Information Processing Unit Research Articles

Multifunctional Logic Applications of a Single Molecule: A Molecular Photo‐Switch Performing as Simple and Complex Gates, Memory Element, and a Molecular Keypad Lock

AbstractCarbazole (CZ) can act as a photo‐switch leading to a multifunctional logic system when triggered by fluoride (F–) ions, H2O and light, through efficient interaction of the pyrrole unit with the anions. Here we are reporting a unimolecular platform of CZ (and case specific CZ‐F–) that can be configured as NOT, YES, complimentary IMPLICATION and INHIBIT, a new complex logic gate performing IF‐THEN and NOT operations and a memory element with cyclic “Erase‐Read‐Write‐Read” ability with feedback loop mechanism. The fluorescence responses of the CZ system also have been exploited to design a potential highly secured molecular keypad lock operating with a purely opto‐chemical password composed with optical and chemical input keys. The system displays the applications of light responsive molecules as multifunctional, reconfigurable molecular logic devices that may lead towards true molecular information processing units.

Neuronal Assemblies Evidence Distributed Interactions within a Tactile Discrimination Task in Rats.

Accumulating evidence suggests that neural interactions are distributed and relate to animal behavior, but many open questions remain. The neural assembly hypothesis, formulated by Hebb, states that synchronously active single neurons may transiently organize into functional neural circuits—neuronal assemblies (NAs)—and that would constitute the fundamental unit of information processing in the brain. However, the formation, vanishing, and temporal evolution of NAs are not fully understood. In particular, characterizing NAs in multiple brain regions over the course of behavioral tasks is relevant to assess the highly distributed nature of brain processing. In the context of NA characterization, active tactile discrimination tasks with rats are elucidative because they engage several cortical areas in the processing of information that are otherwise masked in passive or anesthetized scenarios. In this work, we investigate the dynamic formation of NAs within and among four different cortical regions in long-range fronto-parieto-occipital networks (primary somatosensory, primary visual, prefrontal, and posterior parietal cortices), simultaneously recorded from seven rats engaged in an active tactile discrimination task. Our results first confirm that task-related neuronal firing rate dynamics in all four regions is significantly modulated. Notably, a support vector machine decoder reveals that neural populations contain more information about the tactile stimulus than the majority of single neurons alone. Then, over the course of the task, we identify the emergence and vanishing of NAs whose participating neurons are shown to contain more information about animal behavior than randomly chosen neurons. Taken together, our results further support the role of multiple and distributed neurons as the functional unit of information processing in the brain (NA hypothesis) and their link to active animal behavior.

Development of an improved device to control flame brightness in combustion chambers of steam boilers

The study has helped create a device by developing the design of a sensor to control the fire brightness of a coal burner as well as by using the electronic circuit of an information processing unit. The proposed optical fiber transformer design provides a comparison of the brightness of adjacent areas and the total area of a separate torch, and it increases the viewing angle of the sensor up to 20 degrees. A third channel has been introduced to correct measurements, taking into account the radiation of combustion products that hinder the accuracy of the measurement. The study has determined the radiation spectrum of combustion products in the furnace and their dependence on the temperature of the flame. It has been revealed that the developed optical fiber sensor increases the area of the controlled flame, which increases the accuracy of control. The presence of a “window” in the logic source block will help adapt the device to the temperature and location of burners in the furnace. The design of the optical fiber transformer and some nodes of the electronic unit can be used in the development of serial combustion control devices for coal burners. The use of CCD matrices will help achieve future two-coordinate control of the burner flame and increase the selectivity and performance of the device

Dendritic Spines Prevent Synaptic Voltage Clamp

Synapses are the fundamental units of information processing in the mammalian brain. Much of our understanding of their functional properties comes from voltage-clamp analysis, the predominant approach for investigating synaptic physiology. Here, we reveal that voltage clamp is completely ineffective for most excitatory synapses due to spineelectrical compartmentalization. Under local dendritic voltage clamp, single-spine activation produced large spine head depolarizations that severely distorted measurements and recruited voltage-dependent channels. To overcome these voltage-clamp errors, we developed an approach to provide new, accurate measurements of synaptic conductance. Single-synapse AMPA conductance was much larger than previously appreciated, producing saturation effects on synaptic currents. We conclude that electrical compartmentalization profoundly shapes both synaptic function and how that function can be assessed with electrophysiological methods.

