Chinese Herbal Medicine: A Safe Alternative Therapy for Urinary Tract Infection in Patients with Renal Insufficiency

We have used reduced doses of Chinese herbs for estimation of urinary tract infections (UTIs) patients with stable impairment of renal function. A total of 33 adult female patients with moderately impaired renal function and symptomatic UTIs were included in this study. Urine cultures were carried out. Patients were monitored clinically and with various laboratory tests. Chinese herbal concoction divided by milligrams of creatinine per 100 ml were orally administrated for ten days. Three patients were excluded from final analysis. Most of the patients responded symptomatically to treatment. Chinese herbs eradicated the primary pathogen in 68.7% of the patients at the day 10 of treatment. Two patients relapsed (one had abbreviated courses of therapy) 6 to 8 days posttreatment. Organisms which recurred included Escherichia coli and Pseudomonas aeruginosa. Bacterial reinfections occurred 5 to 8 days posttreatment in four patients. Adverse reactions observed among the 30 patients were rare. Nausea (6.67%) and mild elevation of hepatic enzymes (3.33%) were probably drug related. Nausea disappeared when the therapy ended. Elevated hepatic enzymes resumed at the 2-week follow-up. Two patients demonstrated slight increases in serum creatinine on day 10 of treatment. One patient had a 12.5% elevation over baseline and the other had a 13.0% elevation. Serum creatinine values had improved in these two patients at 4-week follow-up. Chinese herbal medicine was effective and safe in the treatment of UTIs with renal insufficiency.Key words: Chinese herbs; Urinary tract infection; Renal insufficiency; Dose adjustment

Muon spin rotation study of the topological superconductor SrxBi2Se3

We report transverse-field (TF) muon spin rotation experiments on single crystals of the topological superconductor Sr$_x$Bi$_2$Se$_3$ with nominal concentrations $x=0.15$ and $0.18$ ($T_c \sim 3$ K). The TF spectra ($B= 10$ mT), measured after cooling to below $T_c$ in field, did not show any additional damping of the muon precession signal due to the flux line lattice within the experimental uncertainty. This puts a lower bound on the magnetic penetration depth $\lambda \geq 2.3 ~\mu$m. However, when we induce disorder in the vortex lattice by changing the magnetic field below $T_c$ a sizeable damping rate is obtained for $T \rightarrow 0$. The data provide microscopic evidence for a superconducting volume fraction of $\sim 70~ \%$ in the $x=0.18$ crystal and thus bulk superconductivity.Comment: 6 pages, includes 4 figure

Weak ferromagnetism and spin glass state with nano-sized nickel carbide

Ni3C nanoparticles of about 40 nm have been studied experimentally to exhibit weak ferromagnetic (FM), spin-glass (SG) and paramagnetic (PM) properties. The freezing temperature of the SG phase at zero applied field is determined as, TF0 ~ 11.0 K. At T > TF0, a very weak ferromagnetism has been observed over a PM background. The Curie temperature, TC, is shown to exceed 300 K and the ferromagnetism at 300 K is determined as about 0.02 emu/g (~6.7*10^{-4}mu_B per Ni3C formula unit) by subtracting the background paramagnetism. An anomalous dip appears in the temperature dependent coercivity, HC(T), near the freezing temperature, TF0. It reflects a distortedly reduced coercivity in the M(H) hysteresis loop measured at T = TF0 with the applied sweeping field around H = 0. This is attributable to the exchange coupling effect between the SG and the weak FM phases. The possible origin of the magnetic moments that account for the observed FM, SG and PM properties is discussed.Comment: 25 pages, 8 figures, 1 table, J Appl Phys In pres

