Imaging-based Parametric Resonance in an Optical Dipole Atom Trap

We report sensitive detection of parametric resonances in a high-density sample of ultracold $^{87}Rb$ atoms confined to a far-off-resonance optical dipole trap. Fluorescence imaging of the expanded ultracold atom cloud after a period of parametric excitation shows significant modification of the atomic spatial distribution and has high sensitivity compared with traditional measurements of parametrically-driven trap loss. Using this approach, a significant shift of the parametric resonance frequency is observed, and attributed to the anharmonic shape of the dipole trap potential

Soft information for localization-of-things

Location awareness is vital for emerging Internetof- Things applications and opens a new era for Localizationof- Things. This paper first reviews the classical localization techniques based on single-value metrics, such as range and angle estimates, and on fixed measurement models, such as Gaussian distributions with mean equal to the true value of the metric. Then, it presents a new localization approach based on soft information (SI) extracted from intra- and inter-node measurements, as well as from contextual data. In particular, efficient techniques for learning and fusing different kinds of SI are described. Case studies are presented for two scenarios in which sensing measurements are based on: 1) noisy features and non-line-of-sight detector outputs and 2) IEEE 802.15.4a standard. The results show that SI-based localization is highly efficient, can significantly outperform classical techniques, and provides robustness to harsh propagation conditions.RYC-2016-1938

Crowd-Centric Counting via Unsupervised Learning

Counting targets (people or things) within a moni-tored area is an important task in emerging wireless applications,including those for smart environments, safety, and security.Conventional device-free radio-based systems for counting targetsrely on localization and data association (i.e., individual-centric information) to infer the number of targets present in an area(i.e., crowd-centric information). However, many applications(e.g., affluence analytics) require only crowd-centric rather than individual-centric information. Moreover, individual-centric approaches may be inadequate due to the complexity of data association. This paper proposes a new technique for crowd-centric counting of device-free targets based on unsupervised learning, where the number of targets is inferred directly from a low-dimensional representation of the received waveforms. The proposed technique is validated via experimentation using an ultra-wideband sensor radar in an indoor environment.RYC-2016-1938

Optimum Quantum Error Recovery using Semidefinite Programming

Quantum error correction (QEC) is an essential element of physical quantum information processing systems. Most QEC efforts focus on extending classical error correction schemes to the quantum regime. The input to a noisy system is embedded in a coded subspace, and error recovery is performed via an operation designed to perfectly correct for a set of errors, presumably a large subset of the physical noise process. In this paper, we examine the choice of recovery operation. Rather than seeking perfect correction on a subset of errors, we seek a recovery operation to maximize the entanglement fidelity for a given input state and noise model. In this way, the recovery operation is optimum for the given encoding and noise process. This optimization is shown to be calculable via a semidefinite program (SDP), a well-established form of convex optimization with efficient algorithms for its solution. The error recovery operation may also be interpreted as a combining operation following a quantum spreading channel, thus providing a quantum analogy to the classical diversity combining operation.Comment: 7 pages, 3 figure

2-Bromo-1,2-diphenylethenyl 4-methyl­phenyl sulfoxide

In the title compound, C21H17BrO2S, the two phenyl rings attached to the ethene group are oriented at dihedral angles of 76.19 (10) and 57.99 (8)° with respect to the Br—C=C—S plane [r.m.s. deviation 0.003 Å]. The sulfonyl-bound phenyl ring forms a dihedral angle of 83.26 (8)° with the above plane. The crystal structure is stabilized by weak C—H⋯π inter­actions

Clinical and echocardiographic characteristics and cardiovascular outcomes according to diabetes status in patients with heart failure and preserved ejection fraction. A report from the Irbesartan in Heart Failure with Preserved Ejection Fraction Trial (I-Preserve)

