Selective suppression of high-order harmonics within phase-matched spectral regions.

PubMed

Lerner, Gavriel; Diskin, Tzvi; Neufeld, Ofer; Kfir, Ofer; Cohen, Oren

2017-04-01

Phase matching in high-harmonic generation leads to enhancement of multiple harmonics. It is sometimes desired to control the spectral structure within the phase-matched spectral region. We propose a scheme for selective suppression of high-order harmonics within the phase-matched spectral region while weakly influencing the other harmonics. The method is based on addition of phase-mismatched segments within a phase-matched medium. We demonstrate the method numerically in two examples. First, we show that one phase-mismatched segment can significantly suppress harmonic orders 9, 15, and 21. Second, we show that two phase-mismatched segments can efficiently suppress circularly polarized harmonics with one helicity over the other when driven by a bi-circular field. The new method may be useful for various applications, including the generation of highly helical bright attosecond pulses.

Suppressing disease spreading by using information diffusion on multiplex networks.

PubMed

Wang, Wei; Liu, Quan-Hui; Cai, Shi-Min; Tang, Ming; Braunstein, Lidia A; Stanley, H Eugene

2016-07-06

Although there is always an interplay between the dynamics of information diffusion and disease spreading, the empirical research on the systemic coevolution mechanisms connecting these two spreading dynamics is still lacking. Here we investigate the coevolution mechanisms and dynamics between information and disease spreading by utilizing real data and a proposed spreading model on multiplex network. Our empirical analysis finds asymmetrical interactions between the information and disease spreading dynamics. Our results obtained from both the theoretical framework and extensive stochastic numerical simulations suggest that an information outbreak can be triggered in a communication network by its own spreading dynamics or by a disease outbreak on a contact network, but that the disease threshold is not affected by information spreading. Our key finding is that there is an optimal information transmission rate that markedly suppresses the disease spreading. We find that the time evolution of the dynamics in the proposed model qualitatively agrees with the real-world spreading processes at the optimal information transmission rate.

Focal Suppression of Distractor Sounds by Selective Attention in Auditory Cortex.

PubMed

Schwartz, Zachary P; David, Stephen V

2018-01-01

Auditory selective attention is required for parsing crowded acoustic environments, but cortical systems mediating the influence of behavioral state on auditory perception are not well characterized. Previous neurophysiological studies suggest that attention produces a general enhancement of neural responses to important target sounds versus irrelevant distractors. However, behavioral studies suggest that in the presence of masking noise, attention provides a focal suppression of distractors that compete with targets. Here, we compared effects of attention on cortical responses to masking versus non-masking distractors, controlling for effects of listening effort and general task engagement. We recorded single-unit activity from primary auditory cortex (A1) of ferrets during behavior and found that selective attention decreased responses to distractors masking targets in the same spectral band, compared with spectrally distinct distractors. This suppression enhanced neural target detection thresholds, suggesting that limited attention resources serve to focally suppress responses to distractors that interfere with target detection. Changing effort by manipulating target salience consistently modulated spontaneous but not evoked activity. Task engagement and changing effort tended to affect the same neurons, while attention affected an independent population, suggesting that distinct feedback circuits mediate effects of attention and effort in A1. © The Author 2017. Published by Oxford University Press.

Optogenetic activation of superior colliculus neurons suppresses seizures originating in diverse brain networks

PubMed Central

Soper, Colin; Wicker, Evan; Kulick, Catherine V.; N’Gouemo, Prosper; Forcelli, Patrick A.

2016-01-01

Because sites of seizure origin may be unknown or multifocal, identifying targets from which activation can suppress seizures originating in diverse networks is essential. We evaluated the ability of optogenetic activation of the deep/intermediate layers of the superior colliculus (DLSC) to fill this role. Optogenetic activation of DLSC suppressed behavioral and electrographic seizures in the pentylenetetrazole (forebrain+brainstem seizures) and Area Tempestas (forebrain/complex partial seizures) models; this effect was specific to activation of DLSC, and not neighboring structures. DLSC activation likewise attenuated seizures evoked by gamma butyrolactone (thalamocortical/absence seizures), or acoustic stimulation of genetically epilepsy prone rates (brainstem seizures). Anticonvulsant effects were seen with stimulation frequencies as low as 5 Hz. Unlike previous applications of optogenetics for the control of seizures, activation of DLSC exerted broad-spectrum anticonvulsant actions, attenuating seizures originating in diverse and distal brain networks. These data indicate that DLSC is a promising target for optogenetic control of epilepsy. PMID:26721319

Optogenetic activation of superior colliculus neurons suppresses seizures originating in diverse brain networks.

PubMed

Soper, Colin; Wicker, Evan; Kulick, Catherine V; N'Gouemo, Prosper; Forcelli, Patrick A

2016-03-01

Because sites of seizure origin may be unknown or multifocal, identifying targets from which activation can suppress seizures originating in diverse networks is essential. We evaluated the ability of optogenetic activation of the deep/intermediate layers of the superior colliculus (DLSC) to fill this role. Optogenetic activation of DLSC suppressed behavioral and electrographic seizures in the pentylenetetrazole (forebrain+brainstem seizures) and Area Tempestas (forebrain/complex partial seizures) models; this effect was specific to activation of DLSC, and not neighboring structures. DLSC activation likewise attenuated seizures evoked by gamma butyrolactone (thalamocortical/absence seizures), or acoustic stimulation of genetically epilepsy prone rates (brainstem seizures). Anticonvulsant effects were seen with stimulation frequencies as low as 5 Hz. Unlike previous applications of optogenetics for the control of seizures, activation of DLSC exerted broad-spectrum anticonvulsant actions, attenuating seizures originating in diverse and distal brain networks. These data indicate that DLSC is a promising target for optogenetic control of epilepsy. Copyright © 2015 Elsevier Inc. All rights reserved.

A fuzzy neural network sliding mode controller for vibration suppression in robotically assisted minimally invasive surgery.

PubMed

Sang, Hongqiang; Yang, Chenghao; Liu, Fen; Yun, Jintian; Jin, Guoguang

2016-12-01

It is very important for robotically assisted minimally invasive surgery to achieve a high-precision and smooth motion control. However, the surgical instrument tip will exhibit vibration caused by nonlinear friction and unmodeled dynamics, especially when the surgical robot system is attempting low-speed, fine motion. A fuzzy neural network sliding mode controller (FNNSMC) is proposed to suppress vibration of the surgical robotic system. Nonlinear friction and modeling uncertainties are compensated by a Stribeck model, a radial basis function (RBF) neural network and a fuzzy system, respectively. Simulations and experiments were performed on a 3 degree-of-freedom (DOF) minimally invasive surgical robot. The results demonstrate that the FNNSMC is effective and can suppress vibrations at the surgical instrument tip. The proposed FNNSMC can provide a robust performance and suppress the vibrations at the surgical instrument tip, which can enhance the quality and security of surgical procedures. Copyright © 2016 John Wiley & Sons, Ltd.

Does modulation of selective attention to features reflect enhancement or suppression of neural activity?

PubMed

Daffner, Kirk R; Zhuravleva, Tatyana Y; Sun, Xue; Tarbi, Elise C; Haring, Anna E; Rentz, Dorene M; Holcomb, Phillip J

2012-02-01

Numerous studies have demonstrated that selective attention to color is associated with a larger neural response under attend than ignore conditions, but have not addressed whether this difference reflects enhanced activity under attend or suppressed activity under ignore. In this study, a color-neutral condition was included, which presented stimuli physically identical to those under attend and ignore conditions, but in which color was not task relevant. Attention to color did not modulate the early sensory-evoked P1 and N1 components. Traditional ERP markers of early selection (the anterior Selection Positivity and posterior Selection Negativity) did not differ between the attend and neutral conditions, arguing against a mechanism of enhanced activity. However, there were markedly reduced responses under the ignore relative to the neutral condition, consistent with the view that early selection mechanisms reflect suppression of neural activity under the ignore condition. Copyright © 2011 Elsevier B.V. All rights reserved.

Amplification or suppression: Social networks and the climate change-migration association in rural Mexico.

PubMed

Nawrotzki, Raphael J; Riosmena, Fernando; Hunter, Lori M; Runfola, Daniel M

2015-11-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks - the ties connecting an origin and destination - may operate as "migration corridors" with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying , social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.

Top-down enhancement and suppression of activity in category-selective extrastriate cortex from an act of reflective attention.

PubMed

Johnson, Matthew R; Johnson, Marcia K

2009-12-01

Recent research has demonstrated top-down attentional modulation of activity in extrastriate category-selective visual areas while stimuli are in view (perceptual attention) and after they are removed from view (reflective attention). Perceptual attention is capable of both enhancing and suppressing activity in category-selective areas relative to a passive viewing baseline. In this study, we demonstrate that a brief, simple act of reflective attention ("refreshing") is also capable of both enhancing and suppressing activity in some scene-selective areas (the parahippocampal place area [PPA]) but not others (refreshing resulted in enhancement but not in suppression in the middle occipital gyrus [MOG]). This suggests that different category-selective extrastriate areas preferring the same class of stimuli may contribute differentially to reflective processing of one's internal representations of such stimuli.

Top-down suppression of incompatible motor activations during response selection under conflict.

PubMed

Klein, Pierre-Alexandre; Petitjean, Charlotte; Olivier, Etienne; Duque, Julie

2014-02-01

Top-down control is critical to select goal-directed actions in changeable environments, particularly when several options compete for selection. This control system is thought to involve a mechanism that suppresses activation of unwanted response representations. We tested this hypothesis, in humans, by measuring motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) in a left finger muscle during motor preparation in an adapted Eriksen flanker task. Subjects reported, by a left or right button-press, the orientation of a left- or right-facing central arrow, flanked by two distractor arrows on each side. Central and peripheral arrows either pointed in the same (congruent trial) or in the opposite direction (incongruent trial). Top-down control was manipulated by changing the probability of congruent and incongruent trials in a given block. In the "mostly incongruent" (MI) blocks, 80% of trials were incongruent, producing a context in which subjects strongly anticipated that they would have to face conflict. In the "mostly congruent" (MC) blocks, 80% of trials were congruent and thus subjects barely anticipated conflict in that context. Thus, we assume that top-down control was stronger in the MI than in the MC condition. Accordingly, subjects displayed a lower error rate and shorter reaction times for the incongruent trials in the MI context than for similar trials in the MC context. More interestingly, we found that top-down control specifically reduced activation of the incompatible motor representation during response selection under high conflict. That is, when the central arrow specified a right hand response, left (non-selected) MEPs became smaller in the MI than in the MC condition, but only for incongruent trials, and this measure was positively correlated with performance. In contrast, MEPs elicited in the non-selected hand during congruent trials, or during all trials in which the left hand was selected, tended to increase

Amplification or suppression: Social networks and the climate change—migration association in rural Mexico

PubMed Central

Riosmena, Fernando; Hunter, Lori M.; Runfola, Daniel M.

2015-01-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks – the ties connecting an origin and destination – may operate as “migration corridors” with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying, social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place. PMID:26692656

Social exclusion impairs distractor suppression but not target enhancement in selective attention.

PubMed

Xu, Mengsi; Li, Zhiai; Diao, Liuting; Fan, Lingxia; Zhang, Lijie; Yuan, Shuge; Yang, Dong

2017-11-01

Social exclusion has been thought to weaken one's ability to exert inhibitory control. Existing studies have primarily focused on the relationship between exclusion and behavioral inhibition, and have reported that exclusion impairs behavioral inhibition. However, whether exclusion also affects selective attention, another important aspect of inhibitory control, remains unknown. Therefore, the current study aimed to explore whether social exclusion impairs selective attention, and to specifically examine its effect on two hypothesized mechanisms of selective attention: target enhancement and distractor suppression. The Cyberball game was used to manipulate social exclusion. Participants then performed a visual search task while event-related potentials were recorded. In the visual search task, target and salient distractor were either both presented laterally or one was presented on the vertical midline and the other laterally. Results showed that social exclusion differentially affected target and distractor processing. While exclusion impaired distractor suppression, reflected as smaller distractor-positivity (Pd) amplitudes for the exclusion group compared to the inclusion group, it did not affect target enhancement, reflected as similar target-negativity (Nt) amplitudes for both the exclusion and inclusion groups. Together, these results extend our understanding of the relationship between exclusion and inhibitory control, and suggest that social exclusion affects selective attention in a more complex manner than previously thought. Copyright © 2017. Published by Elsevier B.V.

Modality-specificity of Selective Attention Networks.

PubMed

Stewart, Hannah J; Amitay, Sygal

2015-01-01

To establish the modality specificity and generality of selective attention networks. Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT), the Test of Everyday Attention (TEA), and the Test of Attention in Listening (TAiL). These provided independent measures for auditory and visual alerting, orienting, and conflict resolution networks. The measures were subjected to an exploratory factor analysis to assess underlying attention constructs. The analysis yielded a four-component solution. The first component comprised of a range of measures from the TEA and was labeled "general attention." The third component was labeled "auditory attention," as it only contained measures from the TAiL using pitch as the attended stimulus feature. The second and fourth components were labeled as "spatial orienting" and "spatial conflict," respectively-they were comprised of orienting and conflict resolution measures from the vANT, aANT, and TAiL attend-location task-all tasks based upon spatial judgments (e.g., the direction of a target arrow or sound location). These results do not support our a-priori hypothesis that attention networks are either modality specific or supramodal. Auditory attention separated into selectively attending to spatial and non-spatial features, with the auditory spatial attention loading onto the same factor as visual spatial attention, suggesting spatial attention is supramodal. However, since our study did not include a non-spatial measure of visual attention, further research will be required to ascertain whether non-spatial attention is modality-specific.

Suppression of epidemic spreading in complex networks by local information based behavioral responses

NASA Astrophysics Data System (ADS)

Zhang, Hai-Feng; Xie, Jia-Rong; Tang, Ming; Lai, Ying-Cheng

2014-12-01

The interplay between individual behaviors and epidemic dynamics in complex networks is a topic of recent interest. In particular, individuals can obtain different types of information about the disease and respond by altering their behaviors, and this can affect the spreading dynamics, possibly in a significant way. We propose a model where individuals' behavioral response is based on a generic type of local information, i.e., the number of neighbors that has been infected with the disease. Mathematically, the response can be characterized by a reduction in the transmission rate by a factor that depends on the number of infected neighbors. Utilizing the standard susceptible-infected-susceptible and susceptible-infected-recovery dynamical models for epidemic spreading, we derive a theoretical formula for the epidemic threshold and provide numerical verification. Our analysis lays on a solid quantitative footing the intuition that individual behavioral response can in general suppress epidemic spreading. Furthermore, we find that the hub nodes play the role of "double-edged sword" in that they can either suppress or promote outbreak, depending on their responses to the epidemic, providing additional support for the idea that these nodes are key to controlling epidemic spreading in complex networks.

Suppression of epidemic spreading in complex networks by local information based behavioral responses.

PubMed

Zhang, Hai-Feng; Xie, Jia-Rong; Tang, Ming; Lai, Ying-Cheng

2014-12-01

The interplay between individual behaviors and epidemic dynamics in complex networks is a topic of recent interest. In particular, individuals can obtain different types of information about the disease and respond by altering their behaviors, and this can affect the spreading dynamics, possibly in a significant way. We propose a model where individuals' behavioral response is based on a generic type of local information, i.e., the number of neighbors that has been infected with the disease. Mathematically, the response can be characterized by a reduction in the transmission rate by a factor that depends on the number of infected neighbors. Utilizing the standard susceptible-infected-susceptible and susceptible-infected-recovery dynamical models for epidemic spreading, we derive a theoretical formula for the epidemic threshold and provide numerical verification. Our analysis lays on a solid quantitative footing the intuition that individual behavioral response can in general suppress epidemic spreading. Furthermore, we find that the hub nodes play the role of "double-edged sword" in that they can either suppress or promote outbreak, depending on their responses to the epidemic, providing additional support for the idea that these nodes are key to controlling epidemic spreading in complex networks.

