Optical design of multilayer antireflection coatings for indoor solar cell applications.

Multilayer antireflection coatings (ARCs) for solar cells are conventionally designed to enhance the photocurrent level obtained at normal incidence. This is mainly because outdoor solar panels are usually placed such that they can receive strong midday sunlight at a nearly vertical angle. However, in the case of indoor photovoltaic devices, the direction of light changes considerably with changes in the relative position and angle between the device and light sources; therefore, it is often difficult to predict the incident angle. In this study, we explore a method to design ARCs suitable for indoor photovoltaics by essentially taking into account the indoor lighting environment, which is different from the outdoor conditions. We propose an optimization-based design strategy that aims to enhance the average level of the photocurrent generated when a solar cell receives irradiance randomly from all directions. We apply the proposed method to design an ARC for organic photovoltaics, which are expected to be promising indoor devices, and numerically compare the resultant performance with that obtained using a conventional design method. The results demonstrate that our design strategy is effective for achieving excellent omnidirectional antireflection performance and allows the realization of practical and efficient ARCs for indoor devices.

Oxygen vacancy mediated room-temperature ferromagnetism and band gap narrowing in DyFe0.5Cr0.5O3 nanoparticles.

We report on the magnetic and optical properties of DyFe0.5Cr0.5O3 nanoparticles synthesized by a sol-gel method. Rietveld refinement of a powder X-ray diffraction (XRD) pattern confirms the formation of an orthorhombic disordered phase with the Pnma space group. The formation of nano-sized particles, with an average size of 42(±12) nm, was approximated by the transmission electron microscopy (TEM) image analysis. X-ray photoelectron spectroscopy (XPS) of this compound reveals the presence of Fe2+/Fe3+ and Cr2+/Cr3+ mixed-valence states as a consequence of oxygen vacancies present at the surface of nanoparticles. The temperature-dependent magnetization (M-T) shows a finite non-zero magnetization up to 300 K and the field-dependent magnetization (M-H) curve exhibits a weak ferromagnetic (WFM) nature at 300 K with a clear hysteresis loop, which is quite appealing compared to that of the previously reported micron-sized DyFe0.5Cr0.5O3. These observations indicate that the large concentration of uncompensated surface spin of nanoparticles could be responsible for the observed room-temperature ferromagnetism. Moreover, DyFe0.5Cr0.5O3 nanoparticles show a significantly narrow band gap (Eg ∼ 2.0 eV). Meanwhile, the oxygen vacancies may generate shallow trap energy levels within the band gap as observed from photoluminescence (PL) spectroscopy. The observed band gap narrowing by Fe doping and the effect of oxygen vacancies on the band gap are consistent with the predictions of density functional theory (DFT) calculations. The evidence of room-temperature ferromagnetism in DyFe0.5Cr0.5O3 nanoparticles compared to their bulk counterparts and the significantly narrow band gap in the visible range manifest the potential of this material in spintronic and optical applications.

Mean-field analysis of directed modular networks.

We considered a modular network with a binomial degree distribution and related the analytical relationships of the network properties (modularity, average clustering coefficient, and small-worldness) with structural parameters that define the network, i.e., number of nodes, number of modules, average node degree, and ratio of intra-modular to total connections. Even though modular networks are universally found in real-world systems and are consequently of broad interest in complex network science, the relationship between network properties and structural parameters has not yet been formulated. Here, we show that a series of equations for predicting the network properties can be related using a mean-field connectivity matrix that is defined on the basis of the structural parameters in the network generation algorithm. The theoretical results are then compared with values calculated numerically using the original connectivity matrix and are found to agree well, except when the connections between modules are sparse. Representation of the structure of the network using simple parameters is expected to be conducive for elucidating the structure-dynamics relationship.

Impact of modular organization on dynamical richness in cortical networks.

As in many naturally formed networks, the brain exhibits an inherent modular architecture that is the basis of its rich operability, robustness, and integration-segregation capacity. However, the mechanisms that allow spatially segregated neuronal assemblies to swiftly change from localized to global activity remain unclear. Here, we integrate microfabrication technology with in vitro cortical networks to investigate the dynamical repertoire and functional traits of four interconnected neuronal modules. We show that the coupling among modules is central. The highest dynamical richness of the network emerges at a critical connectivity at the verge of physical disconnection. Stronger coupling leads to a persistently coherent activity among the modules, while weaker coupling precipitates the activity to be localized solely within the modules. An in silico modeling of the experiments reveals that the advent of coherence is mediated by a trade-off between connectivity and subquorum firing, a mechanism flexible enough to allow for the coexistence of both segregated and integrated activities. Our results unveil a new functional advantage of modular organization in complex networks of nonlinear units.

