Coxiella burnetii is the agent of Q fever, or "query fever," a zoonosis first described in Australia in 1937. Since this first description, knowledge about this pathogen and its associated infections has increased dramatically. We review here all the progress made over the last 20 years on this topi …

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Information about Q fever from the U.S. Centers for Disease Control and Prevention.

Information on Q fever for healthcare providers.

Information about Q fever from the U.S. Centers for Disease Control and Prevention.

Chronic Q fever, caused by Coxiella burnetii, has high mortality and morbidity rates if left untreated. Controversy about the diagnosis of this complex disease has emerged recently. We applied the guideline from the Dutch Q Fever Consensus Group and a ...

Coxiella burnetii causes Q fever, a zoonosis, which has acute and chronic manifestations. From 2007 to 2010, the Netherlands experienced a large Q fever outbreak, which has offered a unique opportunity to analyze chronic Q fever cases. In an observational ...

Chronic Q fever, caused by Coxiella burnetii, has high mortality and morbidity rates if left untreated. Controversy about the diagnosis of this complex disease has emerged recently. We applied the guideline from the Dutch Q Fever Consensus Group and a ...

Chronic Q Fever Diagnosis

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We studied 32 heroin and methadone addicts, divided into 4 groups according to the type of drugs used: 5 heroin-dependent, 10 taking methadone plus heroin more or less constantly, 10 taking methadone plus heroin occasionally, and 7 taking methadone only. 93% of the heroin addicts and 65% of those ta …

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We present a quantum interior-point method (IPM) for second-order cone programming (SOCP) that runs in time $\widetilde{O} \left( n\sqrt{r} \frac{ζκ}{δ^2} \log...

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This paper investigates an intelligent reflecting surface (IRS)-aided multi-cell multiple-input single-output (MISO) network with a set of multi-antenna base stations (BSs) each communicating with multiple single-antenna users, in which an IRS is dedicatedly deployed for assisting the wireless transmission and suppressing the inter-cell interference. Under this setup, we jointly optimize the coordinated transmit beamforming vectors at the BSs and the reflective beamforming vector (with both reflecting phases and amplitudes) at the IRS, for the purpose of maximizing the minimum weighted signal-to-interference-plus-noise ratio (SINR) at the users, subject to the individual maximum transmit power constraints at the BSs and the reflection constraints at the IRS. To solve the non-convex min-weighted-SINR maximization problem, we first present an exact-alternating-optimization approach to optimize the transmit and reflective beamforming vectors in an alternating manner, in which the transmit and reflective beamforming optimization subproblems are solved exactly in each iteration by using the techniques of second-order-cone program (SOCP) and semi-definite relaxation (SDR), respectively. However, the exact-alternating-optimization approach has high computational complexity, and may lead to compromised performance due to the uncertainty of randomization in SDR. To avoid these drawbacks, we further propose an inexact-alternating-optimization approach, in which the transmit and reflective beamforming optimization subproblems are solved inexactly in each iteration based on the principle of successive convex approximation (SCA). In addition, to further reduce the computational complexity, we propose a low-complexity inexact-alternating-optimization design, in which the reflective beamforming optimization subproblem is solved more inexactly. Via numerical results, it is shown that the proposed three designs achieve significantly increased min-weighted-SINR values, as compared with benchmark schemes without the IRS or with random reflective beamforming. It is also shown that the inexact-alternating-optimization design outperforms the exact-alternating-optimization one in terms of both the achieved min-weighted-SINR value and the computational complexity, while the low-complexity inexact-alternating-optimization design has much lower computational complexity with slightly compromised performance. Furthermore, we show that our proposed design can be applied to the scenario with unit-amplitude reflection constraints, with a negligible performance loss.

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