it a powerful tool to evaluate in vivo toxicity. New methodologies of genome editing as CRISPR/Cas9; ZFN and TALEN make it a suitable model to perform studies to pair human genetic diseases as well. This review surveys recent studies employing zebrafish as experimental model, comparing it with other in vivo and in vitro models, presenting zebrafish as a potent vertebrate tool to evaluate drug toxicity and efficacy in order to facilitate more extensive, easy and comprehensive knowledge of new generation drugs.
Covariance matrix entanglement criterion for an arbitrary set of operators

A criterion for entanglement detection based on covariance matrices for an arbitrary set of observables is formulated. The method generalizes the covariance matrix entanglement criterion by Simon (2000 Phys. Rev. Lett. 84 2726) to a more general set of operators using the positive partial transpose test for the covariance matrix. The relation is found by starting from the generalized uncertainty relation for multiple operators, and taking the partial transpose on the bipartition. The method is highly efficient and versatile in the sense that the set of measurement operators can be freely chosen, and there is no constraint on the commutation relations. The main restriction on the chosen set of measurement operators is that the correlators and expectation values of the partially transposed observable operators can be evaluated. The method is particularly suited for systems with higher dimensionality since the computations do not scale with the dimension of the Hilbert space—rather they scale with the number of chosen observables. We illustrate the approach by examining the entanglement between two spin ensembles, and show that it detects entanglement in a basis independent way.
Quantum Markov processes on graphs, monitoring and hitting times

We make use of matrix representations of completely positive maps in order to study open quantum dynamics on graphs, with emphasis on quantum walks and the associated trajectories obtained via a monitoring of the position. We discuss the discrete and continuous time setting and consider the statistics of particles located on a vertex with some internal degree of freedom. Other classes of semigroup generators, such as graph-induced generators are also considered. In the case of primitive quantum channels we present expressions of the mean hitting time for a particle to reach a vertex in terms of a quantum version of the fundamental matrix, thus extending recent results in the setting of open quantum random walks. An open quantum version of Kac's Lemma for the expected return time is discussed. By considering appropriate block matrix expressions we are able to make computations in terms of matrix-valued transition rates, in analogy with the notion of rates from classical continuous-time Markov chains. Also inspired by the classical case a recurrence criterion for the continuous time open walk setting is presented.
A Relational Approach to Quantum Mechanics, Part II: Measurement

The work presented here is a continuation of the relational formulation of quantum mechanics. Relational formulation of quantum mechanics is based on the idea that relational properties among quantum systems, instead of the independent properties of a quantum system, are the most fundamental elements to construct quantum mechanics. In the earlier works, basic framework is formulated to derive quantum probability, Born’s Rule, and Schrödinger Equations. This paper further develops the formulations for ideal quantum measurement and general quantum operation. The formulation is compatible with the traditional quantum mechanics mathematically but gives new insights on several important concepts. First, the formulation shows how mutual information is exchanged during measurement. Second, it asserts that Schrödinger Equations alone cannot explain the measurement process. The “collapse” of wave function is simply an update of relational matrix based on measurement outcome. Third, the relational nature of a quantum state is discussed in depth that leads to a resolution of the EPR paradox. Completeness of quantum mechanics and locality can coexist by recognizing that a quantum state is observer-dependent. Lastly, objectivity of a quantum state can be preserved via synchronization of information among observers.
On small beams with large topological charge: II. Photons, electrons and gravitational waves

Beams of light with a large topological charge significantly change their spatial structure when they are focused strongly. Physically, it can be explained by an emerging electromagnetic field component in the direction of propagation, which is neglected in the simplified scalar wave picture in optics. Here we ask: is this a specific photonic behavior, or can similar phenomena also be predicted for other species of particles? We show that the same modification of the spatial structure exists for relativistic electrons as well as for focused gravitational waves. However, this is for different physical reasons: for electrons, which are described by the Dirac equation, the spatial structure changes due to a spin–orbit coupling in the relativistic regime. In gravitational waves described with linearized general relativity, the curvature of space–time between the transverse and propagation direction leads to the modification of the spatial structure. Thus, this universal phenomenon exists for both massive and massless elementary particles with spin 1/2, 1 and 2. It would be very interesting whether other types of particles such as composite systems (neutrons or C60) or neutrinos show a similar behavior and how this phenomenon can be explained in a unified physical way.
Diversity Climate and Job Crafting: The Role of Age.