Numerical optimization of coordinated reset stimulation for desynchronizing neuronal network dynamics.

Excessive synchronization in neural activity is a hallmark of Parkinson's disease (PD). A promising technique for treating PD is coordinated reset (CR) neuromodulation in which a neural population is desynchronized by the delivery of spatially-distributed current stimuli using multiple electrodes. In this study, we perform numerical optimization to find the energy-optimal current waveform for desynchronizing neuronal network with CR stimulation, by proposing and applying a new optimization method based on the direct search algorithm. In the proposed optimization method, the stimulating current is described as a Fourier series, and each Fourier coefficient as well as the stimulation period are directly optimized by evaluating the order parameter, which quantifies the synchrony level, from network simulation. This direct optimization scheme has an advantage that arbitrary changes in the dynamical properties of the network can be taken into account in the search process. By harnessing this advantage, we demonstrate the significant influence of externally applied oscillatory inputs and non-random network topology on the efficacy of CR modulation. Our results suggest that the effectiveness of brain stimulation for desynchronization may depend on various factors modulating the dynamics of the target network. We also discuss the possible relevance of the results to the efficacy of the stimulation in PD treatment.

Effective Subnetwork Topology for Synchronizing Interconnected Networks of Coupled Phase Oscillators.

A system consisting of interconnected networks, or a network of networks (NoN), appears diversely in many real-world systems, including the brain. In this study, we consider NoNs consisting of heterogeneous phase oscillators and investigate how the topology of subnetworks affects the global synchrony of the network. The degree of synchrony and the effect of subnetwork topology are evaluated based on the Kuramoto order parameter and the minimum coupling strength necessary for the order parameter to exceed a threshold value, respectively. In contrast to an isolated network in which random connectivity is favorable for achieving synchrony, NoNs synchronize with weaker interconnections when the degree distribution of subnetworks is heterogeneous, suggesting the major role of the high-degree nodes. We also investigate a case in which subnetworks with different average natural frequencies are coupled to show that direct coupling of subnetworks with the largest variation is effective for synchronizing the whole system. In real-world NoNs like the brain, the balance of synchrony and asynchrony is critical for its function at various spatial resolutions. Our work provides novel insights into the topological basis of coordinated dynamics in such networks.

Size-dependent regulation of synchronized activity in living neuronal networks.

We study the effect of network size on synchronized activity in living neuronal networks. Dissociated cortical neurons form synaptic connections in culture and generate synchronized spontaneous activity within 10 days in vitro. Using micropatterned surfaces to extrinsically control the size of neuronal networks, we show that synchronized activity can emerge in a network as small as 12 cells. Furthermore, a detailed comparison of small (∼20 cells), medium (∼100 cells), and large (∼400 cells) networks reveal that synchronized activity becomes destabilized in the small networks. A computational modeling of neural activity is then employed to explore the underlying mechanism responsible for the size effect. We find that the generation and maintenance of the synchronized activity can be minimally described by: (1) the stochastic firing of each neuron in the network, (2) enhancement in the network activity in a positive feedback loop of excitatory synapses, and (3) Ca-dependent suppression of bursting activity. The model further shows that the decrease in total synaptic input to a neuron that drives the positive feedback amplification of correlated activity is a key factor underlying the destabilization of synchrony in smaller networks. Spontaneous neural activity plays a critical role in cortical information processing, and our work constructively clarifies an aspect of the structural basis behind this.

NMDA-induced burst firing in a model subthalamic nucleus neuron.

Experiments in rat brain slice show that hyperpolarized subthalamic nucleus (STN) neurons engage in slow, regular burst firing when treated with an N-methyl-d-aspartate (NMDA) bath. A depolarization-activated inward current (DIC) has been hypothesized to contribute to this bursting activity. To explore the mechanism for STN burst firing in this setting, we augmented a previously published conductance-based computational model for single rat STN neurons to include both DIC and NMDA currents, fit to data from published electrophysiological recordings. Simulations show that with these additions, the model engages in bursting activity at <1 Hz in response to hyperpolarizing current injection and that this bursting exhibits several features observed experimentally in STN. Furthermore, a reduced model is used to show that the combination of NMDA and DIC currents, but not either alone, suffices to generate oscillations under hyperpolarizing current injection. STN neurons show enhanced burstiness in Parkinson's disease patients and experimental models of parkinsonism, and the burst mechanism studied presently could contribute to this effect.

Possible role of cooperative action of NMDA receptor and GABA function in developmental plasticity.