An ontology-aware integration of clinical models, terminologies and guidelines: an exploratory study of the Scale for the Assessment and Rating of Ataxia (SARA)

BackgroundElectronic rating scales represent an important resource for standardized data collection. However, the ability to exploit reasoning on rating scale data is still limited. The objective of this work is to facilitate the integration of the semantics required to automatically interpret collections of standardized clinical data. We developed an electronic prototype for the Scale of the Assessment and Rating of Ataxia (SARA), broadly used in neurology. In order to address the modeling challenges of the SARA, we propose to combine the best performances from OpenEHR clinical archetypes, guidelines and ontologies.MethodsA scaled-down version of the Human Phenotype Ontology (HPO) was built, extracting the terms that describe the SARA tests from free-text sources. This version of the HPO was then used as backbone to normalize the content of the SARA through clinical archetypes. The knowledge required to exploit reasoning on the SARA data was modeled as separate information-processing units interconnected via the defined archetypes. Each unit used the most appropriate technology to formally represent the required knowledge.ResultsBased on this approach, we implemented a prototype named SARA Management System, to be used for both the assessment of cerebellar syndrome and the production of a clinical synopsis. For validation purposes, we used recorded SARA data from 28 anonymous subjects affected by Spinocerebellar Ataxia Type 36 (SCA36). When comparing the performance of our prototype with that of two independent experts, weighted kappa scores ranged from 0.62 to 0.86.ConclusionsThe combination of archetypes, phenotype ontologies and electronic information-processing rules can be used to automate the extraction of relevant clinical knowledge from plain scores of rating scales. Our results reveal a substantial degree of agreement between the results achieved by an ontology-aware system and the human experts.

PLD1 promotes dendritic spine development by inhibiting ADAM10-mediated N-cadherin cleavage

Synapses are the basic units of information transmission, processing and integration in the nervous system. Dysfunction of the synaptic development has been recognized as one of the main reasons for mental dementia and psychiatric diseases such as Alzheimer’s disease and autism. However, the underlying mechanisms of the synapse formation are far from clear. Here we report that phospholipase D1 (PLD1) promotes the development of dendritic spines in hippocampal neurons. We found that overexpressing PLD1 increases both the density and the area of dendritic spines. On the contrary, loss of function of PLD1, including overexpression of the catalytically-inactive PLD1 (PLD1ci) or knocking down PLD1 by siRNAs, leads to reduction in the spine density and the spine area. Moreover, we found that PLD1 promotes the dendritic spine development via regulating the membrane level of N-cadherin. Further studies showed that the regulation of surface N-cadherin by PLD1 is related with the cleavage of N-cadherin by a member of the disintegrin and metalloprotease family-ADAM10. Taking together, our results indicate a positive role of PLD1 in synaptogenesis by inhibiting the ADAM10 mediated N-cadherin cleavage and provide new therapeutic clues for some neurological diseases.

Microstructural Control of La0.6Sr0.4Co0.2Fe0.8O3 (LSCF) Cathode by Validated Kinetic Monte Carlo Simulations