Behavioral performance follows the time course of neural facilitation and suppression during cued shifts of feature-selective attention.

PubMed

Andersen, S K; Müller, M M

2010-08-03

A central question in the field of attention is whether visual processing is a strictly limited resource, which must be allocated by selective attention. If this were the case, attentional enhancement of one stimulus should invariably lead to suppression of unattended distracter stimuli. Here we examine voluntary cued shifts of feature-selective attention to either one of two superimposed red or blue random dot kinematograms (RDKs) to test whether such a reciprocal relationship between enhancement of an attended and suppression of an unattended stimulus can be observed. The steady-state visual evoked potential (SSVEP), an oscillatory brain response elicited by the flickering RDKs, was measured in human EEG. Supporting limited resources, we observed both an enhancement of the attended and a suppression of the unattended RDK, but this observed reciprocity did not occur concurrently: enhancement of the attended RDK started at 220 ms after cue onset and preceded suppression of the unattended RDK by about 130 ms. Furthermore, we found that behavior was significantly correlated with the SSVEP time course of a measure of selectivity (attended minus unattended) but not with a measure of total activity (attended plus unattended). The significant deviations from a temporally synchronized reciprocity between enhancement and suppression suggest that the enhancement of the attended stimulus may cause the suppression of the unattended stimulus in the present experiment.

Vasopressin excites interneurons to suppress hippocampal network activity across a broad span of brain maturity at birth

PubMed Central

Spoljaric, Albert; Seja, Patricia; Spoljaric, Inkeri; Virtanen, Mari A.; Lindfors, Jenna; Uvarov, Pavel; Summanen, Milla; Crow, Ailey K.; Hsueh, Brian; Puskarjov, Martin; Ruusuvuori, Eva; Voipio, Juha; Deisseroth, Karl; Kaila, Kai

2017-01-01

During birth in mammals, a pronounced surge of fetal peripheral stress hormones takes place to promote survival in the transition to the extrauterine environment. However, it is not known whether the hormonal signaling involves central pathways with direct protective effects on the perinatal brain. Here, we show that arginine vasopressin specifically activates interneurons to suppress spontaneous network events in the perinatal hippocampus. Experiments done on the altricial rat and precocial guinea pig neonate demonstrated that the effect of vasopressin is not dependent on the level of maturation (depolarizing vs. hyperpolarizing) of postsynaptic GABAA receptor actions. Thus, the fetal mammalian brain is equipped with an evolutionarily conserved mechanism well-suited to suppress energetically expensive correlated network events under conditions of reduced oxygen supply at birth. PMID:29183979

Artificial neural network for suppression of banding artifacts in balanced steady-state free precession MRI.

PubMed

Kim, Ki Hwan; Park, Sung-Hong

2017-04-01

The balanced steady-state free precession (bSSFP) MR sequence is frequently used in clinics, but is sensitive to off-resonance effects, which can cause banding artifacts. Often multiple bSSFP datasets are acquired at different phase cycling (PC) angles and then combined in a special way for banding artifact suppression. Many strategies of combining the datasets have been suggested for banding artifact suppression, but there are still limitations in their performance, especially when the number of phase-cycled bSSFP datasets is small. The purpose of this study is to develop a learning-based model to combine the multiple phase-cycled bSSFP datasets for better banding artifact suppression. Multilayer perceptron (MLP) is a feedforward artificial neural network consisting of three layers of input, hidden, and output layers. MLP models were trained by input bSSFP datasets acquired from human brain and knee at 3T, which were separately performed for two and four PC angles. Banding-free bSSFP images were generated by maximum-intensity projection (MIP) of 8 or 12 phase-cycled datasets and were used as targets for training the output layer. The trained MLP models were applied to another brain and knee datasets acquired with different scan parameters and also to multiple phase-cycled bSSFP functional MRI datasets acquired on rat brain at 9.4T, in comparison with the conventional MIP method. Simulations were also performed to validate the MLP approach. Both the simulations and human experiments demonstrated that MLP suppressed banding artifacts significantly, superior to MIP in both banding artifact suppression and SNR efficiency. MLP demonstrated superior performance over MIP for the 9.4T fMRI data as well, which was not used for training the models, while visually preserving the fMRI maps very well. Artificial neural network is a promising technique for combining multiple phase-cycled bSSFP datasets for banding artifact suppression. Copyright © 2016 Elsevier Inc. All

Dissociating the influence of response selection and task anticipation on corticospinal suppression during response preparation.

PubMed

Duque, Julie; Labruna, Ludovica; Cazares, Christian; Ivry, Richard B

2014-12-01

Motor behavior requires selecting between potential actions. The role of inhibition in response selection has frequently been examined in tasks in which participants are engaged in some advance preparation prior to the presentation of an imperative signal. Under such conditions, inhibition could be related to processes associated with response selection, or to more general inhibitory processes that are engaged in high states of anticipation. In Experiment 1, we manipulated the degree of anticipatory preparation. Participants performed a choice reaction time task that required choosing between a movement of the left or right index finger, and used transcranial magnetic stimulation (TMS) to elicit motor evoked potentials (MEPs) in the left hand agonist. In high anticipation blocks, a non-informative cue (e.g., fixation marker) preceded the imperative; in low anticipation blocks, there was no cue and participants were required to divide their attention between two tasks to further reduce anticipation. MEPs were substantially reduced before the imperative signal in high anticipation blocks. In contrast, in low anticipation blocks, MEPs remained unchanged before the imperative signal but showed a marked suppression right after the onset of the imperative. This effect occurred regardless of whether the imperative had signalled a left or right hand response. After this initial inhibition, left MEPs increased when the left hand was selected and remained suppressed when the right hand was selected. We obtained similar results in Experiment 2 except that the persistent left MEP suppression when the left hand was not selected was attenuated when the alternative response involved a non-homologous effector (right foot). These results indicate that, even in the absence of an anticipatory period, inhibitory mechanisms are engaged during response selection, possibly to prevent the occurrence of premature and inappropriate responses during a competitive selection process. Copyright

Dissociating the Influence of Response Selection and Task Anticipation on Corticospinal Suppression During Response Preparation

PubMed Central

Duque, Julie; Labruna, Ludovica; Cazares, Christian; Ivry, Richard B.

2014-01-01

Motor behavior requires selecting between potential actions. The role of inhibition in response selection has frequently been examined in tasks in which participants are engaged in some advance preparation prior to the presentation of an imperative signal. Under such conditions, inhibition could be related to processes associated with response selection, or to more general inhibitory processes that are engaged in high states of anticipation. In Experiment 1, we manipulated the degree of anticipatory preparation. Participants performed a choice reaction time task that required choosing between a movement of the left or right index finger, and used transcranial magnetic stimulation (TMS) to elicit motor evoked potentials (MEPs) in the left hand agonist. In high anticipation blocks, a non-informative cue (e.g., fixation marker) preceded the imperative; in low anticipation blocks, there was no cue and participants were required to divide their attention between two tasks to further reduce anticipation. MEPs were substantially reduced before the imperative signal in high anticipation blocks. In contrast, in low anticipation blocks, MEPs remained unchanged before the imperative signal but showed a marked suppression right after the onset of the imperative. This effect occurred regardless of whether the imperative had signaled a left or right hand response. After this initial inhibition, left MEPs increased when the left hand was selected and remained suppressed when the right hand was selected. We obtained similar results in Experiment 2 except that the persistent left MEP suppression when the left hand was not selected was attenuated when the alternative response involved a non-homologous effector (right foot). These results indicate that, even in the absence of an anticipatory period, inhibitory mechanisms are engaged during response selection, possibly to prevent the occurrence of premature and inappropriate responses during a competitive selection process. PMID

An exotic invasive plant selects for increased competitive tolerance, but not competitive suppression, in a native grass.

PubMed

Fletcher, Rebecca A; Callaway, Ragan M; Atwater, Daniel Z

2016-06-01

Exotic invasive plants can exert strong selective pressure for increased competitive ability in native plants. There are two fundamental components of competitive ability: suppression and tolerance, and the current paradigm that these components have equal influences on a species' overall competitive ability has been recently questioned. If these components do not have equal influences on overall ability, then selection on competitive tolerance and suppression may be disproportionate. We used naturally invaded communities to study the effects of selection caused by an invasive forb, Centaurea stoebe, on a native grass, Pseudoroegneria spicata. P. spicata plants were harvested from within dense C. stoebe patches and from nearby uninvaded areas, divided clonally into replicates, then transplanted into a common garden where they grew alone or competed with C. stoebe. We found that P. spicata plants collected from within C. stoebe patches were significantly more tolerant of competition with C. stoebe than P. spicata plants collected from uninvaded areas, but plants from inside invaded patches were not superior at suppressing C. stoebe. These results are consistent with the hypothesis that strong competitors may select for tolerance to competition more than for the ability to suppress neighbors. This has important implications for how native plant communities may respond to invasion over time, and how invasive and native species may ultimately coexist.

Interaction of oscillations, and their suppression via deep brain stimulation, in a model of the cortico-basal ganglia network.

PubMed

Kang, Guiyeom; Lowery, Madeleine M

2013-03-01

Growing evidence suggests that synchronized neural oscillations in the cortico-basal ganglia network may play a critical role in the pathophysiology of Parkinson's disease. In this study, a new model of the closed loop network is used to explore the generation and interaction of network oscillations and their suppression through deep brain stimulation (DBS). Under simulated dopamine depletion conditions, increased gain through the hyperdirect pathway resulted in the interaction of neural oscillations at different frequencies in the cortex and subthalamic nucleus (STN), leading to the emergence of synchronized oscillations at a new intermediate frequency. Further increases in synaptic gain resulted in the cortex driving synchronous oscillatory activity throughout the network. When DBS was added to the model a progressive reduction in STN power at the tremor and beta frequencies was observed as the frequency of stimulation was increased, with resonance effects occurring for low frequency DBS (40 Hz) in agreement with experimental observations. The results provide new insights into the mechanisms by which synchronous oscillations can arise within the network and how DBS may suppress unwanted oscillatory activity.

Modality-specificity of Selective Attention Networks

PubMed Central

Stewart, Hannah J.; Amitay, Sygal

2015-01-01

Objective: To establish the modality specificity and generality of selective attention networks. Method: Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT), the Test of Everyday Attention (TEA), and the Test of Attention in Listening (TAiL). These provided independent measures for auditory and visual alerting, orienting, and conflict resolution networks. The measures were subjected to an exploratory factor analysis to assess underlying attention constructs. Results: The analysis yielded a four-component solution. The first component comprised of a range of measures from the TEA and was labeled “general attention.” The third component was labeled “auditory attention,” as it only contained measures from the TAiL using pitch as the attended stimulus feature. The second and fourth components were labeled as “spatial orienting” and “spatial conflict,” respectively—they were comprised of orienting and conflict resolution measures from the vANT, aANT, and TAiL attend-location task—all tasks based upon spatial judgments (e.g., the direction of a target arrow or sound location). Conclusions: These results do not support our a-priori hypothesis that attention networks are either modality specific or supramodal. Auditory attention separated into selectively attending to spatial and non-spatial features, with the auditory spatial attention loading onto the same factor as visual spatial attention, suggesting spatial attention is supramodal. However, since our study did not include a non-spatial measure of visual attention, further research will be required to ascertain whether non-spatial attention is modality-specific. PMID:26635709

Some scale-free networks could be robust under selective node attacks

NASA Astrophysics Data System (ADS)

Zheng, Bojin; Huang, Dan; Li, Deyi; Chen, Guisheng; Lan, Wenfei

2011-04-01

It is a mainstream idea that scale-free network would be fragile under the selective attacks. Internet is a typical scale-free network in the real world, but it never collapses under the selective attacks of computer viruses and hackers. This phenomenon is different from the deduction of the idea above because this idea assumes the same cost to delete an arbitrary node. Hence this paper discusses the behaviors of the scale-free network under the selective node attack with different cost. Through the experiments on five complex networks, we show that the scale-free network is possibly robust under the selective node attacks; furthermore, the more compact the network is, and the larger the average degree is, then the more robust the network is; with the same average degrees, the more compact the network is, the more robust the network is. This result would enrich the theory of the invulnerability of the network, and can be used to build robust social, technological and biological networks, and also has the potential to find the target of drugs.

Investigating category- and shape-selective neural processing in ventral and dorsal visual stream under interocular suppression.

PubMed

Ludwig, Karin; Kathmann, Norbert; Sterzer, Philipp; Hesselmann, Guido

2015-01-01

Recent behavioral and neuroimaging studies using continuous flash suppression (CFS) have suggested that action-related processing in the dorsal visual stream might be independent of perceptual awareness, in line with the "vision-for-perception" versus "vision-for-action" distinction of the influential dual-stream theory. It remains controversial if evidence suggesting exclusive dorsal stream processing of tool stimuli under CFS can be explained by their elongated shape alone or by action-relevant category representations in dorsal visual cortex. To approach this question, we investigated category- and shape-selective functional magnetic resonance imaging-blood-oxygen level-dependent responses in both visual streams using images of faces and tools. Multivariate pattern analysis showed enhanced decoding of elongated relative to non-elongated tools, both in the ventral and dorsal visual stream. The second aim of our study was to investigate whether the depth of interocular suppression might differentially affect processing in dorsal and ventral areas. However, parametric modulation of suppression depth by varying the CFS mask contrast did not yield any evidence for differential modulation of category-selective activity. Together, our data provide evidence for shape-selective processing under CFS in both dorsal and ventral stream areas and, therefore, do not support the notion that dorsal "vision-for-action" processing is exclusively preserved under interocular suppression. © 2014 Wiley Periodicals, Inc.

Heuristic Strategies for Persuader Selection in Contagions on Complex Networks.

PubMed

Wang, Peng; Zhang, Li-Jie; Xu, Xin-Jian; Xiao, Gaoxi

2017-01-01

Individual decision to accept a new idea or product is often driven by both self-adoption and others' persuasion, which has been simulated using a double threshold model [Huang et al., Scientific Reports 6, 23766 (2016)]. We extend the study to consider the case with limited persuasion. That is, a set of individuals is chosen from the population to be equipped with persuasion capabilities, who may succeed in persuading their friends to take the new entity when certain conditions are satisfied. Network node centrality is adopted to characterize each node's influence, based on which three heuristic strategies are applied to pick out persuaders. We compare these strategies for persuader selection on both homogeneous and heterogeneous networks. Two regimes of the underline networks are identified in which the system exhibits distinct behaviors: when networks are sufficiently sparse, selecting persuader nodes in descending order of node centrality achieves the best performance; when networks are sufficiently dense, however, selecting nodes with medium centralities to serve as the persuaders performs the best. Under respective optimal strategies for different types of networks, we further probe which centrality measure is most suitable for persuader selection. It turns out that for the first regime, degree centrality offers the best measure for picking out persuaders from homogeneous networks; while in heterogeneous networks, betweenness centrality takes its place. In the second regime, there is no significant difference caused by centrality measures in persuader selection for homogeneous network; while for heterogeneous networks, closeness centrality offers the best measure.

Bidirectional selection between two classes in complex social networks.

PubMed

Zhou, Bin; He, Zhe; Jiang, Luo-Luo; Wang, Nian-Xin; Wang, Bing-Hong

2014-12-19

The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals' neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.

Sexual networks: measuring sexual selection in structured, polyandrous populations.