The maturation of cortical circuits is strongly influenced by sensory experience during a restricted critical period. The developmental alteration in the subunit composition of NMDA receptors (NMDARs) has been suggested to be involved in regulating the timing of such plasticity. However, this hypothesis does not explain the evidence that enhancing GABA inhibition triggers a critical period in the visual cortex. Here, to investigate how the NMDAR and GABA functions influence synaptic organization, we examine an spike-timing-dependent plasticity (STDP) model that incorporates the dynamic modulation of LTP, associated with the activity- and subunit-dependent desensitization of NMDARs, as well as the background inhibition by GABA. We show that the competitive interaction between correlated input groups, required for experience-dependent synaptic modifications, may emerge when both the NMDAR subunit expression and GABA inhibition reach a sufficiently mature state. This may suggest that the cooperative action of these two developmental mechanisms can contribute to embedding the spatiotemporal structure of input spikes in synaptic patterns and providing the trigger for experience-dependent cortical plasticity.

Modulation of LTP/LTD balance in STDP by an activity-dependent feedback mechanism.

Spike-timing-dependent plasticity (STDP) has been suggested to play a role in the development of functional neuronal connections. However, for STDP to contribute to the synaptic organization, its learning curve should satisfy a requirement that the magnitude of long-term potentiation (LTP) is approximately the same as that of long-term depression (LTD). Without such balance between LTP and LTD, all the synapses are potentiated toward the upper limit or depressed toward the lower limit. Therefore, in this study, we explore the mechanisms by which the LTP/LTD balance in STDP can be modulated adequately. We examine a plasticity model that incorporates an activity-dependent feedback (ADFB) mechanism, wherein LTP induction is suppressed by higher postsynaptic activity. In this model, strengthening an ADFB function gradually decreases the temporal average of the ratio of the magnitude of LTP to that of LTD, whereas enhancing background inhibition augments this ratio. Additionally, correlated inputs can be strengthened or weakened depending on whether the correlation time is shorter or longer than a threshold value, respectively, suggesting that STDP may lead to either Hebbian or anti-Hebbian plasticity outcomes. At an intermediate range of correlation times, the reversal between the two distinct plasticity regimes can occur by changing the level of ADFB modulation and inhibition, providing a physiological mechanism for neurons to select from functionally different forms of learning rules.

A model for synaptic development regulated by NMDA receptor subunit expression.

Activation of NMDA receptors (NMDARs) is highly involved in the potentiation and depression of synaptic transmission. NMDARs comprise NR1 and NR2B subunits in the neonatal forebrain, while the expression of NR2A subunit is increased over time, leading to shortening of NMDAR-mediated synaptic currents. It has been suggested that the developmental switch in the NMDAR subunit composition regulates synaptic plasticity, but its physiological role remains unclear. In this study, we examine the effects of the NMDAR subunit switch on the spike-timing-dependent plasticity and the synaptic weight dynamics and demonstrate that the subunit switch contributes to inducing two consecutive processes-the potentiation of weak synapses and the induction of the competition between them-at an adequately rapid rate. Regulation of NMDAR subunit expression can be considered as a mechanism that promotes rapid and stable growth of immature synapses.

Stochastic resonance of localized activity driven by common noise.

We study the influence of spatially correlated noise on the transient dynamics of a recurrent network with Mexican-Hat-type connectivity. We derive the closed form of the order parameter functional in the thermodynamical limit of neuron number N. Our analysis shows that network dynamics is qualitatively changed by the presence of common noise. Network dynamics driven by common noise obtains the global level of fluctuation, which is not observed in a network driven by independent noise only. We show that the optimal level of global fluctuation enhances the transition from non-localized firing states to spatially localized firing states, and also enhances the rotation speed of localized activity.

[Usefulness of patient education and quality of life (QOL) evaluation in asthma patients].

Achieving successful treatment of bronchial asthma depends on its control by the patient. We implemented a program of educating asthma patients and conducted a QOL survey to objectively evaluate the patients'conditions. Thirty-nine asthma patients who were receiving treatment with an inhaled corticosteroid [beclomethasone dipropionate (BDP) ] on an outpatient basis at our hospital, received instructions on proper drug administration in cooperation with the Pharmacy department of our hospital. The QOL survey (SF-36 and Marks et al. AQLQ) was conducted at the initial education session and again two months later. Thirty-two patients (82.0%) responded that they would like to continue to receive instructions on the administration of drugs. Significant improvements in Social, Concerns, Marks, and Scales were observed after the education. In addition, even those patients who stated that they did not want to receive instructions showed significant improvements in their QOL scores. The usefulness of patient education can be assessed by the change in the patients' QOL scores.