Microstructural parameters such as Triple Phase Boundary (TPB) density, specific surface area, connectivity and tortuosity of different phases strongly affect the performance of solid oxide fuel cells (SOFCs). Degradation of SOFCs is partially attributed to the coarsening of electrode during operation. The Potts Kinetic Monte Carlo (KMC) model [1], proven as a robust tool to study all stages of the sintering process, is an ideal tool to analyze the microstructural evolution of electrodes due to sintering [2]. The KMC model considers following three sintering mechanisms: (i) curvature driven grain growth by short-range atomic diffusion across the grain boundaries; (ii) pore migration by long range surface diffusion of pores; and (iii) vacancies formation at grain boundaries and annihilation along grain boundaries to cause densification. Hence, in the KMC models, the microstructures are controlled by sintering temperatures (KBT) and frequencies (f), i.e., KBTgg , f gg for grain growth, KBTpm , f pm for pore migration, and KBTvf , f vf for vacancy formation and annihilation. As these sintering parameters are not material physical properties, we firstly calibrated these parameters in the KMC model by comparing the microstructural parameters measured from the simulated 3-dimensional (3D) microstructures and the FIB-SEM reconstructed 3D microstructures of La0.6Sr0.4Co0.2Fe0.8O3 (LSCF) cathode pellet samples with different densities. The sintering parameters were calibrated using an artificial neural network (ANN) consisting of input layer (sintering material parameters), hidden layers (information processing units) and output layer (microstructural parameters). Inputs/outputs functional relationships were learned from a limited number of KMC simulations based on ‘Design of Experiment (DoE)’ based parametric studies. The trained ANN predicted more input/output pairs to form a database containing ‘material parameter-microstructural parameters’ pairs. Input sintering parameters that result in microstructural parameters within a desired error intolerance of the experimental results are called calibrated parameters. In this study, we identified input parameters as K B T gg=1.16, f gg =0.68, K B T pm =1.48, f pm =0.20, K B T vf = 37.0, and f vf=0.52 for LSCF material. These calibrated parameters were validated successfully by predicting an extra experimental data, i.e. a further densified LSCF pellet sample. By using the validated KMC simulations, we comprehensively examined the effect of the powder morphology on the microstructural characteristics of a La0.6Sr0.4Co0.2Fe0.8O3 (LSCF) cathode. A number of numerical samples consisting of packing of spheres or clumped spheres were created using a discrete element method (DEM), taking into account the morphology of powders such as particle size, particle size distribution (PSD), aspect ratio (AR), sphericity, and particle orientation. The packings were subject to quasi-static compression under tri-axial pressures until having a prescribed relative density. Then, these DEM-generated numerical structures with different particle morphology were submitted to the KMC simulations. Their effects on relative density, specific surface area, and connectivity and tortuosity factors of LSCF and pore phases were compared and analyzed. It is found in this study that using fine sized powder can improve the specific surface area and decrease the tortuosity factors of the LSCF phase. However, the decreased particle size at the same time enhances the sinterability of the LSCF, resulting in a decreased thermal stability of the LSCF cathode. The decreased particle size can also provide a decreased pore phase connectivity, which is disadvantageous for gas transport in the cathode. Secondly, a wider-PSD powder can improve the thermal stability by decreasing the sinterability of the powder. Another consequence of increasing width of PSD is that the pore phase tortuosity factor decreases, which benefits the gas transport in the cathode. The effect of the width of the PSD on the specific surface area and tortuosity factor of the LSCF phase is ignorable. Thirdly, powder with higher-AR particles has higher specific surface area and lower tortuosity factor for LSCF (better ionic and electronic conductivity). However, it also has a lower thermal stability and higher pore tortuosity factor. AR in the range of 1.0-2.0 seems has a very limited effect. Fourthly, powder with irregular shapes has better sinterability (poorer thermal stability). The tortuosity factors for LSCF and pores seems not significantly influenced in the study. Finally, in the case of elongated particles being used, alignment of particles in the green state will lead to lower sinterability of the packing, hence a better thermal stability of cathode. As a consequence of the particle alignment, anisotropic tortuosity factors for LSCF and pores have developed. In the alignment direction, the tortuosity factors appear smaller than the other orthogonal directions.

Qualitative changes in phase-response curve and synchronization at the saddle-node-loop bifurcation.

Prominent changes in neuronal dynamics have previously been attributed to a specific switch in onset bifurcation, the Bogdanov-Takens (BT) point. This study unveils another, relevant and so far underestimated transition point: the saddle-node-loop bifurcation, which can be reached by several parameters, including capacitance, leak conductance, and temperature. This bifurcation turns out to induce even more drastic changes in synchronization than the BT transition. This result arises from a direct effect of the saddle-node-loop bifurcation on the limit cycle and hence spike dynamics. In contrast, the BT bifurcation exerts its immediate influence upon the subthreshold dynamics and hence only indirectly relates to spiking. We specifically demonstrate that the saddle-node-loop bifurcation (i) ubiquitously occurs in planar neuron models with a saddle node on invariant cycle onset bifurcation, and (ii) results in a symmetry breaking of the system's phase-response curve. The latter entails an increase in synchronization range in pulse-coupled oscillators, such as neurons. The derived bifurcation structure is of interest in any system for which a relaxation limit is admissible, such as Josephson junctions and chemical oscillators.