PubMed

McDonald, Grant C; James, Richard; Krause, Jens; Pizzari, Tommaso

2013-03-05

Sexual selection is traditionally measured at the population level, assuming that populations lack structure. However, increasing evidence undermines this approach, indicating that intrasexual competition in natural populations often displays complex patterns of spatial and temporal structure. This complexity is due in part to the degree and mechanisms of polyandry within a population, which can influence the intensity and scale of both pre- and post-copulatory sexual competition. Attempts to measure selection at the local and global scale have been made through multi-level selection approaches. However, definitions of local scale are often based on physical proximity, providing a rather coarse measure of local competition, particularly in polyandrous populations where the local scale of pre- and post-copulatory competition may differ drastically from each other. These limitations can be solved by social network analysis, which allows us to define a unique sexual environment for each member of a population: 'local scale' competition, therefore, becomes an emergent property of a sexual network. Here, we first propose a novel quantitative approach to measure pre- and post-copulatory sexual selection, which integrates multi-level selection with information on local scale competition derived as an emergent property of networks of sexual interactions. We then use simple simulations to illustrate the ways in which polyandry can impact estimates of sexual selection. We show that for intermediate levels of polyandry, the proposed network-based approach provides substantially more accurate measures of sexual selection than the more traditional population-level approach. We argue that the increasing availability of fine-grained behavioural datasets provides exciting new opportunities to develop network approaches to study sexual selection in complex societies.

Suppressing epidemic spreading in multiplex networks with social-support

NASA Astrophysics Data System (ADS)

Chen, Xiaolong; Wang, Ruijie; Tang, Ming; Cai, Shimin; Stanley, H. Eugene; Braunstein, Lidia A.

2018-01-01

Although suppressing the spread of a disease is usually achieved by investing in public resources, in the real world only a small percentage of the population have access to government assistance when there is an outbreak, and most must rely on resources from family or friends. We study the dynamics of disease spreading in social-contact multiplex networks when the recovery of infected nodes depends on resources from healthy neighbors in the social layer. We investigate how degree heterogeneity affects the spreading dynamics. Using theoretical analysis and simulations we find that degree heterogeneity promotes disease spreading. The phase transition of the infected density is hybrid and increases smoothly from zero to a finite small value at the first invasion threshold and then suddenly jumps at the second invasion threshold. We also find a hysteresis loop in the transition of the infected density. We further investigate how an overlap in the edges between two layers affects the spreading dynamics. We find that when the amount of overlap is smaller than a critical value the phase transition is hybrid and there is a hysteresis loop, otherwise the phase transition is continuous and the hysteresis loop vanishes. In addition, the edge overlap allows an epidemic outbreak when the transmission rate is below the first invasion threshold, but suppresses any explosive transition when the transmission rate is above the first invasion threshold.

A Compact Band-Pass Filter with High Selectivity and Second Harmonic Suppression

PubMed Central

Hadarig, Ramona Cosmina; de Cos Gomez, Maria Elena; Las-Heras, Fernando

2013-01-01

The design of a novel band-pass filter with narrow-band features based on an electromagnetic resonator at 6.4 GHz is presented. A prototype is manufactured and characterized in terms of transmission and reflection coefficient. The selective passband and suppression of the second harmonic make the filter suitable to be used in a C band frequency range for radar systems and satellite/terrestrial applications. To avoid substantial interference for this kind of applications, passive components with narrow band features and small dimensions are required. Between 3.6 GHz and 4.2 GHz the band-pass filter with harmonic suppression should have an attenuation of at least 35 dB, whereas for a passband, less than 10% is sufficient. PMID:28788412

Network and neuronal membrane properties in hybrid networks reciprocally regulate selectivity to rapid thalamocortical inputs.

PubMed

Pesavento, Michael J; Pinto, David J

2012-11-01

Rapidly changing environments require rapid processing from sensory inputs. Varying deflection velocities of a rodent's primary facial vibrissa cause varying temporal neuronal activity profiles within the ventral posteromedial thalamic nucleus. Local neuron populations in a single somatosensory layer 4 barrel transform sparsely coded input into a spike count based on the input's temporal profile. We investigate this transformation by creating a barrel-like hybrid network with whole cell recordings of in vitro neurons from a cortical slice preparation, embedding the biological neuron in the simulated network by presenting virtual synaptic conductances via a conductance clamp. Utilizing the hybrid network, we examine the reciprocal network properties (local excitatory and inhibitory synaptic convergence) and neuronal membrane properties (input resistance) by altering the barrel population response to diverse thalamic input. In the presence of local network input, neurons are more selective to thalamic input timing; this arises from strong feedforward inhibition. Strongly inhibitory (damping) network regimes are more selective to timing and less selective to the magnitude of input but require stronger initial input. Input selectivity relies heavily on the different membrane properties of excitatory and inhibitory neurons. When inhibitory and excitatory neurons had identical membrane properties, the sensitivity of in vitro neurons to temporal vs. magnitude features of input was substantially reduced. Increasing the mean leak conductance of the inhibitory cells decreased the network's temporal sensitivity, whereas increasing excitatory leak conductance enhanced magnitude sensitivity. Local network synapses are essential in shaping thalamic input, and differing membrane properties of functional classes reciprocally modulate this effect.

Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

PubMed Central

Indiveri, Giacomo

2008-01-01

Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention. PMID:27873818

Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems.

PubMed

Indiveri, Giacomo

2008-09-03

Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks

NASA Astrophysics Data System (ADS)

Chen, Liang; Jin, Le; He, Feng; Cheng, Hanwen; Wu, Lenan

In next generation mobile multimedia communications, different wireless access networks are expected to cooperate. However, it is a challenging task to choose an optimal transmission path in this scenario. This paper focuses on the problem of selecting the optimal access network for multicast services in the cooperative mobile and broadcasting networks. An algorithm is proposed, which considers multiple decision factors and multiple optimization objectives. An analytic hierarchy process (AHP) method is applied to schedule the service queue and an artificial neural network (ANN) is used to improve the flexibility of the algorithm. Simulation results show that by applying the AHP method, a group of weight ratios can be obtained to improve the performance of multiple objectives. And ANN method is effective to adaptively adjust weight ratios when users' new waiting threshold is generated.

Multi-objective optimization of piezoelectric circuitry network for mode delocalization and suppression of bladed disk

NASA Astrophysics Data System (ADS)

Yoo, David; Tang, J.

2017-04-01

Since weakly-coupled bladed disks are highly sensitive to the presence of uncertainties, they can easily undergo vibration localization. When vibration localization occurs, vibration modes of bladed disk become dramatically different from those under the perfectly periodic condition, and the dynamic response under engine-order excitation is drastically amplified. In previous studies, it is investigated that amplified vibration response can be suppressed by connecting piezoelectric circuitry into individual blades to induce the damped absorber effect, and localized vibration modes can be alleviated by integrating piezoelectric circuitry network. Delocalization of vibration modes and vibration suppression of bladed disk, however, require different optimal set of circuit parameters. In this research, multi-objective optimization approach is developed to enable finding the best circuit parameters, simultaneously achieving both objectives. In this way, the robustness and reliability in bladed disk can be ensured. Gradient-based optimizations are individually developed for mode delocalization and vibration suppression, which are then integrated into multi-objective optimization framework.

Selective suppression of CARS signal with three-beam competing stimulated Raman scattering processes.

PubMed

Choi, Dae Sik; Rao, B Jayachander; Kim, Doyeon; Shim, Sang-Hee; Rhee, Hanju; Cho, Minhaeng

2018-06-14

Coherent Raman scattering spectroscopy and microscopy are useful methods for studying the chemical and biological structures of molecules with Raman-active modes. In particular, coherent anti-Stokes Raman scattering (CARS) microscopy, which is a label-free method capable of imaging structures by displaying the vibrational contrast of the molecules, has been widely used. However, the lack of a technique for switching-off the CARS signal has prevented the development of the super-resolution Raman imaging method. Here, we demonstrate that a selective suppression of the CARS signal is possible by using a three-beam double stimulated Raman scattering (SRS) scheme; the three beams are the pump, Stokes, and depletion lights in order of frequency. Both pump-Stokes and pump-depletion beam pairs can generate SRS processes by tuning their beat frequencies to match two different vibrational modes, then two CARS signals induced by pump-Stokes-pump and pump-depletion-pump interactions can be generated, where the two CARS signals are coupled with each other because they both involve interactions with the common pump beam. Herein, we show that as the intensity of the depletion beam is increased, one can selectively suppress the pump-Stokes-pump CARS signal because the pump-depletion SRS depletes the pump photons. A detailed theoretical description of the coupled differential equations for the three incident fields and the generated CARS signal fields is presented. Taking benzene as a molecular system, we obtained a maximum CARS suppression efficiency of about 97% with our experimental scheme, where the ring breathing mode of the benzene is associated with pump-Stokes-pump CARS, while the C-H stretching mode is associated with the competing pump-depletion SRS process. We anticipate that this selective switching-off scheme will be of use in developing super-resolution label-free CARS microscopy.

Relay Selection for Cooperative Relaying in Wireless Energy Harvesting Networks

NASA Astrophysics Data System (ADS)

Zhu, Kaiyan; Wang, Fei; Li, Songsong; Jiang, Fengjiao; Cao, Lijie

2018-01-01

Energy harvesting from the surroundings is a promising solution to provide energy supply and extend the life of wireless sensor networks. Recently, energy harvesting has been shown as an attractive solution to prolong the operation of cooperative networks. In this paper, we propose a relay selection scheme to optimize the amplify-and-forward (AF) cooperative transmission in wireless energy harvesting cooperative networks. The harvesting energy and channel conditions are considered to select the optimal relay as cooperative relay to minimize the outage probability of the system. Simulation results show that our proposed relay selection scheme achieves better outage performance than other strategies.

Selective Isobar Suppression for Accelerator Mass Spectrometry and Radioactive Ion Beam Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Galindo-Uribarri, Alfredo; Havener, Charles C; Lewis, Thomas L.

2010-01-01

Several applications of AMS will benefit from pushing further the detection limits of AMS isotopes. A new method of selective isobar suppression by photodetachment in a radio-frequency quadrupole ion cooler is being developed at HRIBF with a two-fold purpose: (1) increasing the AMS sensitivity for certain isotopes of interest and (2) purifying radioactive ion beams for nuclear science. The potential of suppressing the 36S contaminants in a 36Cl beam using this method has been explored with stable S- and Cl- ions and a Nd:YLF laser. In the study, the laser beam was directed along the experiment's beam line and throughmore » a RF quadrupole ion cooler. Negative 32S and 35Cl ions produced by a Cs sputter ion source were focused into the ion cooler where they were slowed by collisions with He buffer gas; this increased the interaction time between the negative ion beam and the laser beam. As a result, suppression of S- by a factor of 3000 was obtained with about 2.5 W average laser power in the cooler while no reduction in Cl- current was observed.« less

Generative model selection using a scalable and size-independent complex network classifier

NASA Astrophysics Data System (ADS)

Motallebi, Sadegh; Aliakbary, Sadegh; Habibi, Jafar

2013-12-01

Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree for model selection. Our proposed method, which is named "Generative Model Selection for Complex Networks," outperforms existing methods with respect to accuracy, scalability, and size-independence.

Deconstructing continuous flash suppression

PubMed Central

Yang, Eunice; Blake, Randolph

2012-01-01

In this paper, we asked to what extent the depth of interocular suppression engendered by continuous flash suppression (CFS) varies depending on spatiotemporal properties of the suppressed stimulus and CFS suppressor. An answer to this question could have implications for interpreting the results in which CFS influences the processing of different categories of stimuli to different extents. In a series of experiments, we measured the selectivity and depth of suppression (i.e., elevation in contrast detection thresholds) as a function of the visual features of the stimulus being suppressed and the stimulus evoking suppression, namely, the popular “Mondrian” CFS stimulus (N. Tsuchiya & C. Koch, 2005). First, we found that CFS differentially suppresses the spatial components of the suppressed stimulus: Observers' sensitivity for stimuli of relatively low spatial frequency or cardinally oriented features was more strongly impaired in comparison to high spatial frequency or obliquely oriented stimuli. Second, we discovered that this feature-selective bias primarily arises from the spatiotemporal structure of the CFS stimulus, particularly within information residing in the low spatial frequency range and within the smooth rather than abrupt luminance changes over time. These results imply that this CFS stimulus operates by selectively attenuating certain classes of low-level signals while leaving others to be potentially encoded during suppression. These findings underscore the importance of considering the contribution of low-level features in stimulus-driven effects that are reported under CFS. PMID:22408039

Deconstructing continuous flash suppression.

PubMed

Yang, Eunice; Blake, Randolph

2012-03-08

In this paper, we asked to what extent the depth of interocular suppression engendered by continuous flash suppression (CFS) varies depending on spatiotemporal properties of the suppressed stimulus and CFS suppressor. An answer to this question could have implications for interpreting the results in which CFS influences the processing of different categories of stimuli to different extents. In a series of experiments, we measured the selectivity and depth of suppression (i.e., elevation in contrast detection thresholds) as a function of the visual features of the stimulus being suppressed and the stimulus evoking suppression, namely, the popular "Mondrian" CFS stimulus (N. Tsuchiya & C. Koch, 2005). First, we found that CFS differentially suppresses the spatial components of the suppressed stimulus: Observers' sensitivity for stimuli of relatively low spatial frequency or cardinally oriented features was more strongly impaired in comparison to high spatial frequency or obliquely oriented stimuli. Second, we discovered that this feature-selective bias primarily arises from the spatiotemporal structure of the CFS stimulus, particularly within information residing in the low spatial frequency range and within the smooth rather than abrupt luminance changes over time. These results imply that this CFS stimulus operates by selectively attenuating certain classes of low-level signals while leaving others to be potentially encoded during suppression. These findings underscore the importance of considering the contribution of low-level features in stimulus-driven effects that are reported under CFS.

Select phytochemicals suppress human T-lymphocytes and mouse splenocytes suggesting their use in autoimmunity and transplantation

PubMed Central

Hushmendy, Shazaan; Jayakumar, Lalithapriya; Hahn, Amy B.; Bhoiwala, Devang; Bhoiwala, Dipti L.; Crawford, Dana R.

2009-01-01

We have considered a novel “rational” gene targeting approach for treating pathologies whose genetic bases are defined using select phytochemicals. We reason that one such potential application of this approach would be conditions requiring immunosuppression such as autoimmune disease and transplantation, where the genetic target is clearly defined; i.e., interleukin-2 and associated T-cell activation. Therefore, we hypothesized that select phytochemicals can suppress T-lymphocyte proliferation both in vitro and in vivo. The immunosuppressive effects of berry extract, curcumin, quercetin, sulforaphane, epigallocatechin gallate (EGCG), resveratrol, α-tocopherol, vitamin C and sucrose were tested on anti-CD3 plus anti-CD28-activated primary human T-lymphocytes in culture. Curcumin, sulforaphane, quercetin, berry extract and EGCG all significantly inhibited T-cell proliferation, and this effect was not due to toxicity. IL-2 production was also reduced by these agents, implicating this important T-cell cytokine in proliferation suppression. Except for berry extract, these same agents also inhibited mouse splenic T-cell proliferation and IL-2 production. Subsequent in vivo studies revealed that quercetin (but not sulforaphane) modestly suppressed mouse splenocyte proliferation following supplementation of BALB/c mice diets. This effect was especially prominent if corrected for the loss of supplement “recall” as observed in cultured T-cells. These results suggest the potential use of these select phytochemicals for treating autoimmune and transplant patients, and support our strategy of using select phytochemicals to treat genetically-defined pathologies, an approach that we believe is simple, healthy, and cost-effective. PMID:19761891

Stochastic cycle selection in active flow networks

NASA Astrophysics Data System (ADS)

Woodhouse, Francis; Forrow, Aden; Fawcett, Joanna; Dunkel, Jorn

2016-11-01

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such non-equilibrium networks. By connecting concepts from lattice field theory, graph theory and transition rate theory, we show how topology controls dynamics in a generic model for actively driven flow on a network. Through theoretical and numerical analysis we identify symmetry-based rules to classify and predict the selection statistics of complex flow cycles from the network topology. Our conceptual framework is applicable to a broad class of biological and non-biological far-from-equilibrium networks, including actively controlled information flows, and establishes a new correspondence between active flow networks and generalized ice-type models.