Background—In patients with HF and preserved ejection fraction (HFpEF), little is known about the characteristics of and outcomes in those with and without diabetes. Methods—We examined clinical and echocardiographic characteristics and outcomes in the Irbesartan in Heart Failure with Preserved Ejection Fraction trial (I-Preserve), according to history of diabetes. Cox regression models were used to estimate hazard ratios (HR) for cardiovascular outcomes adjusted for known predictors, including age, sex, natriuretic peptides, and comorbidity. Echocardiographic data were available in 745 patients and were additionally adjusted for in supplementary analyses. Results—Overall, 1134 of 4128 patients (27%) had diabetes. Compared to those without diabetes, they were more likely to have a history of myocardial infarction (28% vs. 22%), higher BMI (31kg/m2 vs. 29kg/m2), worse Minnesota living with HF score (48 vs. 40), higher median NT-proBNP concentration (403 vs 320 pg/ml; all p<0.01), more signs of congestion but no significant difference in LVEF. Patients with diabetes had a greater left ventricular (LV) mass and left atrial area than patients without diabetes. Doppler E wave velocity (86 vs 76 cm/sec, p<0.0001) and the ratio of E/e' (11.7 vs 10.4, p=0.010) were higher in patients with diabetes. Over a median follow-up of 4.1 years, cardiovascular death or HF hospitalization occurred in 34% of patients with diabetes vs. 22% of those without diabetes; adjusted HR 1.75 (95% CI 1.49-2.05) and 28% vs. 19% of patients with and without diabetes died; adjusted HR 1.59 (1.33-1.91). Conclusions—In HFpEF, patients with diabetes have more signs of congestion, worse quality of life, higher NT-proBNP levels, and a poorer prognosis. They also display greater structural and functional echocardiographic abnormalities. Further investigation is needed to determine the mediators of the adverse impact of diabetes on outcomes in HFPEF, and whether they are modifiable

Wake and power prediction of horizontal-axis wind farm under yaw-controlled conditions with machine learning

The main objective of this study is to employ the Extreme Gradient Boosting (XGBoost) machine learning algorithm to predict the power, wake, and turbulent characteristics of horizontal-axis wind farms under yaw-controlled conditions. For this purpose, a series of high-fidelity numerical simulations using LES method are performed over tandem NREL-5 MW wind turbines to generate the input data for training and testing in machine learning analysis. It is observed that XGBoost is more accurate for wake prediction of the yaw-controlled wind farms compared to ANN, which was used in previous studies. The results illustrate that XGBoost can predict the power with a mean deviation of 0.94 % for different yaw angles, while ANN can estimate the power generation with a mean deviation of 2.15 % for various tested yaw angles. At far wake regions (X > 2000 m) of the second wind turbine, the deviations reach below 1 %. Moreover, XGBoost requires a much shorter training time, 87.5 % faster than ANN. The power production of both wind turbines can be predicted more accurately with XGBoost compared to ANN. The wake prediction time of XGBoost is just 0.105 sec, while this time is 4.480 for the ANN model. In conclusion, XGBoost provides a significant reduction in error and training time compared to ANN and deep learning algorithms over yaw-misaligned wind farms

Anopheles stephensi p38 MAPK signaling regulates innate immunity and bioenergetics during Plasmodium falciparum infection.

BackgroundFruit flies and mammals protect themselves against infection by mounting immune and metabolic responses that must be balanced against the metabolic needs of the pathogens. In this context, p38 mitogen-activated protein kinase (MAPK)-dependent signaling is critical to regulating both innate immunity and metabolism during infection. Accordingly, we asked to what extent the Asian malaria mosquito Anopheles stephensi utilizes p38 MAPK signaling during infection with the human malaria parasite Plasmodium falciparum.MethodsA. stephensi p38 MAPK (AsP38 MAPK) was identified and patterns of signaling in vitro and in vivo (midgut) were analyzed using phospho-specific antibodies and small molecule inhibitors. Functional effects of AsP38 MAPK inhibition were assessed using P. falciparum infection, quantitative real-time PCR, assays for reactive oxygen species and survivorship under oxidative stress, proteomics, and biochemical analyses.ResultsThe genome of A. stephensi encodes a single p38 MAPK that is activated in the midgut in response to parasite infection. Inhibition of AsP38 MAPK signaling significantly reduced P. falciparum sporogonic development. This phenotype was associated with AsP38 MAPK regulation of mitochondrial physiology and stress responses in the midgut epithelium, a tissue critical for parasite development. Specifically, inhibition of AsP38 MAPK resulted in reduction in mosquito protein synthesis machinery, a shift in glucose metabolism, reduced mitochondrial metabolism, enhanced production of mitochondrial reactive oxygen species, induction of an array of anti-parasite effector genes, and decreased resistance to oxidative stress-mediated damage. Hence, P. falciparum-induced activation of AsP38 MAPK in the midgut facilitates parasite infection through a combination of reduced anti-parasite immune defenses and enhanced host protein synthesis and bioenergetics to minimize the impact of infection on the host and to maximize parasite survival, and ultimately, transmission.ConclusionsThese observations suggest that, as in mammals, innate immunity and mitochondrial responses are integrated in mosquitoes and that AsP38 MAPK-dependent signaling facilitates mosquito survival during parasite infection, a fact that may attest to the relatively longer evolutionary relationship of these parasites with their invertebrate compared to their vertebrate hosts. On a practical level, improved understanding of the balances and trade-offs between resistance and metabolism could be leveraged to generate fit, resistant mosquitoes for malaria control