(Invited) Synaptic Plasticity in a Memristive Device below 500mV

Neuromorphic engineering aims to develop intelligent systems by mimicking the key computational architecture of biological neural networks [1]. Neurons or nerve cells are the functional units of information processing in the brain. They are interconnected with each other via junctions called synapses to form parallel networks; it is estimated that there can be as many as ten thousand synapses per neuron in certain regions of the human brain. The plasticity of the junction conductance based on neuronal activity leads to memory, learning, and adaptation. Thus, the neuron processor together with local synaptic storage makes brain a highly parallel computing system. Human brain consumes only about 20 W, whereas the today's best supercomputers consume millions of Watts. The processing power of the brain is attributed to its parallel architecture and local learning. Implementing a scalable high connectivity network with local adaptive storage is an important step in realizing neuromorphic computing systems. Memristive devices integrated in cross-bar arrays, with neuronal circuitry in periphery, can mimic the architecture of the brain efficiently. Memristive devices show non-volatile conductance modulation which is a function of the current that has passed through it [2]. Such devices exhibit an analog hysteresis in their IV responses and has been suggested for neuromorphic engineering applications. Even though the current state of research suggests that the challenges related to reliability and repeatability have to be overcome, these devices offer significant advantages in terms of scalability and power consumption. We recently demonstrated half-integer quantized conductance in Cu/SiO2/W devices which have switching threshold less than 250mV [3]. The conductance quantization suggests the presence of nano-filaments whose effective radius was estimated to be in the range of 2-6 nm. This corresponds to the total average area involved in resistive switching; it is indeed possible that multiple filaments are active in parallel in the device. A multi-state memory device is essential for compact local storage and learning in neuromorphic engineering. However, the quantized conductance states, which are multiples of 2e2/h (G0), allow currents in the micro-ampere range for read voltages as low as 50 mV, which is large for a high-density memory array. It might be possible to engineer a selector device in series with the RRAM structure which can avoid both the sneak path problem in a cross-bar array structure and at the same time act as a series resistance to lower the read current. Hence, we explored the possibility of utilizing the off-state device conductance of our device to mimic synaptic plasticity, by programming it with waveforms that do not exceed the switching threshold for a sufficiently long time. We chose the waveforms to be approximations of neuronal actions potentials and their amplitudes are chosen to be below device switching threshold. Pre and post-synaptic waveforms were used and their different time shifted versions were applied across the device. In the actual experiment, the W electrode was grounded and the difference of two waveforms was applied to the Cu electrode. When we plotted the normalized device conductance change as a function of the time shifts, the response approximated the biologically observed STDP behavior. The observed behavior might be the result of partial filament formation and metal ion doping of SiO2. Similar gradual conductance change behavior has been observed earlier in oxide based RRAMs [4], which operates at higher voltages than our device. The programming waveform we used has a peak amplitude of 0.5V during the maximum conductance change. The bio-mimetic behavior we demonstrated here from a two terminal, low voltage, CMOS-technology compatible device structure takes us closer to the goal of builind an intelligent system at the energy budget of the human brain. The reduction in programming voltage amplitude can result in significant energy savings in large array implementations which is vital to bio-inspired computing platforms.

Decoding Network Structure in On-Chip Integrated Flow Cells with Synchronization of Electrochemical Oscillators

The analysis of network interactions among dynamical units and the impact of the coupling on self-organized structures is a challenging task with implications in many biological and engineered systems. We explore the coupling topology that arises through the potential drops in a flow channel in a lab-on-chip device that accommodates chemical reactions on electrode arrays. The networks are revealed by analysis of the synchronization patterns with the use of an oscillatory chemical reaction (nickel electrodissolution) and are further confirmed by direct decoding using phase model analysis. In dual electrode configuration, a variety coupling schemes, (uni- or bidirectional positive or negative) were identified depending on the relative placement of the reference and counter electrodes (e.g., placed at the same or the opposite ends of the flow channel). With three electrodes, the network consists of a superposition of a localized (upstream) and global (all-to-all) coupling. With six electrodes, the unique, position dependent coupling topology resulted spatially organized partial synchronization such that there was a synchrony gradient along the quasi-one-dimensional spatial coordinate. The networked, electrode potential (current) spike generating electrochemical reactions hold potential for construction of an in-situ information processing unit to be used in electrochemical devices in sensors and batteries.

Cell assemblies at multiple time scales with arbitrary lag constellations.