In recent years, scientific interest in generational differences has increased. More attention has been paid to the younger (Y generation) and to older workers (baby boom generation), little attention has been given to the X generation, composed of people who are between 35 and 50 years old. This paper aimed to examine the role of age in the relationship between diversity climate and job crafting, focusing on the middle aged (X generation). Based on lifespan development, self-regulation and job demands-resources theory, we postulated that the association between diversity climate and job crafting weakens with age. Specifically, we hypothesized that age can moderate the positive relationship between diversity climate and job crafting. The participants were 271 employees from different Italian organizations.The results from hierarchical regression analysis showed that the relationship between diversity climate and job crafting is stronger in middle aged workers rather than in older workers.The findings suggest that diversity climate, in terms of organizational fairness, inclusion and personal diversity value can play a crucial role in the influence of job crafting which is, in turn, essential to improve positive organizational outcomes. Limitations and theoretical and operative implications are discussed.
Modelling and Development of Electrical Aptasensors: A Short Review

Aptamers are strands of DNA or RNA molecules, chemically synthetized and able to bind a wide range of targets, from small molecules to live cells, and even tissues, with high affinity and specificity. Due to their efficient targeting ability, they have many different kinds of applications. Particularly attractive is their use in biotechnology and disease therapy, in substitution of antibodies. They represent a promising way for early diagnosis (aptasensors), but also for delivering imaging agents and drugs and for inhibiting specific proteins (therapeutic aptamers). Starting by briefly reviewing the most recent literature concerning advances in biomedical applications of aptamers and aptasensors, the focus is on the issues of a theoretical/computational framework (proteotronics) for modelling the electrical properties of biomolecules. Some recent results of proteotronics concerning the electrical, topological and affinity properties of aptamers are reviewed.
Mapping Ecosystem Service Bundles to Detect Distinct Types of Multifunctionality within the Diverse Landscape of the Yangtze River Basin, China

The tradeoffs and synergies of ecosystem services are widely discussed and recognized. However, explicit information for understanding and managing the complex relationships of multiple ecosystem services at regional scales is still lacking, which often leads to the degradation of important ecosystem services due to one ecosystem service being enhanced over another. We assessed the biodiversity and the production of nine ESs (ecosystem services) across 779 counties in the Yangtze River Basin, the largest basin in China. Then, we mapped the distribution of ES for each county and used correlations and “partitioning around medoids” clustering analysis to assess the existence of ES bundles. We found five distinct types of bundles of ecosystem services spatially agglomerated in the landscape, which could be mainly explained by land use, slope and altitude gradients. Our results also show landscape-scale tradeoffs between provisioning and almost all regulating services (and biodiversity), and synergies among almost all regulating services (and biodiversity). Mapping ecosystem service bundles can identify areas in a landscape where ecosystem management has produced exceptionally desirable or undesirable sets of ecosystem services, and can also provide explicit, tailored information on landscape planning for ecosystem service conservation and the design of payment policies for ecosystem services within diverse landscapes at watershed scales.
Agrichemicals boost the effects of antibiotics on antibiotic resistance evolution