Learning quadratic games on networks

Individuals, or organizations, cooperate with or compete against one another in a wide range of practical situations. Such strategic interactions are often modeled as games played on networks, where an individual’s payoff depends not only on her action but also on that of her neighbors. The current literature has largely focused on analyzing the characteristics of network games in the scenario where the structure of the network, which is represented by a graph, is known beforehand. It is often the case, however, that the actions of the players are readily observable while the underlying interaction network remains hidden. In this paper, we propose two novel frameworks for learning, from the observations on individual actions, network games with linear-quadratic payoffs, and in particular, the structure of the interaction network. Our frameworks are based on the Nash equilibrium of such games and involve solving a joint optimization problem for the graph structure and the individual marginal benefits. Both synthetic and real-world experiments demonstrate the effectiveness of the proposed frameworks, which have theoretical as well as practical implications for understanding strategic interactions in a network environment

Classification of Overlapped Audio Events Based on AT, PLSA, and the Combination of Them

Audio event classification, as an important part of Computational Auditory Scene Analysis, has attracted much attention. Currently, the classification technology is mature enough to classify isolated audio events accurately, but for overlapped audio events, it performs much worse. While in real life, most audio documents would have certain percentage of overlaps, and so the overlap classification problem is an important part of audio classification. Nowadays, the work on overlapped audio event classification is still scarce, and most existing overlap classification systems can only recognize one audio event for an overlap. In this paper, in order to deal with overlaps, we innovatively introduce the author-topic (AT) model which was first proposed for text analysis into audio classification, and innovatively combine it with PLSA (Probabilistic Latent Semantic Analysis). We propose 4 systems, i.e. AT, PLSA, AT-PLSA and PLSA-AT, to classify overlaps. The 4 proposed systems have the ability to recognize two or more audio events for an overlap. The experimental results show that the 4 systems perform well in classifying overlapped audio events, whether it is the overlap in training set or the overlap out of training set. Also they perform well in classifying isolated audio events

Magnetodielectric effect in nickel nanosheet-Na-4 mica composites

Nickel nanosheets of thickness 0.6 nm were grown within the nanochannels of Na-4 mica template. The specimens show magnetodielectric effect at room temperature with a change of dielectric constant as a function of magnetic field, the electric field frequency varying from 100 to 700 kHz. A decrease of 5% in the value of dielectric constant was observed up to a field of 1.2 Tesla. This is explained by an inhomogeneous two-component composite model as theoretically proposed recently. The present approach will open up synthesis of various nanocomposites for sensor applications.Comment: 11 pages, 7 figure

Prediction of mechanical properties of composite materials based on convolutional neural network-long and short-term memory neural network

Convolutional neural networks (CNNs) have the advantage of processing complex images and extracting feature information from the images, while long and short term memory networks (LSTMs) are good at processing data with sequential features. In this paper, based on the deep material network, we propose to apply the CNN-LSTM neural network model to the prediction of mechanical properties of carbon fibre composites. Then the experimental results are compared with the model prediction results, and the results show that the CNN-LSTM prediction of the mechanical properties of carbon fibre composites is within 5% of the corresponding tensile mechanical experimental results, which proves the accuracy of the CNN-LSTM neural network model in the prediction of the mechanical properties of carbon fibre composites

Conceptual Design for Long-Endurance Convertible Unmanned Aerial System

This research is aimed at analysing the effect of design parameters on critical aerodynamic performance of convertible unmanned aerial vehicle (UAV) with vertical take-off and landing (VTOL) capabilities and providing a sizing tool for its conceptual design. The research was based on new aerodynamic models specifically developed and validated for convertible aircraft, performed using mission-based optimisation techniques. To accommodate a wide range of convertible aircraft configurations, a non-linear lifting-line method was used to efficiently analyse different combinations of lifting surface and propeller arrangements. Propeller loads were calculated using a blade element momentum approach and corrected for high incidence angle conditions according to numerical and experimental studies. Propeller-wing interactions were considered by modifying local boundary conditions at wing sections immersed in propeller slipstream. Previous studies have suggested that the design of convertible aircraft is sensitive to typical mission requirements, notably the endurance breakdown between near-hover flight and cruise flight. A clear sizing law for wing and propeller according to given mission specification could greatly improve the understanding of compromises between hover and high speed flight