Hebb's idea of a cell assembly as the fundamental unit of neural information processing has dominated neuroscience like no other theoretical concept within the past 60 years. A range of different physiological phenomena, from precisely synchronized spiking to broadly simultaneous rate increases, has been subsumed under this term. Yet progress in this area is hampered by the lack of statistical tools that would enable to extract assemblies with arbitrary constellations of time lags, and at multiple temporal scales, partly due to the severe computational burden. Here we present such a unifying methodological and conceptual framework which detects assembly structure at many different time scales, levels of precision, and with arbitrary internal organization. Applying this methodology to multiple single unit recordings from various cortical areas, we find that there is no universal cortical coding scheme, but that assembly structure and precision significantly depends on the brain area recorded and ongoing task demands.

Trigger control characteristics of fuze-recoil simulation system based on electromagnetic launcher

Fuze is the information processing and control unit of the ammunition, so the quality of the fuze becomes one of the most important aspects of ammunition detection. Since using recoil force is a common method to the arm fuze, its dynamic simulation test has always been the focus of the fuze test research. A new fuze recoil environmental simulation method is proposed based on the electromagnetic launcher. Then the trigger control characteristics of the fuze recoil simulation system and the influence of the trigger position on the recoil force are studied. The results of the study show that although the pulse width of the armature force curve can be changed by adjusting the trigger position, due to the limit of the range, there also exists the contradiction that the electromagnetic pulse width gets narrow with the increase of electromagnetic force peak. Thus, it cannot meet the requirements of the fuze launch recoil simulation. In order to make the recoil force close to the actual environment, the multi-stage trigger control characteristics are analyzed, and the influence of trigger position on recoil environmental force characteristics is studied. Then a fuze launch recoil environmental simulation platform is established and continuous electromagnetic force is achieved by using the trigger strategy. Finally, the experiment is performed to simulate the fuze launch recoil environment and show the feasibility and effectiveness of the proposed theoretical analysis. The major research work of this paper includes studying the composition and basic principle of the simulation system, establishing a launch model to analyze the single-stage and multi-stage coil fuze launch recoil characteristics, designing the test device to verify the correctness and validity of the research. This paper draws the conclusions that the feasibility of the fuze launch environmental simulation based on the electromagnetic launcher is verified, the trigger position has a great influence on force peak continuity, the problems of low maximum overload peak and short peak duration in the multi-stage coil fuze launch environmental simulation can be effectively solved through adjusting the trigger position, the system has creative and extensive application prospects.

Corn starch solid electrolyte gated proton/electron hybrid synaptic transistor

A human brain is a high-density neural network, which has~1011 neurons and~1015 synapses. Neuron as a basic information processing unit builds the biological neural network, and the realization of information transmission and integration depends on the synaptic connection between neurons. This information transfer and integration work is difficult to realize by relying on von Neumann computer, due to the computer only works according to the well-defined programs. To further simulate the imagery thinking of human brain neural network, the researchers begin with the information memory and processing mechanism of human brain neural network. A large number of microelectronic devices with human thinking characteristics are designed, such as memristor, atomic switch, phase change memory, and transistors. The oxide-based thin film transistor under the new material system is one of these devices, and has attracted the attention of researchers. The transistors working as the biological synapses, the gate electrode is regard as presynaptic input terminal, and the channel current is measured as postsynaptic output. Utilizing the proton gating behaviors, a series of synaptic behaviors, such as short-term and long-term memory, paired-pulse facilitation, and spike timing-dependent plasticity is mimicked successfully in these synaptic transistors.#br#With the progressing of science and technology, and the increasing of requirements for environmental protection, researchers pay more attention to the environmentally friendly solid electrolyte materials to fabricate oxide-based thin film synaptic transistor. Researchers have a major interest in starch, due to the low price, rich source, and excellent mechanical properties. Starch can be extracted from corn, potato, sweet potato and other starch-containing substances, and is generally insoluble in cold water, and gelatinized in boiling water. In this study, corn starch solid electrolyte is prepared on ITO glass by spin coating progress, and dried at a constant temperature at 30℃. The electrical performances of protonic/electronic hybrid IZO synaptic transistor gated by corn starch solid electrolyte are excellent, operation voltage, Ion/off ratio, field-effect mobility and subthreshold swing are 1.5 V, 1×107, 18.7 cm2·V-1·s-1 and 156.8 mV/dec., respectively. Due to the mobile proton migrating in corn starch solid electrolyte, the paired-pulse facilitation, learning and memory behaviors and high-pass filter of biological neural synaptic plasticity are realized successfully. The synaptic transistors have potential applications in the field of environment-friendly microelectronic devices to reduce the production costs. Therefore, the corn starch solid electrolyte gated proton/electron hybrid synaptic transistor as an artificial synapse can offer a suitable option to building the neural network.