Antibiotic resistance is medicine’s climate change: caused by human activity, and resulting in more extreme outcomes. Resistance emerges in microbial populations when antibiotics act on phenotypic variance within the population. This can arise from either genotypic diversity (resulting from a mutation or horizontal gene transfer), or from ‘adaptive’ differences in gene expression due to environmental variation. Adaptive changes can increase fitness allowing bacteria to survive at higher concentrations of the antibiotic. They can also decrease fitness, potentially leading to selection for antibiotic resistance at lower concentrations. There are opportunities for other environmental stressors to promote antibiotic resistance in ways that are hard to predict using conventional assays. Exploiting our observation that commonly used herbicides can increase or decrease the minimum inhibitory concentration (MIC) of different antibiotics, we provide the first comprehensive test of the hypothesis that the rate of antibiotic resistance evolution under specified conditions can increase, regardless of whether a herbicide increases or decreases the antibiotic MIC. Short term evolution experiments were used for various herbicide and antibiotic combinations. We found conditions where acquired resistance arises more frequently regardless of whether the exogenous non-antibiotic agent increased or decreased antibiotic effectiveness. This “damned if you do/damned if you don’t” outcome suggests that the emergence of antibiotic resistance is exacerbated by additional environmental factors that influence competition between bacteria. Our work demonstrates that bacteria may acquire antibiotic resistance in the environment at rates substantially faster than predicted from laboratory conditions.
Roughness of tensile crack fronts in heterogenous materials

The dynamics of planar crack fronts in heterogeneous media is studied using a recently proposed stochastic equation of motion that takes into account nonlinear effects. The analysis is carried for a moving front in the quasi-static regime using the Self Consistent Expansion. A continuous dynamical phase transition between a flat phase and a dynamically rough phase, with a roughness exponent ζ = 1/2, is found. The rough phase becomes possible due to the destabilization of the linear modes by the nonlinear terms. Taking into account the irreversibility of the crack propagation, we infer that the roughness exponent found in experiments might become history dependent, and so our result gives a lower bound for ζ.
MoonShine: Optimizing OS Fuzzer Seed Selection with Trace Distillation

OS fuzzers primarily test the system-call interface between the OS kernel and user-level applications for security vulnerabilities. The effectiveness of all existing evolutionary OS fuzzers depends heavily on the quality and diversity of their seed system call sequences. However, generating good seeds for OS fuzzing is a hard problem as the behavior of each system call depends heavily on the OS kernel state created by the previously executed system calls. Therefore, popular evolutionary OS fuzzers often rely on hand-coded rules for generating valid seed sequences of system calls that can bootstrap the fuzzing process. Unfortunately, this approach severely restricts the diversity of the seed system call sequences and therefore limits the effectiveness of the fuzzers. In this paper, we develop MoonShine, a novel strategy for distilling seeds for OS fuzzers from system call traces of real-world programs while still preserving the dependencies across the system calls. MoonShine leverages light-weight static analysis for efficiently detecting dependencies across different system calls. We designed and implemented MoonShine as an extension to Syzkaller, a state-of-the-art evolutionary fuzzer for the Linux kernel. Starting from traces containing 2.8 million system calls gathered from 3,220 real-world programs, MoonShine distilled down to just over 14,000 calls while preserving 86% of the original code coverage. Using these distilled seed system call sequences, MoonShine was able to improve Syzkaller’s achieved code coverage for the Linux kernel by 13% on average. MoonShine also found 17 new vulnerabilities in the Linux kernel that were not found by Syzkaller.
Approximation of Bessel functions for nonlinear interaction of acoustic--gravity waves

We present an approximation of Bessel function of the first kind near the origin (near-field). The approximation comprises a simple cosine function that is matched at exactly $\pi/\e$. This allows a smooth matching with the standard far-field approximation. The approximation is useful when nonlinear dynamics comes into play, such as in the case of nonlinear interaction of acoustic--gravity waves in cylindrical coordinates.
Improved Approximations for Posted Price and Second-price Mechanisms

We study the fundamental problem of selling a single indivisible good to one of n buyers with independent valuations. We seek to design improved approximations to the optimal revenue achievable through two simple and widely used mechanisms: second price auction with eager personalized reserve prices, and sequential posted price mechanisms. We give improved approximations of 1− 1 e + 0.022 ∼ 0.6543 for the sequential posted price mechanism and 1− 1 e + 0.029 ∼ 0.662 for the second price auction with eager reserve prices. We also make some progress towards the problem of computing the optimal personalized eager reserve prices for a second price auction.