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Alzheimer's disease (AD) is a leading cause of dementia in the elderly, with no effective treatment currently available. Transcranial direct current stimulation (tDCS), a non-drug and non-invasive therapy, has been testified efficient in cognitive enhancement. This study aims to examine the effects of tDCS on brain function in a mouse model of AD. The amyloid precursor protein (APP) and presenilin 1 (PS1) transgenic mice (7-8 months old) were subjected to 20-min anodal and cathodal tDCS (atDCS and ctDCS; 300 mA, 3.12 mA/cm2) for continuous five days. tDCS was applied on the left frontal skull of the animals, targeting on their prefrontal cortex (PFC). Behavioral performances were assessed by open-field, Y-maze, Barnes maze and T-maze paradigms; and their PFC electroencephalogram (EEG) activities were recorded under spontaneous state and during Y-maze performance. Behaviorally, atDCS and ctDCS improved spatial learning and/or memory in AD mice without affecting their general locomotion and anxiety-like behaviors, but the effects depended on the testing paradigms. Interestingly, the memory improvements were accompanied by decreased PFC EEG delta (2-4 Hz) and increased EEG gamma (20-100 Hz) activities when the animals needed memory retrieval during task performance. The decreased EEG delta activities could also be observed in animals under spontaneous state. Specifically, atDCS increased PFC EEG activity in the alpha band (8-12 Hz) for spontaneous state, whereas ctDCS increased that in alpha-beta band (8-20 Hz) for task-related state. In addition, some EEG changes after ctDCS could be found in other cortical regions except PFC. These data indicate that tDCS can reverse the situation of slower brain activity in AD mice, which may further lead to cognitive improvement. Our work highlights the potential clinical use of tDCS to restore neural network activity and improve cognition in AD. [ABSTRACT FROM AUTHOR]

Multiyear drought has been proved to cause non-stationary rainfall-runoff relationship. But whether this change can occur in catchments that have also experienced vegetation change and whether it invalidates the most widely used methods (the paired-catchment method (PCM), the time-trend method (TTM), and the sensitivity-based method (SBM)) for estimating impacts of vegetation change on runoff is still unknown and rarely discussed. In the Red Hill paired experimental catchments in Australia, which has experienced a 10-year drought (2000-2009) and afforestation, estimated inconsistent afforestation impacts were 32.8%, 93.5%, and 76.1% of total runoff changes by the PCM, TTM and SBM, respectively. In addition to afforestation, multiyear drought has also led to the non-stationary rainfall-runoff relationship of the paired catchments. For the TTM and SBM, traditional application did not further differentiate different drivers of non-stationary rainfall-runoff relationship, which led to significant overestimation of afforestation effects. A new framework was proposed to separate the effects of three factors on runoff changes including vegetation change, climate variability and multiyear drought caused non-stationarity. Based on the new framework, impacts of afforestation on runoff were 38.8% by the TTM and 21.4% by the SBM, agreeing well with that by the PCM (32.8%). Using paired-catchment observations, this study proved multiyear drought can induce non-stationary rainfall-runoff relationship and proposed a new framework to better separate the impact of vegetation changes on runoff under climate-induced non-stationary condition. More importantly, paired-catchment method is proven to be still the most reliable method even the control catchment experienced climate-induced shift in rainfall-runoff relationship. [ABSTRACT FROM AUTHOR]

Mobile Augmented Reality (AR), which overlays digital content on the real-world scenes surrounding a user, is bringing immersive interactive experiences where the real and virtual worlds are tightly coupled. To enable seamless and precise AR experiences, an image recognition system that can accurately recognize the object in the camera view with low system latency is required. However, due to the pervasiveness and severity of image distortions, an effective and robust image recognition solution for “in the wild” mobile AR is still elusive. In this article, we present CollabAR, an edge-assisted system that provides distortion-tolerant image recognition for mobile AR with imperceptible system latency. CollabAR incorporates both distortion-tolerant and collaborative image recognition modules in its design. The former enables distortion-adaptive image recognition to improve the robustness against image distortions, while the latter exploits the spatial-temporal correlation among mobile AR users to improve recognition accuracy. Moreover, as it is difficult to collect a large-scale image distortion dataset, we propose a Cycle-Consistent Generative Adversarial Network-based data augmentation method to synthesize realistic image distortion. Our evaluation demonstrates that CollabAR achieves over 85% recognition accuracy for “in the wild” images with severe distortions, while reducing the end-to-end system latency to as low as 18.2 ms. [ABSTRACT FROM AUTHOR]

The most widely used approaches for estimating impacts of vegetation changes on runoff are the paired-catchment method, the time-trend analysis method, and the sensitivity-based method. These three methods have yielded consistent results in many paired-catchment studies, except at the Red Hill experimental site in Australia. However, reasons for the inconsistency have not yet been identified. The objective of this study was to identify the reasons for the inconsistency amongst results using observations of two paired catchments from 1990 to 2015. Results from these three methods showed that afforestation accounted for 32.8 %, 93.5 %, and 76.1 % of total runoff changes, respectively. The inconsistency in results were still apparent even the longest available observation record was used. The rainfall-runoff relationship of the control catchment has been used only in the paired-catchment method. This relationship was confirmed to become non-stationary during the pre- and post-calibration periods due to a 10-year prolonged drought, leading to the inconsistency amongst results. By eliminating drought's effects on the rainfall-runoff relationship of the control catchment, afforestation's contribution to runoff reduction was 73.4 % using the paired-catchment method, agreeing well the other two methods. This study not only revealed the reason for the inconsistent results that had long been observed at the famous experimental site, but also proved, using experimental observations, that prolonged drought can induce non-stationary rainfall-runoff relationship in catchment. It also demonstrated that the stationarity test is vital for correct use of historical time series and effective research on ecological hydrology in the case of frequent extreme climate. [ABSTRACT FROM AUTHOR]