Can You Hear Me Now? Musical Training Shapes Functional Brain Networks for Selective Auditory Attention and Hearing Speech in Noise

PubMed Central

Strait, Dana L.; Kraus, Nina

2011-01-01

Even in the quietest of rooms, our senses are perpetually inundated by a barrage of sounds, requiring the auditory system to adapt to a variety of listening conditions in order to extract signals of interest (e.g., one speaker's voice amidst others). Brain networks that promote selective attention are thought to sharpen the neural encoding of a target signal, suppressing competing sounds and enhancing perceptual performance. Here, we ask: does musical training benefit cortical mechanisms that underlie selective attention to speech? To answer this question, we assessed the impact of selective auditory attention on cortical auditory-evoked response variability in musicians and non-musicians. Outcomes indicate strengthened brain networks for selective auditory attention in musicians in that musicians but not non-musicians demonstrate decreased prefrontal response variability with auditory attention. Results are interpreted in the context of previous work documenting perceptual and subcortical advantages in musicians for the hearing and neural encoding of speech in background noise. Musicians’ neural proficiency for selectively engaging and sustaining auditory attention to language indicates a potential benefit of music for auditory training. Given the importance of auditory attention for the development and maintenance of language-related skills, musical training may aid in the prevention, habilitation, and remediation of individuals with a wide range of attention-based language, listening and learning impairments. PMID:21716636

Generative model selection using a scalable and size-independent complex network classifier

DOE Office of Scientific and Technical Information (OSTI.GOV)

Motallebi, Sadegh, E-mail: motallebi@ce.sharif.edu; Aliakbary, Sadegh, E-mail: aliakbary@ce.sharif.edu; Habibi, Jafar, E-mail: jhabibi@sharif.edu

2013-12-15

Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree formore » model selection. Our proposed method, which is named “Generative Model Selection for Complex Networks,” outperforms existing methods with respect to accuracy, scalability, and size-independence.« less

Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks

PubMed Central

Fogelmark, Karl; Peterson, Carsten; Troein, Carl

2016-01-01

Background Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. Methodology To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. Principal Findings We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks. PMID:26927540

Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks.

PubMed

Fogelmark, Karl; Peterson, Carsten; Troein, Carl

2016-01-01

Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks.

Circulating Current Suppressing Control’s Impact on Arm Inductance Selection for Modular Multilevel Converter

DOE PAGES

Li, Yalong; Jones, Edward A.; Wang, Fred

2016-10-13

Arm inductor in a modular multilevel converter (MMC) is used to limit the circulating current and dc short circuit fault current. The circulating current in MMC is dominated by second-order harmonic, which can be largely reduced with circulating current suppressing control. By analyzing the mechanism of the circulating current suppressing control, it is found that the circulating current at switching frequency becomes the main harmonic when suppression control is implemented. Unlike the second-order harmonic that circulates only within the three phases, switching frequency harmonic also flows through the dc side and may further cause high-frequency dc voltage harmonic. This articlemore » develops the theoretical relationship between the arm inductance and switching frequency circulating current, which can be used to guide the arm inductance selection. The experimental results with a downscaled MMC prototype verify the existence of the switching frequency circulating current and its relationship with arm inductance.« less

Optimal allocation of resources for suppressing epidemic spreading on networks

NASA Astrophysics Data System (ADS)

Chen, Hanshuang; Li, Guofeng; Zhang, Haifeng; Hou, Zhonghuai

2017-07-01

Efficient allocation of limited medical resources is crucial for controlling epidemic spreading on networks. Based on the susceptible-infected-susceptible model, we solve the optimization problem of how best to allocate the limited resources so as to minimize prevalence, providing that the curing rate of each node is positively correlated to its medical resource. By quenched mean-field theory and heterogeneous mean-field (HMF) theory, we prove that an epidemic outbreak will be suppressed to the greatest extent if the curing rate of each node is directly proportional to its degree, under which the effective infection rate λ has a maximal threshold λcopt=1 / , where is the average degree of the underlying network. For a weak infection region (λ ≳λcopt ), we combine perturbation theory with the Lagrange multiplier method (LMM) to derive the analytical expression of optimal allocation of the curing rates and the corresponding minimized prevalence. For a general infection region (λ >λcopt ), the high-dimensional optimization problem is converted into numerically solving low-dimensional nonlinear equations by the HMF theory and LMM. Counterintuitively, in the strong infection region the low-degree nodes should be allocated more medical resources than the high-degree nodes to minimize prevalence. Finally, we use simulated annealing to validate the theoretical results.

Stochastic cycle selection in active flow networks.

PubMed

Woodhouse, Francis G; Forrow, Aden; Fawcett, Joanna B; Dunkel, Jörn

2016-07-19

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models.

Stochastic cycle selection in active flow networks

PubMed Central

Woodhouse, Francis G.; Forrow, Aden; Fawcett, Joanna B.; Dunkel, Jörn

2016-01-01

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models. PMID:27382186

New RNAi strategy for selective suppression of a mutant allele in polyglutamine disease.

PubMed

Kubodera, Takayuki; Yokota, Takanori; Ishikawa, Kinya; Mizusawa, Hidehiro

2005-12-01

In gene therapy of dominantly inherited diseases with small interfering RNA (siRNA), mutant allele specific suppression may be necessary for diseases in which the defective gene normally has an important role. It is difficult, however, to design a mutant allele-specific siRNA for trinucleotide repeat diseases in which the difference of sequences is only repeat length. To overcome this problem, we use a new RNA interference (RNAi) strategy for selective suppression of mutant alleles. Both mutant and wild-type alleles are inhibited by the most effective siRNA, and wild-type protein is restored using the wild-type mRNA modified to be resistant to the siRNA. Here, we applied this method to spinocerebellar ataxia type 6 (SCA6). We discuss its feasibility and problems for future gene therapy.

Popularity and adolescent friendship networks: selection and influence dynamics.

PubMed

Dijkstra, Jan Kornelis; Cillessen, Antonius H N; Borch, Casey

2013-07-01

This study examined the dynamics of popularity in adolescent friendship networks across 3 years in middle school. Longitudinal social network modeling was used to identify selection and influence in the similarity of popularity among friends. It was argued that lower status adolescents strive to enhance their status through befriending higher status adolescents, whereas higher status adolescents strive to maintain their status by keeping lower status adolescents at a distance. The results largely supported these expectations. Selection partially accounted for similarity in popularity among friends; adolescents preferred to affiliate with similar-status or higher status peers, reinforcing the attractiveness of popular adolescents and explaining stability of popularity at the individual level. Influence processes also accounted for similarity in popularity over time, showing that peers increase in popularity and become more similar to their friends. The results showed how selection and influence processes account for popularity dynamics in adolescent networks over time.

Oroxin B selectively induces tumor-suppressive ER stress and concurrently inhibits tumor-adaptive ER stress in B-lymphoma cells for effective anti-lymphoma therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Ping; Fu, Shilong; Cao, Zhifei

Cancer cells have both tumor-adaptive and -suppressive endoplasmic reticulum (ER) stress machineries that determine cell fate. In malignant tumors including lymphoma, constant activation of tumor-adaptive ER stress and concurrent reduction of tumor-suppressive ER stress favors cancer cell proliferation and tumor growth. Current ER stress-based anti-tumor drugs typically activate both tumor-adaptive and -suppressive ER stresses, resulting in low anti-cancer efficacy; hence, selective induction of tumor-suppressive ER stress and inhibition of tumor-adaptive ER stress are new strategies for novel anti-cancer drug discovery. Thus far, specific tumor-suppressive ER stress therapeutics have remained absent in clinical settings. In this study, we explored unique tumor-suppressivemore » ER stress agents from the traditional Chinese medicinal herb Oroxylum indicum, and found that a small molecule oroxin B selectively induced tumor-suppressive ER stress in malignant lymphoma cells, but not in normal cells, effectively inhibited lymphoma growth in vivo, and significantly prolonged overall survival of lymphoma-xenografted mice without obvious toxicity. Mechanistic studies have revealed that the expression of key tumor-adaptive ER-stress gene GRP78 was notably suppressed by oroxin B via down-regulation of up-stream key signaling protein ATF6, while tumor-suppressive ER stress master gene DDIT3 was strikingly activated through activating the MKK3-p38 signaling pathway, correcting the imbalance between tumor-suppressive DDIT3 and tumor-adaptive GRP78 in lymphoma. Together, selective induction of unique tumor-suppressive ER stress and concurrent inhibition of tumor-adaptive ER stress in malignant lymphoma are new and feasible approaches for novel anti-lymphoma drug discovery and anti-lymphoma therapy. - Highlights: • Oroxin B selectively induces tumor-suppressive ER stress in B-lymphoma cells. • Oroxin B significantly prolonged overall survival of lymphoma-xenografted mice

Rituximab selectively suppresses specific islet antibodies.

PubMed

Yu, Liping; Herold, Kevan; Krause-Steinrauf, Heidi; McGee, Paula L; Bundy, Brian; Pugliese, Alberto; Krischer, Jeff; Eisenbarth, George S

2011-10-01

The TrialNet Study Group evaluated rituximab, a B-cell-depleting monoclonal antibody, for its effect in new-onset patients with type 1A diabetes. Rituximab decreased the loss of C-peptide over the first year of follow-up and markedly depleted B lymphocytes for 6 months after administration. This article analyzes the specific effect of rituximab on multiple islet autoantibodies. A total of 87 patients between the ages of 8 and 40 years received either rituximab or a placebo infusion weekly for four doses close to the onset of diabetes. Autoantibodies to insulin (IAAs), GAD65 (GADAs), insulinoma-associated protein 2 (IA2As), and ZnT8 (ZnT8As) were measured with radioimmunoassays. The primary outcome for this autoantibody analysis was the mean level of autoantibodies during follow-up. Rituximab markedly suppressed IAAs compared with the placebo injection but had a much smaller effect on GADAs, IA2As, and ZnT8As. A total of 40% (19 of 48) of rituximab-treated patients who were IAA positive became IAA negative versus 0 of 29 placebo-treated patients (P < 0.0001). In the subgroup (n = 6) treated within 50 days of diabetes, IAAs were markedly suppressed by rituximab in all patients for 1 year and for four patients as long as 3 years despite continuing insulin therapy. Independent of rituximab treatment, the mean level of IAAs at study entry was markedly lower (P = 0.035) for patients who maintained C-peptide levels during the first year of follow-up in both rituximab-treated and placebo groups. A single course of rituximab differentially suppresses IAAs, clearly blocking IAAs for >1 year in insulin-treated patients. For the patients receiving insulin for >2 weeks prior to rituximab administration, we cannot assess whether rituximab not only blocks the acquisition of insulin antibodies induced by insulin administration and/or also suppresses preformed insulin autoantibodies. Studies in prediabetic non-insulin-treated patients will likely be needed to evaluate the specific

Impacts of suppressing guide on information spreading

NASA Astrophysics Data System (ADS)

Xu, Jinghong; Zhang, Lin; Ma, Baojun; Wu, Ye

2016-02-01

It is quite common that guides are introduced to suppress the information spreading in modern society for different purposes. In this paper, an agent-based model is established to quantitatively analyze the impacts of suppressing guides on information spreading. We find that the spreading threshold depends on the attractiveness of the information and the topology of the social network with no suppressing guides at all. Usually, one would expect that the existence of suppressing guides in the spreading procedure may result in less diffusion of information within the overall network. However, we find that sometimes the opposite is true: the manipulating nodes of suppressing guides may lead to more extensive information spreading when there are audiences with the reversal mind. These results can provide valuable theoretical references to public opinion guidance on various information, e.g., rumor or news spreading.

Local Circuit Inhibition in the Cerebral Cortex as the source of Gain Control and Untuned Suppression

PubMed Central

Shapley, Robert M.; Xing, Dajun

2012-01-01

Theoretical considerations have led to the concept that the cerebral cortex is operating in a balanced state in which synaptic excitation is approximately balanced by synaptic inhibition from the local cortical circuit. This paper is about the functional consequences of the balanced state in sensory cortex. One consequence is gain control: there is experimental evidence and theoretical support for the idea that local circuit inhibition acts as a local automatic gain control throughout the cortex. Second, inhibition increases cortical feature selectivity: many studies of different sensory cortical areas have reported that suppressive mechanisms contribute to feature selectivity. Synaptic inhibition from the local microcircuit should be untuned (or broadly tuned) for stimulus features because of the microarchitecture of the cortical microcircuit. Untuned inhibition probably is the source of Untuned Suppression that enhances feature selectivity. We studied inhibition’s function in our experiments, guided by a neuronal network model, on orientation selectivity in the primary visual cortex, V1, of the Macaque monkey. Our results revealed that Untuned Suppression, generated by local circuit inhibition, is crucial for the generation of highly orientation-selective cells in V1 cortex. PMID:23036513

A new bio-inspired stimulator to suppress hyper-synchronized neural firing in a cortical network.

PubMed

Amiri, Masoud; Amiri, Mahmood; Nazari, Soheila; Faez, Karim

2016-12-07

Hyper-synchronous neural oscillations are the character of several neurological diseases such as epilepsy. On the other hand, glial cells and particularly astrocytes can influence neural synchronization. Therefore, based on the recent researches, a new bio-inspired stimulator is proposed which basically is a dynamical model of the astrocyte biophysical model. The performance of the new stimulator is investigated on a large-scale, cortical network. Both excitatory and inhibitory synapses are also considered in the simulated spiking neural network. The simulation results show that the new stimulator has a good performance and is able to reduce recurrent abnormal excitability which in turn avoids the hyper-synchronous neural firing in the spiking neural network. In this way, the proposed stimulator has a demand controlled characteristic and is a good candidate for deep brain stimulation (DBS) technique to successfully suppress the neural hyper-synchronization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Voluntary strategy suppresses the positive impact of preferential selection in prisoner’s dilemma

NASA Astrophysics Data System (ADS)

Sun, Lei; Lin, Pei-jie; Chen, Ya-shan

2014-11-01

Impact of aspiration is ubiquitous in social and biological disciplines. In this work, we try to explore the impact of such a trait on voluntary prisoners’ dilemma game via a selection parameter w. w=0 returns the traditional version of random selection. For positive w, the opponent of high payoff will be selected; while negative w means that the partner of low payoff will be chosen. We find that for positive w, cooperation will be greatly promoted in the interval of small b, at variance cooperation is inhibited with large b. For negative w, cooperation is fully restrained, irrespective of b value. It is found that the positive impact of preferential selection is suppressed by the voluntary strategy in prisoner’s dilemma. These observations can be supported by the spatial patterns. Our work may shed light on the emergence and persistence of cooperation with voluntary participation in social dilemma.

Early-Onset Network Hyperexcitability in Presymptomatic Alzheimer’s Disease Transgenic Mice Is Suppressed by Passive Immunization with Anti-Human APP/Aβ Antibody and by mGluR5 Blockade

PubMed Central

Kazim, Syed F.; Chuang, Shih-Chieh; Zhao, Wangfa; Wong, Robert K. S.; Bianchi, Riccardo; Iqbal, Khalid

2017-01-01

Cortical and hippocampal network hyperexcitability appears to be an early event in Alzheimer’s disease (AD) pathogenesis, and may contribute to memory impairment. It remains unclear if network hyperexcitability precedes memory impairment in mouse models of AD and what are the underlying cellular mechanisms. We thus evaluated seizure susceptibility and hippocampal network hyperexcitability at ~3 weeks of age [prior to amyloid beta (Aβ) plaque deposition, neurofibrillary pathology, and cognitive impairment] in a triple transgenic mouse model of familial AD (3xTg-AD mouse) that harbors mutated human Aβ precursor protein (APP), tau and presenilin 1 (PS1) genes. Audiogenic seizures were elicited in a higher proportion of 3xTg-AD mice compared with wild type (WT) controls. Seizure susceptibility in 3xTg-AD mice was attenuated either by passive immunization with anti-human APP/Aβ antibody (6E10) or by blockade of metabotropic glutamate receptor 5 (mGluR5) with the selective antagonist, 2-methyl-6-(phenylethynyl)pyridine hydrochloride (MPEP). In in vitro hippocampal slices, suppression of synaptic inhibition with the GABAA receptor antagonist, bicuculline, induced prolonged epileptiform (>1.5 s in duration) ictal-like discharges in the CA3 neuronal network in the majority of the slices from 3xTg-AD mice. In contrast, only short epileptiform (<1.5 s in duration) interictal-like discharges were observed following bicuculline application in the CA3 region of WT slices. The ictal-like activity in CA3 region of the hippocampus was significantly reduced in the 6E10-immunized compared to the saline-treated 3xTg-AD mice. MPEP acutely suppressed the ictal-like discharges in 3xTg-AD slices. Remarkably, epileptiform discharge duration positively correlated with intraneuronal human (transgenic) APP/Aβ expression in the CA3 region of the hippocampus. Our data suggest that in a mouse model of familial AD, hypersynchronous network activity underlying seizure susceptibility precedes

Motion streaks in fast motion rivalry cause orientation-selective suppression.

