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Register a new userPersistent URIs Must Be Used To Be Persistent
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Added by
Martin Klein
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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We quantify the extent to which references to papers in scholarly literature use persistent HTTP URIs that leverage the Digital Object Identifier infrastructure. We find a significant number of references that do not, speculate why authors would use brittle URIs when persistent ones are available, and propose an approach to alleviate the problem.
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We report on the main results obtained thanks to an observation campaign, performed with XMM-Newton, of four persistent, low-luminosity (Lx ~ 10^34 erg/s) and long-period (P > 200 s) Be accreting pulsars. We found that all sources considered here are characterized by a spectral excess that can be described with a blackbody component of high temperature (kT > 1 keV) and small area (R < 0.5 km). We show that: 1) this feature is a common property of several low-luminosity X-ray binaries; 2) for most sources the blackbody parameters (radius and temperature) are within a narrow range of values; 3) it can be interpreted as emission from the NS polar caps.
Using the principle of causality as expressed in the Kramers-Kronig relations, we derive a generalized criterion for a negative refractive index that admits imperfect transparency at an observation frequency $omega$. It also allows us to relate the global properties of the loss (i.e. its frequency response) to its local behaviour at $omega$. However, causality-based criteria rely the on the group velocity, not the Poynting vector. Since the two are not equivalent, we provide some simple examples to compare the two criteria.
A broad range of quantum optimisation problems can be phrased as the question whether a specific system has a ground state at zero energy, i.e. whether its Hamiltonian is frustration free. Frustration-free Hamiltonians, in turn, play a central role for constructing and understanding new phases of matter in quantum many-body physics. Unfortunately, determining whether this is the case is known to be a complexity-theoretically intractable problem. This makes it highly desirable to search for efficient heuristics and algorithms in order to, at least, partially answer this question. Here we prove a general criterion - a sufficient condition - under which a local Hamiltonian is guaranteed to be frustration free by lifting Shearers theorem from classical probability theory to the quantum world. Remarkably, evaluating this condition proceeds via a fully classical analysis of a hard-core lattice gas at negative fugacity on the Hamiltonians interaction graph which, as a statistical mechanics problem, is of interest in its own right. We concretely apply this criterion to local Hamiltonians on various regular lattices, while bringing to bear the tools of spin glass physics which permit us to obtain new bounds on the SAT/UNSAT transition in random quantum satisfiability. These also lead us to natural conjectures for when such bounds will be tight, as well as to a novel notion of universality for these computer science problems. Besides providing concrete algorithms leading to detailed and quantitative insights, this underscores the power of marrying classical statistical mechanics with quantum computation and complexity theory.
Emerging wireless technologies, such as 5G and beyond, are bringing new use cases to the forefront, one of the most prominent being machine learning empowered health care. One of the notable modern medical concerns that impose an immense worldwide health burden are respiratory infections. Since cough is an essential symptom of many respiratory infections, an automated system to screen for respiratory diseases based on raw cough data would have a multitude of beneficial research and medical applications. In literature, machine learning has already been successfully used to detect cough events in controlled environments. In this paper, we present a low complexity, automated recognition and diagnostic tool for screening respiratory infections that utilizes Convolutional Neural Networks (CNNs) to detect cough within environment audio and diagnose three potential illnesses (i.e., bronchitis, bronchiolitis and pertussis) based on their unique cough audio features. Both proposed detection and diagnosis models achieve an accuracy of over 89%, while also remaining computationally efficient. Results show that the proposed system is successfully able to detect and separate cough events from background noise. Moreover, the proposed single diagnosis model is capable of distinguishing between different illnesses without the need of separate models.
Scholarly resources, just like any other resources on the web, are subject to reference rot as they frequently disappear or significantly change over time. Digital Object Identifiers (DOIs) are commonplace to persistently identify scholarly resources and have become the de facto standard for citing them. We investigate the notion of persistence of DOIs by analyzing their resolution on the web. We derive confidence in the persistence of these identifiers in part from the assumption that dereferencing a DOI will consistently return the same response, regardless of which HTTP request method we use or from which network environment we send the requests. Our experiments show, however, that persistence, according to our interpretation, is not warranted. We find that scholarly content providers respond differently to varying request methods and network environments and even change their response to requests against the same DOI. In this paper we present the results of our quantitative analysis that is aimed at informing the scholarly communication community about this disconcerting lack of consistency.
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