The air path of a turbocharged diesel engine is a multi-input multi-output (MIMO) system with strong nonlinearity, coupling effect, delay and actuator constraints. This makes the design and tuning of the controller complex. In this paper, a tuneable model predictive control (TMPC) controller for a diesel engine's air path with dual loop exhaust gas recirculation (DLEGR) is presented. The objective is to regulate the intake manifold pressure and exhaust gas recirculation (EGR) mass flow in each loop to meet the time-varying setpoints through coordinated control of the variable geometry turbocharger (VGT) and EGR valves. The TMPC controller adopts the design framework of an MPC controller. This controller is also able to provide a map-based switching scheme for the local controller and the controller's weightings. A comparison between the TMPC controller and a conventional PID controller is conducted on a validated real-time engine model. The simulation results show that the TMPC controller achieves lower overshoot, faster response and a shorter settling time on the manipulated objects. These improvements are beneficial for obtaining lower fuel consumption. In order to test the capability of the TMPC controller, it is validated on a hardware in the loop (HIL) platform. The results show that the agreement between the simulation and the actual ECU's response is good. [ABSTRACT FROM AUTHOR]

In this paper we present a research of propagation characteristics of global Rossby wave and mesoscale eddies, and we preliminarily discussing the relationship between them from multiple datasets analysis. By filtering the MSLA-H data and by means of optimized SSH method we have extracted signals of the Rossby wave, and estimated the propagation speed (zonal phase speed) of the Rossby wave and eddies. Validation for the identification of the Rossby wave also has been completed with the Argo temperature and salinity data. The prime focus covers: propagation speed comparison between the Rossby wave and the eddies, propagation characteristics in different regions. Overlaying the signals of the Rossby wave with the signatures of the eddies indicates that the Rossby wave and the eddies propagates together (westward only) in the mid-latitude, but differences appear with increasing of latitude, especially in some areas affected by ocean current, for instance, the West Wind Drift (WWD) and the North Atlantic Drift (NAD). Actually we have found that the currents led the eddies, and the Rossby wave might play an accelerative or moderative role in the eddies propagation, as a result of the velocities of the eddies and the currents were matched well, but comparison between the Rossby wave and the eddies revealed disparity. The findings are useful for understanding the relationship between the Rossby wave and mesoscale eddies. [ABSTRACT FROM AUTHOR]

Background: Zinc plays important roles in maintaining normal function of the prostate and in development of prostate malignancy. It has been demonstrated that prostate malignant epithelial cells contain much less cellular zinc than the surrounding normal epithelial cells. However, the pathway(s) which leads to lower zinc accumulation in malignant prostate epithelial cells is poorly understood. In this study, the zinc homeostatic features of two human prostate epithelial cell lines (non-tumorigenic, RWPE1, and tumorigenic, RWPE2) were investigated. Effects of over-expression of ZIP1 in RWPE2 on cell proliferation and apoptosis were also studied. Results: RWPE2 accumulated less intracellular zinc than RWPE1 due to the decreased zinc uptake activity. The mRNA expression of ZIP1 and ZIP3 in RWPE1 and RWPE2 was comparable. However, the protein expression of ZIP1 in RWPE2 was lower than that in RWPE1. ZIP3 was detected in a lysosomal compartment of RWPE2 while no ZIP3 was detected in the same compartment of RWPE1. Over-expression of ZIP1 in RWPE2 resulted in an elevation of intracellular zinc concentration and suppression of cell growth of RWPE2 due to the increased apoptosis. Conclusion: These findings suggest that tumorigenic prostate epithelial cells accumulated less intracellular zinc than non-tumorigenic prostate epithelial cells. The reduction in capacity for accumulation of intracellular zinc in tumorigenic prostate epithelial cells may be caused by the decrease in the ZIP1 protein expression and the intracellular redistribution of ZIP3 in RWPE2. RWPE1 and RWPE2 are excellent cellular models to study the association of intracellular zinc levels with prostate cancer progression. [ABSTRACT FROM AUTHOR]

Intensity mapping is a promising technique for surveying the large-scale structure of our universe from z = 0 to z ∼ 150, using the brightness temperature field of spectral lines to directly observe previously unexplored portions of our cosmic timeline. Examples of targeted lines include the 21 cm hyperfine transition of neutral hydrogen, rotational lines of carbon monoxide, and fine-structure lines of singly ionized carbon. Recent efforts have focused on detections of the power spectrum of spatial fluctuations, but have been hindered by systematics such as foreground contamination. This has motivated the decomposition of data into Fourier modes perpendicular and parallel to the line of sight, which has been shown to be a particularly powerful way to diagnose systematics. However, such a method is well-defined only in the limit of a narrow-field, flat-sky approximation. This limits the sensitivity of intensity mapping experiments, as it means that wide surveys must be separately analyzed as a patchwork of smaller fields. In this paper, we develop a framework for analyzing intensity mapping data in a spherical Fourier–Bessel basis, which incorporates curved sky effects without difficulty. We use our framework to generalize a number of techniques in intensity mapping data analysis from the flat sky to the curved sky. These include visibility-based estimators for the power spectrum, treatments of interloper lines, and the “foreground wedge” signature of spectrally smooth foregrounds. [ABSTRACT FROM AUTHOR]