Dysregulation of Corticostriatal Connectivity in Huntington's Disease: ARole for Dopamine Modulation.

Aberrant communication between striatum, the main information processing unit of the basal ganglia, and cerebral cortex plays a critical role in the emergence of Huntington’s disease (HD), a fatal monogenetic condition that typically strikes in the prime of life. Although both striatum and cortex undergo substantial cell loss over the course of HD, corticostriatal circuits become dysfunctional long before neurons die. Understanding the dysfunction is key to developing effective strategies for treating a progressively worsening triad of motor, cognitive, and psychiatric symptoms. Cortical output neurons drive striatal activity through the release of glutamate, an excitatory amino acid. Striatal outputs, in turn, release γ-amino butyric acid (GABA) and exert inhibitory control over downstream basal ganglia targets. Ample evidence from transgenic rodent models points to dysregulation of corticostriatal glutamate transmission along with corresponding changes in striatal GABA release as underlying factors in the HD behavioral phenotype. Another contributor is dysregulation of dopamine (DA), a modulator of both glutamate and GABA transmission. In fact, pharmacological manipulation of DA is the only currently available treatment for HD symptoms. Here, we review data from animal models and human patients to evaluate the role of DA in HD, including DA interactions with glutamate and GABA within the context of dysfunctional corticostriatal circuitry.

Yeşil Bilişim: Bir Kamu Kurumu Örneği Ve Politika Önerileri

Climate change and global warming is one of the most important environmental problems that mankind faces today. Our world today faces negative effects caused by global warming and global climate change more intensely. If our natural resources are consumed as it is today, it is estimated that our planet will not suffice in the mid and long run. That’s why taking necessary measures, changing our way of doing our work and minimizing our negative effects of ours to nature have been important elements. At this point, information technologies emerge as a key element in solving this crucial problem. Information and communication technologies now emerge as fighting tools against environmental threats like global warming, climate change and industrial waste. In Turkey, public institutions have a significant potential from the point of view of energy consumption, purchase of technological products, their usage and the improving the processes. This study aims at handling the public information processing units’ information processing with green IT approach and making suggestions. In this study, the inventory of the information systems, technology and infrastructure that a sample public information processing units has will be taken. The likely environmental impact of the inventory of the prevalent element will be evaluated in a systematic way. Samples from Turkey and the world will be discussed according to the following subjects such as green computing perception, green computing policy in the organization, purchasing of communication technology tools, recycling, rational design of the laboratories, energy consumption, virtualization of projects, server room preferences and their location, green university, and what can be done about green organizations. This study is thought to be important from the point of view of handling green computing considering the factors mentioned above and increasing the personal and organizational awareness

On-chip broadband ultra-compact optical couplers and polarization splitters based on off-centered and non-symmetric slotted Si-wire waveguides

In this work, we propose novel schemes to design on-chip ultra-compact optical directional couplers (DC) and broadband polarization beam splitters (PBS) based on off-centered and asymmetric dielectric slot waveguides, respectively. Slot dimensions and positions are optimized to achieve maximum coupling coefficients between two symmetric and non-symmetric slotted Si wire waveguides through overlap integral method. We observe >88% of enhancement in the coupling coefficients when the size-optimized slots are placed in optimal positions, with respect to the same waveguides with no slot. When the waveguides are parallel, in that case, a coupling length as short as 1.73 μm is accomplished for TM mode with the off-centered and optimized slots. This scheme enables us to design optical DC with very small footprint, Lc ∼ 0.9 μm in the presence of S-bends. We also report a compact (Lc ∼ 1.1 μm) on-chip broadband PBS with hybrid slots. Extinction ratios of 13 dB and 22.3 dB are realized with very low insertion loss (0.055 dB and 0.008 dB) for TM and TE modes at 1.55 μm, respectively. The designed PBS exhibits a bandwidth of 78 nm for the TM mode (C-and partial L-bands) and >100 nm for the TE mode (S + C + L wavelength bands). Such on-chip devices can be used to design compact photonic interconnects and quantum information processing units efficiently. We have also investigated the fabrication tolerances of the proposed devices and described the fabrication steps to realize such hybrid devices. Our results are in good agreement with 3D FDTD simulations.

