Adaptive Transient Fault Model for Sensor Attack Detection

This paper considers the problem of sensor attack detection for multiple operating mode systems, building upon an existing attack detection method that uses a transient fault model with fixed parameters. For a multiple operating mode system, the existing method would have to use the most conservative model parameters to preserve the soundness in attack detection, thus not being effective in attack detection for some operating modes. To address this problem, we propose an adaptive transient fault model to use the appropriate parameter values in accordance with the change of the operating mode of the system. The benefit of our proposed system is demonstrated using real measurement data obtained from an unmanned ground vehicle

Adaptive Threshold Generation for Fault Detection with High Dependability for Cyber-Physical Systems

Cyber-physical systems (CPS) applied to safety-critical or mission-critical domains require high dependability including safety, security, and reliability. However, the safety of CPS can be significantly threatened by increased security vulnerabilities and the lack of flexibility in accepting various normal environments or conditions. To enhance safety and security in CPS, a common and cost-effective strategy is to employ the model-based detection technique; however, detecting faults in practice is challenging due to model and environment uncertainties. In this paper, we present a novel generation method of the adaptive threshold required for providing dependability for the model-based fault detection system. In particular, we focus on statistical and information theoretic analysis to consider the model and environment uncertainties, and non-linear programming to determine an adaptive threshold as an equilibrium point in terms of adaptability and sensitivity. To do this, we assess the normality of the data obtained from real sensors, define performance measures representing the system requirements, and formulate the optimal threshold problem. In addition, in order to efficiently exploit the adaptive thresholds, we design the storage so that it is added to the basic structure of the model-based detection system. By executing the performance evaluation with various fault scenarios by varying intensities, duration and types of faults injected, we prove that the proposed method is well designed to cope with uncertainties. In particular, against noise faults, the proposed method shows nearly 100% accuracy, recall, and precision at each of the operation, regardless of the intensity and duration of faults. Under the constant faults, it achieves the accuracy from 85.4% to 100%, the recall of 100% from the lowest 54.2%, and the precision of 100%. It also gives the accuracy of 100% from the lowest 83.2%, the recall of 100% from the lowest 43.8%, and the precision of 100% against random faults. These results indicate that the proposed method achieves a significantly better performance than existing dynamic threshold methods. Consequently, an extensive performance evaluation demonstrates that the proposed method is able to accurately and reliably detect the faults and achieve high levels of adaptability and sensitivity, compared with other dynamic thresholds

The Effects of Forest Therapy on Immune Function

We conducted a systematic review of the effects of a forest therapy program on adults’ immune function. We used PICO-SD (participants, interventions, comparisons, outcomes, study design) to identify key items. The participants were adults over the age of 18 and the intervention was forest therapy. Our comparisons included studies that comparatively analyzed urban groups or groups that did not participate in forest therapy intervention. Cases without control groups were also included. Immunological outcome measures were included in measuring intervention outcomes. All experimental studies, such as randomized controlled trials (RCTs), non-equivalent control group designs (non-RCTs), and one-group pretest-posttest design were included in the study design. A total of 13 studies were included for comparison. Forest therapy programs were divided into lodging-type and session-type programs. The representative measures for evaluating the effects of immune function were the number of NK cells, the cytotoxic activity of NK cells, and cytotoxic effector molecules. Most studies reported improvement in these measures when comparing values after intervention with values before the forest therapy intervention. Therefore, forest therapy has been found to be effective in improving immune function. More RCT studies on the effects of forest therapy on immune function are necessary

Facile Synthesis of AuPd Nanochain Networks on Carbon Supports and Their Application as Electrocatalysts for Oxygen Reduction Reaction

