Membrane-inspired quantum shuffled frog leaping algorithm for spectrum allocation

To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm,which is an effective discrete optimization algorithm.Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems.By hybridizing the quantum frog colony optimization and membrane computing,the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure.The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time.Simulation results for three utility functions of a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing.

Spiking neural P systems with anti-spikes and without annihilating priority as number acceptors

Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes wil immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, cal ed ASN P systems without anni-hilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation wil consume one time unit. As a result, such systems using two categories of spiking rules （identified by （a, a） and （a,a^-）） can achieve Turing completeness as number accepting devices.

A Fault Diagnosis Method for Power Systems Based on Temporal Tissue-like P Systems

To quickly and accurately identify faulty components based on the alarm information is critical for the fault diagnosis of power grids.To address this chal-lenge,this paper proposes a novel fault diagnosis method based on temporal tissue-like P system(TTPS).In the proposed method,suspected faulty components are iden-tifiedfirst via a network topology analysis method.An TTPS-based fault diagnosis model is then built for each suspected faulty component to perform fault reasoning,so as to accurately detect the faulty components.To take full advantage of the action signals and temporal information of protection devices,TTPS and its forward temporal reasoning algorithm are proposed.TTPS can synchro-nously model the action and temporal logics of protection devices in an intuitive and graphical way,while the rea-soning algorithm can process the fault alarm information in parallel.To demonstrate the effectiveness and superi-ority of the proposed method,simulations are carried out on the IEEE 14-bus and 118-bus systems,while the results are compared to other two widely adopted methods.Index Terms—Alarm signal,fault diagnosis,membrane computing,power system,tissue-like P system.

Membrane Automata with Priorities

In this paper the one-way P automata with priorities are introduced. Suchautomata are P systems where the membranes are only allowed to consume objects from parentmembranes, under the given conditions. The result of computation of these systems is the set ofmultiset sequences consumed by skin membrane into the system. The rules associated in some orderwith each membrane cannot modify any objects, they can only move them through membrane. We show thatP automata with priorities and two membranes can accept every recursively enumerated language.

Reversible spiking neural P systems

Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as the computing power of reversible SN P systems. Reversible SN P systems are proved to have Turing creativity, that is, they can compute any recursively enumerable set of non-negative integers by simulating universal reversible register machine.

Neuroprotective Effect of Shenfu Injection (参附注射液) Following Cardiac Arrest in Pig Correlates with Improved Mitochondrial Function and Cerebral Glucose Uptake

Objective：To test whether Shenfu Injection（参附注射液,SFI）might attenuate the impact of cerebral energy dysfunction after resuscitation in a pig model of cardiac arrest（CA）.Methods：Thirty-four Wuzhishan miniature inbred pigs were randomly divided into three groups：the SFI group（n=12）,the saline group（SA group,n=12）,and the sham-operated group（sham group,n=10）.Following successful return of spontaneous circulation（ROSC）from 8-min untreated ventricular fibrillation,animals received a continuous infusion of either SFI（0.2 mL/min）or saline for 6 h.Cerebral performance category score was evaluated at 24and 48 h after ROSC,followed by positron emission tomography and computed tomography scans of cerebral glucose uptake.Surviving pigs were euthanized 48 h after ROSC,and the brains were removed for detecting mitochondrial function.Results：Compared with the SA group,SFI treatment produced a better neurologic outcome48 h after ROSC（P〈0.05）.However,there was no significant difference of survival rate between the SA and SFI groups（83.3%vs.81.8%,P〉0.05）.After ROSC,the SA group showed a decrease in the maximum standardized uptake value of different regions in the brain tissue,where SFI treatment can ameliorate these decreases（P〈0.01or P〈0.05）.Improved mitochondrial respiratory properties and higher mitochondrial membrane potential were also found following SFI treatment compared with the SA group at 48 h after ROSC（P〈0.05 or P〈0.01）.Conclusion：SFI treatment after resuscitation has significant neuroprotective effects against disruption of cerebral energy metabolism from CA by improving glucose uptake and by normalizing mitochondrial function.