Recognizing Parameters of the Information Security Unit Implemented by the Threshold K-Valued Function

This article discusses some approaches to the recognition of the parameters of the threshold k-valued functions, which can be used for building information processing and security units. The main focus is put on the issue of proving k-valued function belonging to the threshold class. For solving this problem it is proposed to use the input coefficients of expansion and increase. With the help of the latter, the coefficients of linear forms of the k-valued threshold function are procedurally approximated. Along with the proposed analytical approach, the article discusses an algorithmic method based on reducing the problem of finding a threshold representation of k-valued functions to the system of linear inequalities, for the solution of which the ellipsoid method, modified by Khachiyan, is applied. The comparative analysis of the proposed methods is carried out based on experiments.

Canonical correlations reveal co-variability between spike trains and local field potentials in area MT)

Patterns of neuronal correlations can provide important clues about the structure of the underlying network and how it processes information. Several recent studies have found that neural population activity across a region can be explained in large part by a shared, low-dimensional signal [1-5]. Population-wide correlation is likely to influence the local field potential (LFP) - an epiphenomenon that reflects low-frequency, concerted neural activity from anatomically connected circuits. Here, we show that LFP and spike trains recorded simultaneously from the middle temporal (MT) area of the awake macaque indeed share population-wide correlation. We apply canonical correlation analysis (CCA) to 16 channels of LFP and 16 spike sorted neurons (from 12 channels) acquired at 50 ms temporal resolution during inter-trial intervals (when the monkey was free to make eye movements), as well as during performance of a perceptual decision-making task (when the monkey maintained fixation and discriminated the direction of visual motion). CCA finds instantaneous linear projections of the LFP that maximize the correlation to corresponding projections of the population spike trains. Previous studies have suggested using population spike rate as a proxy for the local network state [3,5]. Applied to our dataset, we obtain a correlation coefficient of -12% between population spike rate and the mean LFP during inter-trial interval segments. In contrast, we obtain pairs of canonical variables with corresponding canonical correlations 29%, 26%, and 21%. We then applied the extracted projections to the task-relevant motion stimulus integration window. We find that the correlation of the projections is maintained for the 1st (31%) and 3rd (18%) components, but drops significantly for the 2nd component (7%)-- indicating a task-specific decoupling of LFP and spikes in a subspace uncovered by CCA. Upon further analysis, each CCA projection showed a distinct stimulus encoding pattern in spike rate and LFP. We hypothesize that CCA projections reveal functional, virtual units of information processing. The LFP is an important source of information when neural activity is correlated. It can indicate the strength of correlations, and the common input giving rise to such correlations. Additionally, the LFP provides increased statistical power to analyses, especially in areas where large-scale recording is anatomically difficult. CCA is a simple technique that can reveal low-dimensional structure in the data, uncovering components which maximize covariability between LFP and spike trains within MT.

Microtubule Dynamics in Neuronal Development, Plasticity, and Neurodegeneration.

Neurons are the basic information-processing units of the nervous system. In fulfilling their task, they establish a structural polarity with an axon that can be over a meter long and dendrites with a complex arbor, which can harbor ten-thousands of spines. Microtubules and their associated proteins play important roles during the development of neuronal morphology, the plasticity of neurons, and neurodegenerative processes. They are dynamic structures, which can quickly adapt to changes in the environment and establish a structural scaffold with high local variations in composition and stability. This review presents a comprehensive overview about the role of microtubules and their dynamic behavior during the formation and maturation of processes and spines in the healthy brain, during aging and under neurodegenerative conditions. The review ends with a discussion of microtubule-targeted therapies as a perspective for the supportive treatment of neurodegenerative disorders.

A Study on the Object of the Fraud by Use of Computer

The Criminal Law of South Korea has needed to cope with new kinds of crimes such as the fraud by use of computer efficiently in a legislative way because the society has witnessed the rapid progress of the industrialization and informatization after established in 1953. As a result, the Criminal Law revised on December 29, 1995, created the regulations of the crimes related to fraud by use of computer, work disturbance, and secret piracy by using information processing units. The regulation stipulated in Clause 347, Article 2 of Criminal Law is the most typical one against the new crimes. However, the new regulation of fraud by use of computer, established and revised to supplement the lacking parts of the current rules of the punishment of fraud, limits its object to “any benefits to property.” not to “property” itself, and so cannot achieve the purpose of the revision of the law. This paper aims to suggest a new legislative measure about the object of the regulation of fraud by use of computer to solve this kind of problem efficiently.