The present work reports the facile synthesis and characterization of carbon-supported porous Pd shell coated Au nanochain networks (AuPdNNs/C). By using Co nanoframes as sacrificial templates, AuPdNNs/C series have been prepared by a two-step galvanic replacement reaction (GRR) technique. In the first step, the Au metal precursor, HAuCl4, reacts spontaneously with the formed Co nanoframes through the GRR, resulting in Au nanochain networks (AuNNs). The second GRR is performed with various concentrations of Pd precursor (0.1, 1, and 10mM PdCl2), resulting in AuPdNNs/C. The synthesized AuPdNNs/C series are investigated as electrocatalysts for oxygen reduction reaction (ORR) in alkaline solution. The physical properties of the AuPdNNs/C catalysts are characterized by scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), UV-vis absorption spectroscopy, and cyclic voltammetry (CV). Rotating disk electrode (RDE) voltammetric studies show that the Au0.8Pd0.2NNs/C (prepared using 1mM PdCl2) has the highest ORR activity among all the AuPdNNs/C series, which is comparable to commercial Pt catalyst (E-TEK). The ORR activity of AuPdNNs/C is presumably due to the enhanced Pd surface area and high porosity of Pd nanoshells. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cerebral Hemodynamics and Vascular Reactivity in Mild and Severe Ischemic Rodent Middle Cerebral Artery Occlusion Stroke Models

Ischemia can cause decreased cerebral neurovascular coupling, leading to a failure in the autoregulation of cerebral blood flow. This study aims to investigate the effect of varying degrees of ischemia on cerebral hemodynamic reactivity using in vivo realtime optical imaging. We utilized direct cortical stimulation to elicit hyper-excitable neuronal activation, which leads to induced hemodynamic changes in both the normal and middle cerebral artery occlusion (MCAO) ischemic stroke groups. Hemodynamic measurements from optical imaging accurately predict the severity of occlusion in mild and severe MCAO animals. There is neither an increase in cerebral blood volume nor in vessel reactivity in the ipsilateral hemisphere (I.H) of animals with severe MCAO. The pial artery in the contralateral hemisphere (C.H) of the severe MCAO group reacted more slowly than both hemispheres in the normal and mild MCAO groups. In addition, the arterial reactivity of the I.H in the mild MCAO animals was faster than the normal animals. Furthermore, artery reactivity is tightly correlated with histological and behavioral results in the MCAO ischemic group. Thus, in vivo optical imaging may offer a simple and useful tool to assess the degree of ischemia and to understand how cerebral hemodynamics and vascular reactivity are affected by ischemia. © Experimental Neurobiology 2016.2

Water Extract of Pleurotus eryngii var. ferulae Prevents High-Fat Diet-Induced Obesity by Inhibiting Pancreatic Lipase

Pleurotus eryngii var. ferulae (PEF) is traditionally used in the prevention and treatment of lifestyle-related diseases. In this study, we investigated the ability of PEF extract to prevent obesity and metabolic diseases and explored the underlying mechanism. Mice were fed a high-fat diet (HFD) containing PEF extract for 12 weeks, and their body weight, adipose tissue and liver weights, and lipid profiles and blood glucose levels, were monitored. Fecal triglyceride (TG) levels were also measured and olive oil-loading tests were performed. Furthermore, the effect of PEF extract on pancreatic lipase (PL) activity was examined in vitro. Treatment with PEF extract for 12 weeks resulted in a significant decrease in the HFD-induced increases in body weight, white adipose tissue weight, liver weights, and lipid profiles, and improved glucose tolerance and insulin sensitivity. To assess the mechanism underlying the effect of PEF extract on obesity and diabetes, we investigated its role in inhibiting lipid absorption. Consumption of an HFD containing PEF extract significantly increased the TG level in feces compared with the controls, suggesting inhibition of TG absorption in the digestive tract. Furthermore, PEF extract suppressed the increase in serum TG levels resulting from oral administration of a lipid emulsion to mice, confirming inhibition of TG absorption. Moreover, PEF extract inhibited PL activity in vitro. Our combined results indicate that the anti-obesity and antidiabetic effect of PEF extract in mice fed an HFD may be caused by inhibition of lipid absorption as a result of reduced PL activity.11Nsciescopuskc