PubMed

Apthorp, Deborah; Wenderoth, Peter; Alais, David

2009-05-14

We studied binocular rivalry between orthogonally translating arrays of random Gaussian blobs and measured the strength of rivalry suppression for static oriented probes. Suppression depth was quantified by expressing monocular probe thresholds during dominance relative to thresholds during suppression. Rivalry between two fast motions or two slow motions was compared in order to test the suggestion that fast-moving objects leave oriented "motion streaks" due to temporal integration (W. S. Geisler, 1999). If fast motions do produce motion streaks, then fast motion rivalry might also entail rivalry between the orthogonal streak orientations. We tested this using a static oriented probe that was aligned either parallel to the motion trajectory (hence collinear with the "streaks") or was orthogonal to the trajectory, predicting that rivalry suppression would be greater for parallel probes, and only for rivalry between fast motions. Results confirmed that suppression depth did depend on probe orientation for fast motion but not for slow motion. Further experiments showed that threshold elevations for the oriented probe during suppression exhibited clear orientation tuning. However, orientation-tuned elevations were also present during dominance, suggesting within-channel masking as the basis of the extra-deep suppression. In sum, the presence of orientation-dependent suppression in fast motion rivalry is consistent with the "motion streaks" hypothesis.

Suppression of Hydroxycinnamate Network Formation in Cell Walls of Rice Shoots Grown under Microgravity Conditions in Space

PubMed Central

Wakabayashi, Kazuyuki; Soga, Kouichi; Hoson, Takayuki; Kotake, Toshihisa; Yamazaki, Takashi; Higashibata, Akira; Ishioka, Noriaki; Shimazu, Toru; Fukui, Keiji; Osada, Ikuko; Kasahara, Haruo; Kamada, Motoshi

2015-01-01

Network structures created by hydroxycinnamate cross-links within the cell wall architecture of gramineous plants make the cell wall resistant to the gravitational force of the earth. In this study, the effects of microgravity on the formation of cell wall-bound hydroxycinnamates were examined using etiolated rice shoots simultaneously grown under artificial 1 g and microgravity conditions in the Cell Biology Experiment Facility on the International Space Station. Measurement of the mechanical properties of cell walls showed that shoot cell walls became stiff during the growth period and that microgravity suppressed this stiffening. Amounts of cell wall polysaccharides, cell wall-bound phenolic acids, and lignin in rice shoots increased as the shoot grew. Microgravity did not influence changes in the amounts of cell wall polysaccharides or phenolic acid monomers such as ferulic acid (FA) and p-coumaric acid, but it suppressed increases in diferulic acid (DFA) isomers and lignin. Activities of the enzymes phenylalanine ammonia-lyase (PAL) and cell wall-bound peroxidase (CW-PRX) in shoots also increased as the shoot grew. PAL activity in microgravity-grown shoots was almost comparable to that in artificial 1 g-grown shoots, while CW-PRX activity increased less in microgravity-grown shoots than in artificial 1 g-grown shoots. Furthermore, the increases in expression levels of some class III peroxidase genes were reduced under microgravity conditions. These results suggest that a microgravity environment modifies the expression levels of certain class III peroxidase genes in rice shoots, that the resultant reduction of CW-PRX activity may be involved in suppressing DFA formation and lignin polymerization, and that this suppression may cause a decrease in cross-linkages within the cell wall architecture. The reduction in intra-network structures may contribute to keeping the cell wall loose under microgravity conditions. PMID:26378793

Suppressing explosive synchronization by contrarians

NASA Astrophysics Data System (ADS)

Zhang, Xiyun; Guan, Shuguang; Zou, Yong; Chen, Xiaosong; Liu, Zonghua

2016-01-01

Explosive synchronization (ES) has recently received increasing attention and studies have mainly focused on the conditions of its onset so far. However, its inverse problem, i.e. the suppression of ES, has not been systematically studied so far. As ES is usually considered to be harmful in certain circumstances such as the cascading failure of power grids and epileptic seizure, etc., its suppression is definitely important and deserves to be studied. We here study this inverse problem by presenting an efficient approach to suppress ES from a first-order to second-order transition, without changing the intrinsic network structure. We find that ES can be suppressed by only changing a small fraction of oscillators into contrarians with negative couplings and the critical fraction for the transition from the first order to the second order increases with both the network size and the average degree. A brief theory is presented to explain the underlying mechanism. This finding underlines the importance of our method to improve the understanding of neural interactions underlying cognitive processes.

Satisfaction with social networks: an examination of socioemotional selectivity theory across cohorts.

PubMed

Lansford, J E; Sherman, A M; Antonucci, T C

1998-12-01

This study examines L. L. Carstensen's (1993, 1995) socioemotional selectivity theory within and across three cohorts spanning 4 decades. Socioemotional selectivity theory predicts that as individuals age, they narrow their social networks to devote more emotional resources to fewer relationships with close friends and family. Data from 3 cohorts of nationally representative samples were analyzed to determine whether respondents' satisfaction with the size of their social networks differed by age, cohort, or both. Results support socioemotional selectivity theory: More older adults than younger adults were satisfied with the current size of their social networks rather than wanting larger networks. These findings are consistent across all cohorts. Results are discussed with respect to social relationships across the life course.

Suppression of Aflatoxin Production in Aspergillus Species by Selected Peanut (Arachis hypogaea) Stilbenoids.

PubMed

Sobolev, Victor; Arias, Renee; Goodman, Kerestin; Walk, Travis; Orner, Valerie; Faustinelli, Paola; Massa, Alicia

2018-01-10

Aspergillus flavus is a soil fungus that commonly invades peanut seeds and often produces carcinogenic aflatoxins. Under favorable conditions, the fungus-challenged peanut plant produces and accumulates resveratrol and its prenylated derivatives in response to such an invasion. These prenylated stilbenoids are considered peanut antifungal phytoalexins. However, the mechanism of peanut-fungus interaction has not been sufficiently studied. We used pure peanut stilbenoids arachidin-1, arachidin-3, and chiricanine A to study their effects on the viability of and metabolite production by several important toxigenic Aspergillus species. Significant reduction or virtually complete suppression of aflatoxin production was revealed in feeding experiments in A. flavus, Aspergillus parasiticus, and Aspergillus nomius. Changes in morphology, spore germination, and growth rate were observed in A. flavus exposed to the selected peanut stilbenoids. Elucidation of the mechanism of aflatoxin suppression by peanut stilbenoids could provide strategies for preventing plant invasion by the fungi that produce aflatoxins.

Attentional Selection and Suppression in Children With Attention-Deficit/Hyperactivity Disorder.

PubMed

Wang, Encong; Sun, Li; Sun, Meirong; Huang, Jing; Tao, Ye; Zhao, Xixi; Wu, Zhanliang; Ding, Yulong; Newman, Daniel P; Bellgrove, Mark A; Wang, Yufeng; Song, Yan

2016-07-01

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder with prominent impairments in directing and sustaining attention. The aim of this study was to identify the neurophysiologic bases of attention deficits in ADHD, focusing on electroencephalography markers of attentional selection (posterior contralateral N2 [N2pc]) and suppression (distractor positivity [P D ]). The electroencephalography data were collected from 135 children 9-15 years old with and without ADHD while they searched for a shape target in either the absence (experiment 1) or the presence (experiment 2) of a salient but irrelevant color distractor. In experiment 1, the shape target elicited a smaller N2pc in children with ADHD (n = 38) compared with typically developing children (n = 36). The smaller N2pc amplitude predicted higher levels of inattentive symptoms in children with ADHD. Moreover, the target-elicited N2pc was followed by a positivity in typically developing children but not in children with ADHD. In experiment 2, the salient but irrelevant color distractor elicited a smaller P D component in children with ADHD (n = 32) compared with typically developing children (n = 29). The smaller P D predicted higher inattentive symptom severity as well as lower behavioral accuracy in children with ADHD. The correlation between N2pc/P D amplitudes and ADHD symptom severity suggests that these signals of attentional selection and suppression may serve as potential candidates for neurophysiologic markers of ADHD. Our findings provide a neurophysiologic basis for the subjective reports of attention deficits in children with ADHD and highlight the importance of spatial attention impairments in ADHD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Popularity and Adolescent Friendship Networks: Selection and Influence Dynamics

ERIC Educational Resources Information Center

Dijkstra, Jan Kornelis; Cillessen, Antonius H. N.; Borch, Casey

2013-01-01

This study examined the dynamics of popularity in adolescent friendship networks across 3 years in middle school. Longitudinal social network modeling was used to identify selection and influence in the similarity of popularity among friends. It was argued that lower status adolescents strive to enhance their status through befriending higher…

Smoking-based selection and influence in gender-segregated friendship networks: a social network analysis of adolescent smoking.

PubMed

Mercken, Liesbeth; Snijders, Tom A B; Steglich, Christian; Vertiainen, Erkki; de Vries, Hein

2010-07-01

The main goal of this study was to examine differences between adolescent male and female friendship networks regarding smoking-based selection and influence processes using newly developed social network analysis methods that allow the current state of continuously changing friendship networks to act as a dynamic constraint for changes in smoking behaviour, while allowing current smoking behaviour to be simultaneously a dynamic constraint for changes in friendship networks. Longitudinal design with four measurements. Nine junior high schools in Finland. A total of 1163 adolescents (mean age = 13.6 years) who participated in the control group of the ESFA (European Smoking prevention Framework Approach) study, including 605 males and 558 females. Smoking behaviour of adolescents, parents, siblings and friendship ties. Smoking-based selection of friends was found in male as well as female networks. However, support for influence among friends was found only in female networks. Furthermore, females and males were both influenced by parental smoking behaviour. In Finnish adolescents, both male and female smokers tend to select other smokers as friends but it appears that only females are influenced to smoke by their peer group. This suggests that prevention campaigns targeting resisting peer pressure may be more effective in adolescent girls than boys.

Hadoop neural network for parallel and distributed feature selection.

PubMed

Hodge, Victoria J; O'Keefe, Simon; Austin, Jim

2016-06-01

In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automated selection of computed tomography display parameters using neural networks

NASA Astrophysics Data System (ADS)

Zhang, Di; Neu, Scott; Valentino, Daniel J.

2001-07-01

A collection of artificial neural networks (ANN's) was trained to identify simple anatomical structures in a set of x-ray computed tomography (CT) images. These neural networks learned to associate a point in an image with the anatomical structure containing the point by using the image pixels located on the horizontal and vertical lines that ran through the point. The neural networks were integrated into a computer software tool whose function is to select an index into a list of CT window/level values from the location of the user's mouse cursor. Based upon the anatomical structure selected by the user, the software tool automatically adjusts the image display to optimally view the structure.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Social networks predict selective observation and information spread in ravens

PubMed Central

Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

2016-01-01

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

Joint Energy Supply and Routing Path Selection for Rechargeable Wireless Sensor Networks.

PubMed

Tang, Liangrui; Cai, Jinqi; Yan, Jiangyu; Zhou, Zhenyu

2018-06-17

The topic of network lifetime has been attracting much research attention because of its importance in prolonging the standing operation of battery-restricted wireless sensor networks, and the rechargeable wireless sensor network has emerged as a promising solution. In this paper, we propose a joint energy supply and routing path selection algorithm to extend the network lifetime based on an initiative power supply. We develop a two-stage energy replenishment strategy to supplement the energy consumption of nodes as much as possible. Furthermore, the influence of charging factors on the selection of next-hop nodes in data routing is considered. The simulation results show that our algorithm effectively prolong the network lifetime, and different demands of network delay and energy consumption can be obtained by dynamically adjusting parameters.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

Thyroid hormone suppresses hepatocarcinogenesis via DAPK2 and SQSTM1-dependent selective autophagy.

PubMed

Chi, Hsiang-Cheng; Chen, Shen-Liang; Tsai, Chung-Ying; Chuang, Wen-Yu; Huang, Ya-Hui; Tsai, Ming-Ming; Wu, Sheng-Ming; Sun, Cheng-Pu; Yeh, Chau-Ting; Lin, Kwang-Huei

2016-12-01

Recent studies have demonstrated a critical association between disruption of cellular thyroid hormone (TH) signaling and the incidence of hepatocellular carcinoma (HCC), but the underlying mechanisms remain largely elusive. Here, we showed that disruption of TH production results in a marked increase in progression of diethylnitrosamine (DEN)-induced HCC in a murine model, and conversely, TH administration suppresses the carcinogenic process via activation of autophagy. Inhibition of autophagy via treatment with chloroquine (CQ) or knockdown of ATG7 (autophagy-related 7) via adeno-associated virus (AAV) vectors, suppressed the protective effects of TH against DEN-induced hepatic damage and development of HCC. The involvement of autophagy in TH-mediated protection was further supported by data showing transcriptional activation of DAPK2 (death-associated protein kinase 2; a serine/threonine protein kinase), which enhanced the phosphorylation of SQSTM1/p62 (sequestosome 1) to promote selective autophagic clearance of protein aggregates. Ectopic expression of DAPK2 further attenuated DEN-induced hepatoxicity and DNA damage though enhanced autophagy, whereas, knockdown of DAPK2 displayed the opposite effect. The pathological significance of the TH-mediated hepatoprotective effect by DAPK2 was confirmed by the concomitant decrease in the expression of THRs and DAPK2 in matched HCC tumor tissues. Taken together, these findings indicate that TH promotes selective autophagy via induction of DAPK2-SQSTM1 cascade, which in turn protects hepatocytes from DEN-induced hepatotoxicity or carcinogenesis.

