Iptakalim,an ATP-sensitive potassium channel opener,confers neuroprotection against cerebral ischemia/reperfusion injury in rats by protecting neurovascular unit cells

Objective:To investigate the role of iptakalim,an ATP-sensitive potassium channel opener,in transient cerebral ischemia/reperfusion (I/R) injury and its involved mechanisms.Methods:Intraluminal occlusion of middle cerebral artery (MCAO) in a rat model was used to investigate the effect of iptakalim at different time points.Infarct volume was measured by staining with 2,3,5-triphenyltetrazolium chloride,and immunohistochemistry was used to evaluate the expressions of Bcl-2 and Bax.In vitro,neurovascular unit (NVU) cells,including rat primary cortical neurons,astrocytes,and cerebral microvascular endothelial cells,were cultured and underwent oxygen-glucose deprivation (OGD).The protective effect of iptakalim on NVU cells was investigated by cell viability and injury assessments,which were measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and release of lactate dehydrogenase.Caspase-3,Bcl-2 and Bax mRNA expressions were evaluated by real-time polymerase chain reaction (PCR).Results:Administration of iptakalim 0 or 1 h after reperfusion significantly reduced infarct volumes,improved neurological scores,and attenuated brain edema after cerebral I/R injury.Iptakalim treatment (0 h after reperfusion) also reduced caspase-3 expression and increased the ratio of Bcl-2 to Bax by immunohistochemistry.Iptakalim inhibited OGD-induced cell death in cultured neurons and astrocytes,and lactate dehydrogenase release from cerebral microvascular endothelial cells.Iptakalim reduced mRNA expression of caspase-3 and increased the ratio of Bcl-2 to Bax in NVU cells.Conclusions:Iptakalim confers neuroprotection against cerebral I/R injury by protecting NVU cells via inhibiting of apoptosis.

Probabilistic Modeling and Optimization of Real-Time Protocol for Multifunction Vehicle Bus

In this paper, we present the modeling and optimization of a Real-Time Protocol（RTP） used in Train Communication Networks（TCN）. In the proposed RTP, message arbitration is represented by a probabilistic model and the number of arbitration checks is minimized by using the probability of device activity. Our optimized protocol is fully compatible with the original standard and can thus be implemented easily. The experimental results demonstrate that the proposed algorithm can reduce the number of checks by about 50%, thus significantly enhancing bandwidth.

Understanding Social Relationships with Person-Pair Relations

Social relationship understanding infers existing social relationships among individuals in a given scenario,which has been demonstrated to have a wide range of practical value in reality.However,existing methods infer the social relationship of each person pair in isolation,without considering the context-aware information for person pairs in the same scenario.The context-aware information for person pairs exists extensively in reality,that is,the social relationships of different person pairs in a simple scenario are always related to each other.For instance,if most of the person pairs in a simple scenario have the same social relationship,“friends”,then the other pairs have a high probability of being“friends”or other similar coarse-level relationships,such as“intimate”.This context-aware information should thus be considered in social relationship understanding.Therefore,this paper proposes a novel end-to-end trainable Person-Pair Relation Network(PPRN),which is a GRU-based graph inference network,to first extract the visual and position information as the person-pair feature information,then enable it to transfer on a fully-connected social graph,and finally utilizes different aggregators to collect different kinds of person-pair information.Unlike existing methods,the method—with its message passing mechanism in the graph model—can infer the social relationship of each person-pair in a joint way(i.e.,not in isolation).Extensive experiments on People In Social Context(PISC)-and People In Photo Album(PIPA)-relation datasets show the superiority of our method compared to other methods.

Application Specified Soft-Error Failure Rate Analysis Using Sequential Equivalence Checking Techniques

Soft errors have become a critical challenge as a result of technology scaling. Existing circuit-hardening techniques are commonly associated with prohibitive overhead of performance, area, and power. However,evaluating the influence of soft errors in Flip-Flops(FFs) on the failure of circuit is a difficult verification problem.Here, we proposed a novel flip-flop soft-error failure rate analysis methodology using a formal method with respect to application behaviors. Approach and optimization techniques to implement the proposed methodology based on the given formula using Sequential Equivalence Checking(SEC) are introduced. The proposed method combines the advantage of formal technique-based approaches in completeness and the advantage of application behaviors in accuracy to differentiate vulnerability of components. As a result, the FFs in a circuit are sorted by their failure rates, and designers can use this information to perform optimal hardening of selected sequential components against soft errors. Experimental results of an implementation of a SpaceWire end node and the largest ISCAS’89 benchmark sequential circuits indicate the feasibility and potential scalability of our approach. A case study on an instruction decoder of a practical 32-bit microprocessor demonstrates the applicability of our method.

Review of design principles of 2D photonic crystal microcavity biosensors in silicon and their applications

In this paper, we reviewed the design principles of two-dimensional （2D） silicon photonic crystal microcavity （PCM） biosensors coupled to photonie crystal waveguides （PCWs）. Microcavity radiation loss is con- trolled by engineered the cavity mode volume. Coupling loss into the waveguide is controlled by adjusting the position of the microcavity from the waveguide. We also investigated the dependence of analyte overlap integral （also called fill fraction） of the resonant mode as well as the effect of group index of the coupling waveguide at the resonant wavelength of the microcavity. In addition to the cavity properties, absorbance of the sensing medium or analyte together with the affinity constant of the probe and target biomarkers involved in the biochemical reaction also limits the minimum detection limits. We summarized our results in applications in cancer biomarker detection, heavy metal sensing and therapeutic drug monitoring.