Input Synthesis for Sampled Data Systems by Program Logic

Inspired by a concrete industry problem we consider the input synthesis problem for hybrid systems: given a hybrid system that is subject to input from outside (also called disturbance or noise), find an input sequence that steers the system to the desired postcondition. In this paper we focus on sampled data systems--systems in which a digital controller interrupts a physical plant in a periodic manner, a class commonly known in control theory--and furthermore assume that a controller is given in the form of an imperative program. We develop a structural approach to input synthesis that features forward and backward reasoning in program logic for the purpose of reducing a search space. Although the examples we cover are limited both in size and in structure, experiments with a prototype implementation suggest potential of our program logic based approach.Comment: In Proceedings HAS 2014, arXiv:1501.0540

Fulde-Ferrell-Larkin-Ovchinnikov state in a superconducting thin film attached to a ferromagnetic cluster

We study theoretically the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) states appearing locally in a superconducting thin film with a small circular magnetic cluster. By solving the Eilenberger equation in two dimensions, we calculate the pair potential, pairing correlations, free-energy density, and quasiparticle density of states for various cluster sizes and exchange potentials. Increasing the exchange potential and cluster size leads to a higher number of nodes in the pair potential. Although the free-energy density beneath the ferromagnet locally exceeds the normal-state value, the FFLO states are stabilized by the superconducting condensate away from the magnetic cluster. Analyzing the pairing-correlation functions, we show that the spatial variation of the spin-singlet s-wave pair potential generates p-wave Cooper pairs. These odd-frequency Cooper pairs play a dominant role in governing the inhomogeneous subgap spectra observed in the local density of states. Furthermore, we propose an experimental method for the detection of local FFLO states by analyzing the quasiparticle density of states.</p

Efficient Model Selection for Predictive Pattern Mining Model by Safe Pattern Pruning

Predictive pattern mining is an approach used to construct prediction models when the input is represented by structured data, such as sets, graphs, and sequences. The main idea behind predictive pattern mining is to build a prediction model by considering substructures, such as subsets, subgraphs, and subsequences (referred to as patterns), present in the structured data as features of the model. The primary challenge in predictive pattern mining lies in the exponential growth of the number of patterns with the complexity of the structured data. In this study, we propose the Safe Pattern Pruning (SPP) method to address the explosion of pattern numbers in predictive pattern mining. We also discuss how it can be effectively employed throughout the entire model building process in practical data analysis. To demonstrate the effectiveness of the proposed method, we conduct numerical experiments on regression and classification problems involving sets, graphs, and sequences

AEPおよび脳波へのinsulin低血糖の影響

The effects of insulin-induced hypoglycemia on the central nervous system were studied by auditory evoked potential (AEP), with 8 schizophrenic patients (31~47 y.o.), during the 'kleine Insulinbehandlung'. In the three experimental session on different days, human regular insulin was injected subcutaneously to each patient, whose consciousness level was lowered to the stage of somnolence and recovered by intake of a glucose solution (100 g). EEG containig AEPs evoked by click simuli was derived from the two derivations (3rd ch : Cz→A1+2, 6th ch : Cz→T5). In the experimental session, EEG containing AEPs was recorded before and 20, 40, 60, 80, 100 and 120 min after the injection of insulin, and 20 min after intake of glucose. Consecutive changes of group mean AEP were studied. Individual AEPs were subjected to the component analysis, and to the statistical assessment together with EEG power %. As a result, the middle latency components of AEP significantly reduced in latency and significantly increased in amplitude in the early stage after the injection of insulin, but significantly prolonged in latency in the latter stage. On the other hand, the long latency components of AEP significantly prolonged in latency and significantly decreased in amplitude throughout hypoglycemia. EEG power % significantly decreased in δ power% in the early stage, but significantly increased in δ and θ power % and significantly decreased in α and β power % in the latter stage. These results were attributed to the inhibitory effects of insulin-induced hypoglycemia on the cerebral cortex, and to the activation of the noradrenergic neurons responding to the hypoglycemia in the early stage. The results also indicate that the activated noradrenergic neurons are gradually declined during prolonged hypoglycemia

The differences in VEP (Visual Evoked Potentials) between epileptics and normal subjects

The differences between epileptics and healthy subjects on the visual evoked potential (VEP) were studied. VEPs were recorded through the two derivations (2 ch : O 1→A 1+2, 5 ch : O 1→Cz). The differences in the latencies and interpeak amplitudes were compared and tested statistically, respectively for each sex, with special reference to the drugs been administered. 1. The latencies of VEP components in epileptics were longer than those in healthy subjects, in both sexes. 2. Interpeak amplitudes of VEP components in epileptics were smaller than those in healthy subjects, especially in late components, in both sexes. 3. These tendencies were more marked in males than in females. 4. In epileptics, between the subjects being administered each drug (CBZ, PB, VPA or PHT) or not, significant differences in latencies and intrerpeak amplitudes were not confirmed, with the components in which significant differences in latencies and amplitudes between epileptics and healthy subjects were found. We verified the significant differences in VEPs between epileptics and healthy subjects, which suggested the dysfunction in epileptics in its brain stem and lateral geniculate body, even not considering the seizure types nor epileptic focus sites