Small molecule schweinfurthins selectively inhibit cancer cell proliferation and mTOR/AKT signaling by interfering with trans-Golgi-network trafficking

PubMed Central

Bao, Xingfeng; Zheng, Wanjun; Sugi, Naoko Hata; Agarwala, Kishan L; Xu, Qunli; Wang, Zichun; Tendyke, Karen; Lee, Winnie; Parent, Lana; Li, Wei; Cheng, Hongsheng; Shen, Yongchun; Taylor, Noel; Dezso, Zoltan; Du, Hong; Kotake, Yoshihiko; Zhao, Nanding; Wang, John; Postema, Maarten; Woodall-Jappe, Mary; Takase, Yasutaka; Uenaka, Toshimitsu; Kingston, David G I; Nomoto, Kenichi

2015-01-01

Natural compound schweinfurthins are of considerable interest for novel therapy development because of their selective anti-proliferative activity against human cancer cells. We previously reported the isolation of highly active schweinfurthins E-H, and in the present study, mechanisms of the potent and selective anti-proliferation were investigated. We found that schweinfurthins preferentially inhibited the proliferation of PTEN deficient cancer cells by indirect inhibition of AKT phosphorylation. Mechanistically, schweinfurthins and their analogs arrested trans-Golgi-network trafficking, an intracellular vesicular trafficking system, resulting in the induction of endoplasmic reticulum stress and the suppression of both lipid raft-mediated PI3K activation and mTOR/RheB complex formation, which collectively led to an effective inhibition of mTOR/AKT signaling. The trans-Golgi-network traffic arresting effect of schweinfurthins was associated with their in vitro binding activity to oxysterol-binding proteins that are known to regulate intracellular vesicular trafficking. Moreover, schweinfurthins were found to be highly toxic toward PTEN-deficient B cell lymphoma cells, and displayed 2 orders of magnitude lower activity toward normal human peripheral blood mononuclear cells and primary fibroblasts in vitro. These results revealed a previously unrecognized role of schweinfurthins in regulating trans-Golgi-network trafficking, and linked mechanistically this cellular effect with mTOR/AKT signaling and with cancer cell survival and growth. Our findings suggest the schweinfurthin class of compounds as a novel approach to modulate oncogenic mTOR/AKT signaling for cancer treatment. PMID:25729885

a Method for the Seamlines Network Automatic Selection Based on Building Vector

NASA Astrophysics Data System (ADS)

Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

2018-04-01

In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

Selective pinning control of the average disease transmissibility in an HIV contact network

NASA Astrophysics Data System (ADS)

du Toit, E. F.; Craig, I. K.

2015-07-01

Medication is applied to the HIV-infected nodes of high-risk contact networks with the aim of controlling the spread of disease to a predetermined maximum level. This intervention, known as pinning control, is performed both selectively and randomly in the network. These strategies are applied to 300 independent realizations per reference level of incidence on connected undirectional networks without isolated components and varying in size from 100 to 10 000 nodes per network. It is shown that a selective on-off pinning control strategy can control the networks studied with limited steady-state error and, comparing the medians of the doses from both strategies, uses 51.3% less medication than random pinning of all infected nodes. Selective pinning could possibly be used by public health specialists to identify the maximum level of HIV incidence in a population that can be achieved in a constrained funding environment.

MicroRNA-integrated and network-embedded gene selection with diffusion distance.

PubMed

Huang, Di; Zhou, Xiaobo; Lyon, Christopher J; Hsueh, Willa A; Wong, Stephen T C

2010-10-29

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways.

Selective Class I HDAC Inhibition Suppresses Hypoxia-Induced Cardiopulmonary Remodeling Through an Anti-Proliferative Mechanism

PubMed Central

Cavasin, Maria A.; Demos-Davies, Kim; Horn, Todd R.; Walker, Lori A.; Lemon, Douglas D.; Birdsey, Nicholas; Weiser-Evans, Mary C. M.; Harral, Jules; Irwin, David C.; Anwar, Adil; Yeager, Michael E.; Li, Min; Watson, Peter A.; Nemenoff, Raphael A.; Buttrick, Peter M.; Stenmark, Kurt R.; McKinsey, Timothy A.

2012-01-01

Rationale Histone deacetylase (HDAC) inhibitors are efficacious in models of hypertension-induced left ventricular (LV) heart failure. The consequences of HDAC inhibition in the context of pulmonary hypertension (PH) with associated right ventricular (RV) cardiac remodeling are poorly understood. Objective This study was performed to assess the utility of selective small molecule inhibitors of class I HDACs in a pre-clinical model of PH. Methods and Results Rats were exposed to hypobaric hypoxia for 3 weeks in the absence or presence of a benzamide HDAC inhibitor, MGCD0103, which selectively inhibits class I HDACs −1, −2 and −3. The compound reduced pulmonary arterial pressure (PAP) more dramatically than tadalafil, a standard-of-care therapy for human PH that functions as a vasodilator. MGCD0103 improved pulmonary artery (PA) acceleration time (PAAT) and reduced systolic notching of the PA flow envelope, suggesting a positive impact of the HDAC inhibitor on pulmonary vascular remodeling and stiffening. Similar results were obtained with an independent class I HDAC-selective inhibitor, MS-275. Reduced PAP in MGCD0103-treated animals was associated with blunted pulmonary arterial wall thickening due to suppression of smooth muscle cell proliferation. RV function was maintained in MGCD0103 treated animals. Although the class I HDAC inhibitor only modestly reduced RV hypertrophy, it had multiple beneficial effects on the RV, which included suppression of pathological gene expression, inhibition of pro-apoptotic caspase activity, and repression of pro-inflammatory protein expression. Conclusions By targeting distinct pathogenic mechanisms, isoform-selective HDAC inhibitors have potential as novel therapeutics for PH that will complement vasodilator standards-of-care. PMID:22282194

A New HIV Prevention Network Approach: Sociometric Peer Change Agent Selection

PubMed Central

Schneider, John A.; Zhou, A. Ning; Laumann, Edward O.

2014-01-01

Internationally, the Peer Change Agent (PCA) model is the most frequently used conceptual framework for HIV prevention. Change agents themselves can be more important than the messages they convey. PCA selection is operationalized via heterogeneous methods based upon individual-level attributes. A sociometric position selection strategy, however, could increase peer influence potency and halt transmission at key network locations. In this study, we selected candidate PCAs based upon relative sociometric bridging and centrality scores and assessed their attributes in comparison to one another and to existing peer educators. We focused upon an emerging HIV epidemic among men who have sex with men in Southern India in 2011. PCAs selected based on their bridging score were more likely to be innovators when compared to other centrally-located PCAs, to PCAs located on the periphery, and to existing peer educators. We also found that sociodemographic attributes and risk behaviors were similar across all candidate PCAs, but risk behaviors of existing peer educators differed. Existing peer educators were more likely to engage in higher risk behavior such as receiving money for sex when compared to sociometrically selected peer changes agents. These existing peer educators were also more likely to exhibit leadership qualities within the overall network; they were, however, just as likely as other non-trained candidate peer change agents to report important HIV intravention behavior (encouraging condoms within their network). The importance of identifying bridges who may be able to diffuse innovation more effectively within high risk HIV networks is especially critical given recent efficacy data from novel HIV prevention interventions such as pre-exposure prophylaxis. Moreover, while existing peer educators were more likely to be leaders in our analysis, using peer educators with high risk behavior may have limited utility in enacting behavior change among sex worker peers or

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

A Lifetime Maximization Relay Selection Scheme in Wireless Body Area Networks.

PubMed

Zhang, Yu; Zhang, Bing; Zhang, Shi

2017-06-02

Network Lifetime is one of the most important metrics in Wireless Body Area Networks (WBANs). In this paper, a relay selection scheme is proposed under the topology constrains specified in the IEEE 802.15.6 standard to maximize the lifetime of WBANs through formulating and solving an optimization problem where relay selection of each node acts as optimization variable. Considering the diversity of the sensor nodes in WBANs, the optimization problem takes not only energy consumption rate but also energy difference among sensor nodes into account to improve the network lifetime performance. Since it is Non-deterministic Polynomial-hard (NP-hard) and intractable, a heuristic solution is then designed to rapidly address the optimization. The simulation results indicate that the proposed relay selection scheme has better performance in network lifetime compared with existing algorithms and that the heuristic solution has low time complexity with only a negligible performance degradation gap from optimal value. Furthermore, we also conduct simulations based on a general WBAN model to comprehensively illustrate the advantages of the proposed algorithm. At the end of the evaluation, we validate the feasibility of our proposed scheme via an implementation discussion.

Network characteristics for server selection in online games

NASA Astrophysics Data System (ADS)

Claypool, Mark

2008-01-01

Online gameplay is impacted by the network characteristics of players connected to the same server. Unfortunately, the network characteristics of online game servers are not well-understood, particularly for groups that wish to play together on the same server. As a step towards a remedy, this paper presents analysis of an extensive set of measurements of game servers on the Internet. Over the course of many months, actual Internet game servers were queried simultaneously by twenty-five emulated game clients, with both servers and clients spread out on the Internet. The data provides statistics on the uptime and populations of game servers over a month long period an an in-depth look at the suitability for game servers for multi-player server selection, concentrating on characteristics critical to playability--latency and fairness. Analysis finds most game servers have latencies suitable for third-person and omnipresent games, such as real-time strategy, sports and role-playing games, providing numerous server choices for game players. However, far fewer game servers have the low latencies required for first-person games, such as shooters or race games. In all cases, groups that wish to play together have a greatly reduced set of servers from which to choose because of inherent unfairness in server latencies and server selection is particularly limited as the group size increases. These results hold across different game types and even across different generations of games. The data should be useful for game developers and network researchers that seek to improve game server selection, whether for single or multiple players.

Performance Analysis of Relay Subset Selection for Amplify-and-Forward Cognitive Relay Networks

PubMed Central

Qureshi, Ijaz Mansoor; Malik, Aqdas Naveed; Zubair, Muhammad

2014-01-01

Cooperative communication is regarded as a key technology in wireless networks, including cognitive radio networks (CRNs), which increases the diversity order of the signal to combat the unfavorable effects of the fading channels, by allowing distributed terminals to collaborate through sophisticated signal processing. Underlay CRNs have strict interference constraints towards the secondary users (SUs) active in the frequency band of the primary users (PUs), which limits their transmit power and their coverage area. Relay selection offers a potential solution to the challenges faced by underlay networks, by selecting either single best relay or a subset of potential relay set under different design requirements and assumptions. The best relay selection schemes proposed in the literature for amplify-and-forward (AF) based underlay cognitive relay networks have been very well studied in terms of outage probability (OP) and bit error rate (BER), which is deficient in multiple relay selection schemes. The novelty of this work is to study the outage behavior of multiple relay selection in the underlay CRN and derive the closed-form expressions for the OP and BER through cumulative distribution function (CDF) of the SNR received at the destination. The effectiveness of relay subset selection is shown through simulation results. PMID:24737980

Influence maximization based on partial network structure information: A comparative analysis on seed selection heuristics

NASA Astrophysics Data System (ADS)

Erkol, Şirag; Yücel, Gönenç

In this study, the problem of seed selection is investigated. This problem is mainly treated as an optimization problem, which is proved to be NP-hard. There are several heuristic approaches in the literature which mostly use algorithmic heuristics. These approaches mainly focus on the trade-off between computational complexity and accuracy. Although the accuracy of algorithmic heuristics are high, they also have high computational complexity. Furthermore, in the literature, it is generally assumed that complete information on the structure and features of a network is available, which is not the case in most of the times. For the study, a simulation model is constructed, which is capable of creating networks, performing seed selection heuristics, and simulating diffusion models. Novel metric-based seed selection heuristics that rely only on partial information are proposed and tested using the simulation model. These heuristics use local information available from nodes in the synthetically created networks. The performances of heuristics are comparatively analyzed on three different network types. The results clearly show that the performance of a heuristic depends on the structure of a network. A heuristic to be used should be selected after investigating the properties of the network at hand. More importantly, the approach of partial information provided promising results. In certain cases, selection heuristics that rely only on partial network information perform very close to similar heuristics that require complete network data.

Selection of Multiarmed Spiral Waves in a Regular Network of Neurons

PubMed Central

Hu, Bolin; Ma, Jun; Tang, Jun

2013-01-01

Formation and selection of multiarmed spiral wave due to spontaneous symmetry breaking are investigated in a regular network of Hodgkin-Huxley neuron by changing the excitability and imposing spatial forcing currents on the neurons in the network. The arm number of the multiarmed spiral wave is dependent on the distribution of spatial forcing currents and excitability diversity in the network, and the selection criterion for supporting multiarmed spiral waves is discussed. A broken spiral segment is measured by a short polygonal line connected by three adjacent points (controlled nodes), and a double-spiral wave can be developed from the spiral segment. Multiarmed spiral wave is formed when a group of double-spiral waves rotate in the same direction in the network. In the numerical studies, a group of controlled nodes are selected and spatial forcing currents are imposed on these nodes, and our results show that l-arm stable spiral wave (l = 2, 3, 4,...8) can be induced to occupy the network completely. It is also confirmed that low excitability is critical to induce multiarmed spiral waves while high excitability is important to propagate the multiarmed spiral wave outside so that distinct multiarmed spiral wave can occupy the network completely. Our results confirm that symmetry breaking of target wave in the media accounts for emergence of multiarmed spiral wave, which can be developed from a group of spiral waves with single arm under appropriate condition, thus the potential formation mechanism of multiarmed spiral wave in the media is explained. PMID:23935966

Using principal component analysis for selecting network behavioral anomaly metrics

NASA Astrophysics Data System (ADS)

Gregorio-de Souza, Ian; Berk, Vincent; Barsamian, Alex

2010-04-01

This work addresses new approaches to behavioral analysis of networks and hosts for the purposes of security monitoring and anomaly detection. Most commonly used approaches simply implement anomaly detectors for one, or a few, simple metrics and those metrics can exhibit unacceptable false alarm rates. For instance, the anomaly score of network communication is defined as the reciprocal of the likelihood that a given host uses a particular protocol (or destination);this definition may result in an unrealistically high threshold for alerting to avoid being flooded by false positives. We demonstrate that selecting and adapting the metrics and thresholds, on a host-by-host or protocol-by-protocol basis can be done by established multivariate analyses such as PCA. We will show how to determine one or more metrics, for each network host, that records the highest available amount of information regarding the baseline behavior, and shows relevant deviances reliably. We describe the methodology used to pick from a large selection of available metrics, and illustrate a method for comparing the resulting classifiers. Using our approach we are able to reduce the resources required to properly identify misbehaving hosts, protocols, or networks, by dedicating system resources to only those metrics that actually matter in detecting network deviations.

Gene Expression Network Reconstruction by Convex Feature Selection when Incorporating Genetic Perturbations

PubMed Central

Logsdon, Benjamin A.; Mezey, Jason

2010-01-01

Cellular gene expression measurements contain regulatory information that can be used to discover novel network relationships. Here, we present a new algorithm for network reconstruction powered by the adaptive lasso, a theoretically and empirically well-behaved method for selecting the regulatory features of a network. Any algorithms designed for network discovery that make use of directed probabilistic graphs require perturbations, produced by either experiments or naturally occurring genetic variation, to successfully infer unique regulatory relationships from gene expression data. Our approach makes use of appropriately selected cis-expression Quantitative Trait Loci (cis-eQTL), which provide a sufficient set of independent perturbations for maximum network resolution. We compare the performance of our network reconstruction algorithm to four other approaches: the PC-algorithm, QTLnet, the QDG algorithm, and the NEO algorithm, all of which have been used to reconstruct directed networks among phenotypes leveraging QTL. We show that the adaptive lasso can outperform these algorithms for networks of ten genes and ten cis-eQTL, and is competitive with the QDG algorithm for networks with thirty genes and thirty cis-eQTL, with rich topologies and hundreds of samples. Using this novel approach, we identify unique sets of directed relationships in Saccharomyces cerevisiae when analyzing genome-wide gene expression data for an intercross between a wild strain and a lab strain. We recover novel putative network relationships between a tyrosine biosynthesis gene (TYR1), and genes involved in endocytosis (RCY1), the spindle checkpoint (BUB2), sulfonate catabolism (JLP1), and cell-cell communication (PRM7). Our algorithm provides a synthesis of feature selection methods and graphical model theory that has the potential to reveal new directed regulatory relationships from the analysis of population level genetic and gene expression data. PMID:21152011

Distribution of Orientation Selectivity in Recurrent Networks of Spiking Neurons with Different Random Topologies

PubMed Central

Sadeh, Sadra; Rotter, Stefan

2014-01-01

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity. PMID:25469704

Patterns of population differentiation and natural selection on the celiac disease background risk network.

PubMed

Sams, Aaron; Hawks, John

2013-01-01

Celiac disease is a common small intestinal inflammatory condition induced by wheat gluten and related proteins from rye and barley. Left untreated, the clinical presentation of CD can include failure to thrive, malnutrition, and distension in juveniles. The disease can additionally lead to vitamin deficiencies, anemia, and osteoporosis. Therefore, CD potentially negatively affected fitness in past populations utilizing wheat, barley, and rye. Previous analyses of CD risk variants have uncovered evidence for positive selection on some of these loci. These studies also suggest the possibility that risk for common autoimmune conditions such as CD may be the result of positive selection on immune related loci in the genome to fight infection. Under this evolutionary scenario, disease phenotypes may be a trade-off from positive selection on immunity. If this hypothesis is generally true, we can expect to find a signal of natural selection when we survey across the network of loci known to influence CD risk. This study examines the non-HLA autosomal network of gene loci associated with CD risk in Europe. We reject the null hypothesis of neutrality on this network of CD risk loci. Additionally, we can localize evidence of selection in time and space by adding information from the genome of the Tyrolean Iceman. While we can show significant differentiation between continental regions across the CD network, the pattern of evidence is not consistent with primarily recent (Holocene) selection across this network in Europe. Further localization of ancient selection on this network may illuminate the ecological pressures acting on the immune system during this critically interesting phase of our evolution.

Open Peer Review by a Selected-Papers Network

PubMed Central

Lee, Christopher

2011-01-01

A selected-papers (SP) network is a network in which researchers who read, write, and review articles subscribe to each other based on common interests. Instead of reviewing a manuscript in secret for the Editor of a journal, each reviewer simply publishes his review (typically of a paper he wishes to recommend) to his SP network subscribers. Once the SP network reviewers complete their review decisions, the authors can invite any journal editor they want to consider these reviews and initial audience size, and make a publication decision. Since all impact assessment, reviews, and revisions are complete, this decision process should be short. I show how the SP network can provide a new way of measuring impact, catalyze the emergence of new subfields, and accelerate discovery in existing fields, by providing each reader a fine-grained filter for high-impact. I present a three phase plan for building a basic SP network, and making it an effective peer review platform that can be used by journals, conferences, users of repositories such as arXiv, and users of search engines such as PubMed. I show how the SP network can greatly improve review and dissemination of research articles in areas that are not well-supported by existing journals. Finally, I illustrate how the SP network concept can work well with existing publication services such as journals, conferences, arXiv, PubMed, and online citation management sites. PMID:22291635

Selective serotonin reuptake inhibitor suppression of HIV infectivity and replication.

PubMed

Benton, Tami; Lynch, Kevin; Dubé, Benoit; Gettes, David R; Tustin, Nancy B; Ping Lai, Jian; Metzger, David S; Blume, Joshua; Douglas, Steven D; Evans, Dwight L

2010-11-01

To test the hypothesis that the selective serotonin reuptake inhibitor (SSRI) citalopram would down-regulate human immunodeficiency virus (HIV) infectivity and that the greatest effects would be seen in people with depression. Depression is a risk factor for morbidity and mortality in HIV/acquired immune deficiency syndrome. Serotonin (5-HT) neurotransmission has been implicated in the pathobiology of depression, and pharmacologic therapies for depression target this system. The 5-HT transporter and 5-HT receptors are widely distributed throughout the central nervous and immune systems. Depression has been associated with suppression of natural killer cells and CD8(+) lymphocytes, key regulators of HIV infection. Ex vivo models for acute and chronic HIV infection were used to study the effects of citalopram on HIV viral infection and replication in 48 depressed and nondepressed women. For both the acute and chronic infection models, HIV reverse transcriptase activity was measured in the citalopram treatment condition and the control condition. The SSRI significantly down-regulated the reverse transcriptase response in both the acute and chronic infection models. Specifically, citalopram significantly decreased the acute HIV infectivity of macrophages. Citalopram also significantly decreased HIV viral replication in the latently infected T-cell line and in the latently infected macrophage cell line. There was no difference in down-regulation by depression status. These studies suggest that an SSRI enhances natural killer/CD8 noncytolytic HIV suppression in HIV/acquired immune deficiency syndrome and decreases HIV viral infectivity of macrophages, ex vivo, suggesting the need for in vivo studies to determine a potential role for agents targeting serotonin in the host defense against HIV.

A joint technique for sidelobe suppression and peak-to-average power ratio reduction in non-contiguous OFDM-based cognitive radio networks

NASA Astrophysics Data System (ADS)

Sivadas, Namitha Arackal; Mohammed, Sameer Saheerudeen

2017-02-01

In non-contiguous orthogonal frequency division multiplexing (NC-OFDM)-based interweave cognitive radio networks, the sidelobe power of secondary users (SUs) must be strictly controlled to avoid the interference between the SUs and the primary users (PUs) of the adjacent bands. Similarly, the inherent issue of high peak-to-average power ratio (PAPR) of the OFDM signal is another drawback of the cognitive radio communication system based on the NC-OFDM technology. A few methods are available in the literature to solve either of these problems individually, while in this paper, we propose a new method for the joint minimisation of sidelobe power and PAPR in NC-OFDM-based cognitive radio networks using Zadoff-Chu (ZC) sequence. In this method, the sidelobe power suppression of SUs is benefited by PUs and the PAPR is reduced for SUs. We modelled a new optimisation problem for minimising the sidelobe power with a constraint on the maximum tolerable PAPR and sidelobe power. The proper selection of ZC sequence, which is crucial for minimising both the issues simultaneously, is achieved by solving the proposed optimisation problem. The proposed technique is shown to provide 7 dB and 20 dB reduction in PAPR and sidelobe power, respectively, without causing any signal distortion along with the improvement in bit error rate (BER) performance.

Elaboration versus suppression of cued memories: influence of memory recall instruction and success on parietal lobe, default network, and hippocampal activity.

PubMed

Gimbel, Sarah I; Brewer, James B

2014-01-01

Functional imaging studies of episodic memory retrieval consistently report task-evoked and memory-related activity in the medial temporal lobe, default network and parietal lobe subregions. Associated components of memory retrieval, such as attention-shifts, search, retrieval success, and post-retrieval processing also influence regional activity, but these influences remain ill-defined. To better understand how top-down control affects the neural bases of memory retrieval, we examined how regional activity responses were modulated by task goals during recall success or failure. Specifically, activity was examined during memory suppression, recall, and elaborative recall of paired-associates. Parietal lobe was subdivided into dorsal (BA 7), posterior ventral (BA 39), and anterior ventral (BA 40) regions, which were investigated separately to examine hypothesized distinctions in sub-regional functional responses related to differential attention-to-memory and memory strength. Top-down suppression of recall abolished memory strength effects in BA 39, which showed a task-negative response, and BA 40, which showed a task-positive response. The task-negative response in default network showed greater negatively-deflected signal for forgotten pairs when task goals required recall. Hippocampal activity was task-positive and was influenced by memory strength only when task goals required recall. As in previous studies, we show a memory strength effect in parietal lobe and hippocampus, but we show that this effect is top-down controlled and sensitive to whether the subject is trying to suppress or retrieve a memory. These regions are all implicated in memory recall, but their individual activity patterns show distinct memory-strength-related responses when task goals are varied. In parietal lobe, default network, and hippocampus, top-down control can override the commonly identified effects of memory strength.

Elaboration versus Suppression of Cued Memories: Influence of Memory Recall Instruction and Success on Parietal Lobe, Default Network, and Hippocampal Activity

PubMed Central

Gimbel, Sarah I.; Brewer, James B.

2014-01-01

Functional imaging studies of episodic memory retrieval consistently report task-evoked and memory-related activity in the medial temporal lobe, default network and parietal lobe subregions. Associated components of memory retrieval, such as attention-shifts, search, retrieval success, and post-retrieval processing also influence regional activity, but these influences remain ill-defined. To better understand how top-down control affects the neural bases of memory retrieval, we examined how regional activity responses were modulated by task goals during recall success or failure. Specifically, activity was examined during memory suppression, recall, and elaborative recall of paired-associates. Parietal lobe was subdivided into dorsal (BA 7), posterior ventral (BA 39), and anterior ventral (BA 40) regions, which were investigated separately to examine hypothesized distinctions in sub-regional functional responses related to differential attention-to-memory and memory strength. Top-down suppression of recall abolished memory strength effects in BA 39, which showed a task-negative response, and BA 40, which showed a task-positive response. The task-negative response in default network showed greater negatively-deflected signal for forgotten pairs when task goals required recall. Hippocampal activity was task-positive and was influenced by memory strength only when task goals required recall. As in previous studies, we show a memory strength effect in parietal lobe and hippocampus, but we show that this effect is top-down controlled and sensitive to whether the subject is trying to suppress or retrieve a memory. These regions are all implicated in memory recall, but their individual activity patterns show distinct memory-strength-related responses when task goals are varied. In parietal lobe, default network, and hippocampus, top-down control can override the commonly identified effects of memory strength. PMID:24586492

Bully Victimization: Selection and Influence Within Adolescent Friendship Networks and Cliques.

PubMed

Lodder, Gerine M A; Scholte, Ron H J; Cillessen, Antonius H N; Giletta, Matteo

2016-01-01

Adolescents tend to form friendships with similar peers and, in turn, their friends further influence adolescents' behaviors and attitudes. Emerging work has shown that these selection and influence processes also might extend to bully victimization. However, no prior work has examined selection and influence effects involved in bully victimization within cliques, despite theoretical account emphasizing the importance of cliques in this regard. This study examined selection and influence processes in adolescence regarding bully victimization both at the level of the entire friendship network and the level of cliques. We used a two-wave design (5-month interval). Participants were 543 adolescents (50.1% male, Mage = 15.8) in secondary education. Stochastic actor-based models indicated that at the level of the larger friendship network, adolescents tended to select friends with similar levels of bully victimization as they themselves. In addition, adolescent friends influenced each other in terms of bully victimization over time. Actor Parter Interdependence models showed that similarities in bully victimization between clique members were not due to selection of clique members. For boys, average clique bully victimization predicted individual bully victimization over time (influence), but not vice versa. No influence was found for girls, indicating that different mechanisms may underlie friend influence on bully victimization for girls and boys. The differences in results at the level of the larger friendship network versus the clique emphasize the importance of taking the type of friendship ties into account in research on selection and influence processes involved in bully victimization.

Selective suppression of endothelial cytokine production by progesterone receptor.

PubMed

Goddard, Lauren M; Ton, Amy N; Org, Tõnis; Mikkola, Hanna K A; Iruela-Arispe, M Luisa

2013-01-01

Steroid hormones are well-recognized suppressors of the inflammatory response, however, their cell- and tissue-specific effects in the regulation of inflammation are far less understood, particularly for the sex-related steroids. To determine the contribution of progesterone in the endothelium, we have characterized and validated an in vitro culture system in which human umbilical vein endothelial cells constitutively express human progesterone receptor (PR). Using next generation RNA-sequencing, we identified a selective group of cytokines that are suppressed by progesterone both under physiological conditions and during pathological activation by lipopolysaccharide. In particular, IL-6, IL-8, CXCL2/3, and CXCL1 were found to be direct targets of PR, as determined by ChIP-sequencing. Regulation of these cytokines by progesterone was also confirmed by bead-based multiplex cytokine assays and quantitative PCR. These findings provide a novel role for PR in the direct regulation of cytokine levels secreted by the endothelium. They also suggest that progesterone-PR signaling in the endothelium directly impacts leukocyte trafficking in PR-expressing tissues. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

The Stochastic Evolutionary Game for a Population of Biological Networks Under Natural Selection

PubMed Central

Chen, Bor-Sen; Ho, Shih-Ju

2014-01-01

In this study, a population of evolutionary biological networks is described by a stochastic dynamic system with intrinsic random parameter fluctuations due to genetic variations and external disturbances caused by environmental changes in the evolutionary process. Since information on environmental changes is unavailable and their occurrence is unpredictable, they can be considered as a game player with the potential to destroy phenotypic stability. The biological network needs to develop an evolutionary strategy to improve phenotypic stability as much as possible, so it can be considered as another game player in the evolutionary process, ie, a stochastic Nash game of minimizing the maximum network evolution level caused by the worst environmental disturbances. Based on the nonlinear stochastic evolutionary game strategy, we find that some genetic variations can be used in natural selection to construct negative feedback loops, efficiently improving network robustness. This provides larger genetic robustness as a buffer against neutral genetic variations, as well as larger environmental robustness to resist environmental disturbances and maintain a network phenotypic traits in the evolutionary process. In this situation, the robust phenotypic traits of stochastic biological networks can be more frequently selected by natural selection in evolution. However, if the harbored neutral genetic variations are accumulated to a sufficiently large degree, and environmental disturbances are strong enough that the network robustness can no longer confer enough genetic robustness and environmental robustness, then the phenotype robustness might break down. In this case, a network phenotypic trait may be pushed from one equilibrium point to another, changing the phenotypic trait and starting a new phase of network evolution through the hidden neutral genetic variations harbored in network robustness by adaptive evolution. Further, the proposed evolutionary game is extended to

A network of networks model to study phase synchronization using structural connection matrix of human brain

NASA Astrophysics Data System (ADS)

Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

2018-04-01

The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

Synchronization stability and pattern selection in a memristive neuronal network.

PubMed

Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

2017-11-01

Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

Synchronization stability and pattern selection in a memristive neuronal network

NASA Astrophysics Data System (ADS)

Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

2017-11-01

Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

Selective impairment of attention networks in breast cancer patients receiving chemotherapy treatment.

PubMed

Chen, Xingui; Li, Jingjing; Ren, Jing; Hu, Xinglong; Zhu, Chunyan; Tian, Yanghua; Hu, Panpan; Ma, Huijuan; Yu, Fengqiong; Wang, Kai

2014-10-01

Complaints about attention disorders are common among breast cancer survivors who have undergone chemotherapy treatment. However, it is not known whether these complaints indicate a global attention deficit or the selective impairment of attention networks. This study sought to investigate the attentional abilities of breast cancer patients after chemotherapy treatment using the attention network test (ANT). The participants included breast cancer patients who had undergone chemotherapy (CT, N = 58), patients who had not undergone chemotherapy (non-CT, N = 53), and matched healthy controls (HC, N = 55). All participants completed the ANT, which provides measures of three independent attention networks (alerting, orienting, and executive control) and neuropsychological background tests. Our results indicated that the chemotherapy-treated breast cancer patients had significant deficits in the alerting and executive control networks but not in the orienting network. The CT group scored significantly lower in several cognitive tasks, including attention, memory, and information processing tasks, relative to the other two groups. Additionally, significant correlations were found between information processing and the efficiency of the executive control network within the CT group. These results suggest that the three attention networks were selectively impaired following chemotherapy treatment, which affected different brain areas in the breast cancer survivors. Copyright © 2014 John Wiley & Sons, Ltd.

Teen Alcohol Use and Social Networks: The Contributions of Friend Influence and Friendship Selection

PubMed Central

Cheadle, Jacob E; Walsemann, Katrina M; Goosby, Bridget J

2015-01-01

Background We evaluated the contributions of teen alcohol use to the formation and continuation of new and existing friendships while in turn estimating the influence of friend drinking on individuals’ regular use and heavy drinking. Method Longitudinal network analysis was used to assess the mutual influences between teen drinking and social networks among adolescents in two large Add Health schools where full network data was collected three times. Friendship processes were disaggregated into the formation of new friendships and the continuation of existing friendships in a joint model isolating friendship selection and friend influences. Results Friends have a modest influence on one another when selection is controlled. Selection is more complicated than prior studies suggest, and is only related to new friendships and not their duration in the largest school. Alcohol use predicts decreasing popularity in some cases, and popularity does not predict alcohol consumption. Conclusion Intervention efforts should continue pursuing strategies that mitigate negative peer influences. The development of socializing opportunities that facilitate relationship opportunities to select on healthy behaviors also appears promising. Future work preventing teen substance use should incorporate longitudinal network assessments to determine whether programs promote protective peer relationships in addition to how treatment effects diffuse through social networks. PMID:26692436

Cotton genotypes selection through artificial neural networks.

PubMed

Júnior, E G Silva; Cardoso, D B O; Reis, M C; Nascimento, A F O; Bortolin, D I; Martins, M R; Sousa, L B

2017-09-27

Breeding programs currently use statistical analysis to assist in the identification of superior genotypes at various stages of a cultivar's development. Differently from these analyses, the computational intelligence approach has been little explored in genetic improvement of cotton. Thus, this study was carried out with the objective of presenting the use of artificial neural networks as auxiliary tools in the improvement of the cotton to improve fiber quality. To demonstrate the applicability of this approach, this research was carried out using the evaluation data of 40 genotypes. In order to classify the genotypes for fiber quality, the artificial neural networks were trained with replicate data of 20 genotypes of cotton evaluated in the harvests of 2013/14 and 2014/15, regarding fiber length, uniformity of length, fiber strength, micronaire index, elongation, short fiber index, maturity index, reflectance degree, and fiber quality index. This quality index was estimated by means of a weighted average on the determined score (1 to 5) of each characteristic of the HVI evaluated, according to its industry standards. The artificial neural networks presented a high capacity of correct classification of the 20 selected genotypes based on the fiber quality index, so that when using fiber length associated with the short fiber index, fiber maturation, and micronaire index, the artificial neural networks presented better results than using only fiber length and previous associations. It was also observed that to submit data of means of new genotypes to the neural networks trained with data of repetition, provides better results of classification of the genotypes. When observing the results obtained in the present study, it was verified that the artificial neural networks present great potential to be used in the different stages of a genetic improvement program of the cotton, aiming at the improvement of the fiber quality of the future cultivars.

Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion

NASA Astrophysics Data System (ADS)

Lin, Yi-Kuei; Yeh, Cheng-Ta

2013-05-01

From the perspective of supply chain management, the selected carrier plays an important role in freight delivery. This article proposes a new criterion of multi-commodity reliability and optimises the carrier selection based on such a criterion for logistics networks with routes and nodes, over which multiple commodities are delivered. Carrier selection concerns the selection of exactly one carrier to deliver freight on each route. The capacity of each carrier has several available values associated with a probability distribution, since some of a carrier's capacity may be reserved for various orders. Therefore, the logistics network, given any carrier selection, is a multi-commodity multi-state logistics network. Multi-commodity reliability is defined as a probability that the logistics network can satisfy a customer's demand for various commodities, and is a performance indicator for freight delivery. To solve this problem, this study proposes an optimisation algorithm that integrates genetic algorithm, minimal paths and Recursive Sum of Disjoint Products. A practical example in which multi-sized LCD monitors are delivered from China to Germany is considered to illustrate the solution procedure.

Selection for territory acquisition is modulated by social network structure in a wild songbird

PubMed Central

Farine, D R; Sheldon, B C

2015-01-01

The social environment may be a key mediator of selection that operates on animals. In many cases, individuals may experience selection not only as a function of their phenotype, but also as a function of the interaction between their phenotype and the phenotypes of the conspecifics they associate with. For example, when animals settle after dispersal, individuals may benefit from arriving early, but, in many cases, these benefits will be affected by the arrival times of other individuals in their local environment. We integrated a recently described method for calculating assortativity on weighted networks, which is the correlation between an individual's phenotype and that of its associates, into an existing framework for measuring the magnitude of social selection operating on phenotypes. We applied this approach to large-scale data on social network structure and the timing of arrival into the breeding area over three years. We found that late-arriving individuals had a reduced probability of breeding. However, the probability of breeding was also influenced by individuals’ social networks. Associating with late-arriving conspecifics increased the probability of successfully acquiring a breeding territory. Hence, social selection could offset the effects of nonsocial selection. Given parallel theoretical developments of the importance of local network structure on population processes, and increasing data being collected on social networks in free-living populations, the integration of these concepts could yield significant insights into social evolution. PMID:25611344

Coevolution of cooperation and network structure under natural selection

NASA Astrophysics Data System (ADS)

Yang, D.-P.; Lin, H.; Shuai, J. W.

2011-02-01

A coevolution model by coupling mortality and fertility selection is introduced to investigate the evolution of cooperation and network structure in the prisoner's dilemma game. The cooperation level goes through a continuous phase transition vs. defection temptation b for low mortality selection intensity β and through a discontinuous one for infinite β. The cooperation level is enhanced most at β≈1 for any b. The local and global properties of the network structure, such as cluster and cooperating k-core, are investigated for the understanding of cooperation evolution. Cooperation is promoted by forming a tight cooperating k-core at moderate β, but too large β will destroy the cooperating k-core rapidly resulting in a rapid drop of the cooperation level. Importantly, the infinite β changes the normalized sucker's payoff S from 0 to 1-b and its dynamics of the cooperation level undergoes a very slow power-law decay, which leads the evolution into the regime of neutral evolution.

Suppressing epidemics on networks by exploiting observer nodes.

PubMed

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Suppressing epidemics on networks by exploiting observer nodes

NASA Astrophysics Data System (ADS)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

PubMed

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

Access Selection Algorithm of Heterogeneous Wireless Networks for Smart Distribution Grid Based on Entropy-Weight and Rough Set

NASA Astrophysics Data System (ADS)

Xiang, Min; Qu, Qinqin; Chen, Cheng; Tian, Li; Zeng, Lingkang

2017-11-01

To improve the reliability of communication service in smart distribution grid (SDG), an access selection algorithm based on dynamic network status and different service types for heterogeneous wireless networks was proposed. The network performance index values were obtained in real time by multimode terminal and the variation trend of index values was analyzed by the growth matrix. The index weights were calculated by entropy-weight and then modified by rough set to get the final weights. Combining the grey relational analysis to sort the candidate networks, and the optimum communication network is selected. Simulation results show that the proposed algorithm can implement dynamically access selection in heterogeneous wireless networks of SDG effectively and reduce the network blocking probability.

Database Software Selection for the Egyptian National STI Network.

ERIC Educational Resources Information Center

Slamecka, Vladimir

The evaluation and selection of information/data management system software for the Egyptian National Scientific and Technical (STI) Network are described. An overview of the state-of-the-art of database technology elaborates on the differences between information retrieval and database management systems (DBMS). The desirable characteristics of…

Selective randomized load balancing and mesh networks with changing demands

NASA Astrophysics Data System (ADS)

Shepherd, F. B.; Winzer, P. J.

2006-05-01

We consider the problem of building cost-effective networks that are robust to dynamic changes in demand patterns. We compare several architectures using demand-oblivious routing strategies. Traditional approaches include single-hop architectures based on a (static or dynamic) circuit-switched core infrastructure and multihop (packet-switched) architectures based on point-to-point circuits in the core. To address demand uncertainty, we seek minimum cost networks that can carry the class of hose demand matrices. Apart from shortest-path routing, Valiant's randomized load balancing (RLB), and virtual private network (VPN) tree routing, we propose a third, highly attractive approach: selective randomized load balancing (SRLB). This is a blend of dual-hop hub routing and randomized load balancing that combines the advantages of both architectures in terms of network cost, delay, and delay jitter. In particular, we give empirical analyses for the cost (in terms of transport and switching equipment) for the discussed architectures, based on three representative carrier networks. Of these three networks, SRLB maintains the resilience properties of RLB while achieving significant cost reduction over all other architectures, including RLB and multihop Internet protocol/multiprotocol label switching (IP/MPLS) networks using VPN-tree routing.

Secure relay selection based on learning with negative externality in wireless networks

NASA Astrophysics Data System (ADS)

Zhao, Caidan; Xiao, Liang; Kang, Shan; Chen, Guiquan; Li, Yunzhou; Huang, Lianfen

2013-12-01

In this paper, we formulate relay selection into a Chinese restaurant game. A secure relay selection strategy is proposed for a wireless network, where multiple source nodes send messages to their destination nodes via several relay nodes, which have different processing and transmission capabilities as well as security properties. The relay selection utilizes a learning-based algorithm for the source nodes to reach their best responses in the Chinese restaurant game. In particular, the relay selection takes into account the negative externality of relay sharing among the source nodes, which learn the capabilities and security properties of relay nodes according to the current signals and the signal history. Simulation results show that this strategy improves the user utility and the overall security performance in wireless networks. In addition, the relay strategy is robust against the signal errors and deviations of some user from the desired actions.

Selective early-acquired fear memories undergo temporary suppression during adolescence

PubMed Central

Pattwell, Siobhan S.; Bath, Kevin G.; Casey, B. J.; Ninan, Ipe; Lee, Francis S.

2011-01-01

Highly conserved neural circuitry between rodents and humans has allowed for in-depth characterization of behavioral and molecular processes associated with emotional learning and memory. Despite increased prevalence of affective disorders in adolescent humans, few studies have characterized how associative-emotional learning changes during the transition through adolescence or identified mechanisms underlying such changes. By examining fear conditioning in mice, as they transitioned into and out of adolescence, we found that a suppression of contextual fear occurs during adolescence. Although contextual fear memories were not expressed during early adolescence, they could be retrieved and expressed as the mice transitioned out of adolescence. This temporary suppression of contextual fear was associated with blunted synaptic activity in the basal amygdala and decreased PI3K and MAPK signaling in the hippocampus. These findings reveal a unique form of brain plasticity in fear learning during early adolescence and may prove informative for understanding endogenous mechanisms to suppress unwanted fear memories. PMID:21220344

Evolutionary dynamics on networks of selectively neutral genotypes: effects of topology and sequence stability.

PubMed

Aguirre, Jacobo; Buldú, Javier M; Manrubia, Susanna C

2009-12-01

Networks of selectively neutral genotypes underlie the evolution of populations of replicators in constant environments. Previous theoretical analysis predicted that such populations will evolve toward highly connected regions of the genome space. We first study the evolution of populations of replicators on simple networks and quantify how the transient time to equilibrium depends on the initial distribution of sequences on the neutral network, on the topological properties of the latter, and on the mutation rate. Second, network neutrality is broken through the introduction of an energy for each sequence. This allows to study the competition between two features (neutrality and energetic stability) relevant for survival and subjected to different selective pressures. In cases where the two features are negatively correlated, the population experiences sudden migrations in the genome space for values of the relevant parameters that we calculate. The numerical study of larger networks indicates that the qualitative behavior to be expected in more realistic cases is already seen in representative examples of small networks.

Evolutionary dynamics on networks of selectively neutral genotypes: Effects of topology and sequence stability

NASA Astrophysics Data System (ADS)

Aguirre, Jacobo; Buldú, Javier M.; Manrubia, Susanna C.

2009-12-01

Networks of selectively neutral genotypes underlie the evolution of populations of replicators in constant environments. Previous theoretical analysis predicted that such populations will evolve toward highly connected regions of the genome space. We first study the evolution of populations of replicators on simple networks and quantify how the transient time to equilibrium depends on the initial distribution of sequences on the neutral network, on the topological properties of the latter, and on the mutation rate. Second, network neutrality is broken through the introduction of an energy for each sequence. This allows to study the competition between two features (neutrality and energetic stability) relevant for survival and subjected to different selective pressures. In cases where the two features are negatively correlated, the population experiences sudden migrations in the genome space for values of the relevant parameters that we calculate. The numerical study of larger networks indicates that the qualitative behavior to be expected in more realistic cases is already seen in representative examples of small networks.

Deconstructing Interocular Suppression: Attention and Divisive Normalization.

PubMed

Li, Hsin-Hung; Carrasco, Marisa; Heeger, David J

2015-10-01

In interocular suppression, a suprathreshold monocular target can be rendered invisible by a salient competitor stimulus presented in the other eye. Despite decades of research on interocular suppression and related phenomena (e.g., binocular rivalry, flash suppression, continuous flash suppression), the neural processing underlying interocular suppression is still unknown. We developed and tested a computational model of interocular suppression. The model included two processes that contributed to the strength of interocular suppression: divisive normalization and attentional modulation. According to the model, the salient competitor induced a stimulus-driven attentional modulation selective for the location and orientation of the competitor, thereby increasing the gain of neural responses to the competitor and reducing the gain of neural responses to the target. Additional suppression was induced by divisive normalization in the model, similar to other forms of visual masking. To test the model, we conducted psychophysics experiments in which both the size and the eye-of-origin of the competitor were manipulated. For small and medium competitors, behavioral performance was consonant with a change in the response gain of neurons that responded to the target. But large competitors induced a contrast-gain change, even when the competitor was split between the two eyes. The model correctly predicted these results and outperformed an alternative model in which the attentional modulation was eye specific. We conclude that both stimulus-driven attention (selective for location and feature) and divisive normalization contribute to interocular suppression.

Deconstructing Interocular Suppression: Attention and Divisive Normalization

PubMed Central

Li, Hsin-Hung; Carrasco, Marisa; Heeger, David J.

2015-01-01

In interocular suppression, a suprathreshold monocular target can be rendered invisible by a salient competitor stimulus presented in the other eye. Despite decades of research on interocular suppression and related phenomena (e.g., binocular rivalry, flash suppression, continuous flash suppression), the neural processing underlying interocular suppression is still unknown. We developed and tested a computational model of interocular suppression. The model included two processes that contributed to the strength of interocular suppression: divisive normalization and attentional modulation. According to the model, the salient competitor induced a stimulus-driven attentional modulation selective for the location and orientation of the competitor, thereby increasing the gain of neural responses to the competitor and reducing the gain of neural responses to the target. Additional suppression was induced by divisive normalization in the model, similar to other forms of visual masking. To test the model, we conducted psychophysics experiments in which both the size and the eye-of-origin of the competitor were manipulated. For small and medium competitors, behavioral performance was consonant with a change in the response gain of neurons that responded to the target. But large competitors induced a contrast-gain change, even when the competitor was split between the two eyes. The model correctly predicted these results and outperformed an alternative model in which the attentional modulation was eye specific. We conclude that both stimulus-driven attention (selective for location and feature) and divisive normalization contribute to interocular suppression. PMID:26517321

Relay selection in energy harvesting cooperative networks with rateless codes

NASA Astrophysics Data System (ADS)

Zhu, Kaiyan; Wang, Fei

2018-04-01

This paper investigates the relay selection in energy harvesting cooperative networks, where the relays harvests energy from the radio frequency (RF) signals transmitted by a source, and the optimal relay is selected and uses the harvested energy to assist the information transmission from the source to its destination. Both source and the selected relay transmit information using rateless code, which allows the destination recover original information after collecting codes bits marginally surpass the entropy of original information. In order to improve transmission performance and efficiently utilize the harvested power, the optimal relay is selected. The optimization problem are formulated to maximize the achievable information rates of the system. Simulation results demonstrate that our proposed relay selection scheme outperform other strategies.

Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.

PubMed

Kerr, Robert R; Burkitt, Anthony N; Thomas, Doreen A; Gilson, Matthieu; Grayden, David B

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.

Delay Selection by Spike-Timing-Dependent Plasticity in Recurrent Networks of Spiking Neurons Receiving Oscillatory Inputs

PubMed Central

Kerr, Robert R.; Burkitt, Anthony N.; Thomas, Doreen A.; Gilson, Matthieu; Grayden, David B.

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem. PMID:23408878

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

PubMed Central

Ahmed, Gulnaz; Zou, Jianhua; Zhao, Xi; Sadiq Fareed, Mian Muhammad

2017-01-01

The longer network lifetime of Wireless Sensor Networks (WSNs) is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs) selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED) clustering, Artificial Bee Colony (ABC), Zone Based Routing (ZBR), and Centralized Energy Efficient Clustering (CEEC) using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps) greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput. PMID:28241492

Smartphone technologies and Bayesian networks to assess shorebird habitat selection

USGS Publications Warehouse

Zeigler, Sara; Thieler, E. Robert; Gutierrez, Ben; Plant, Nathaniel G.; Hines, Megan K.; Fraser, James D.; Catlin, Daniel H.; Karpanty, Sarah M.

2017-01-01

Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, >30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

PubMed Central

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Extended shortest path selection for package routing of complex networks

NASA Astrophysics Data System (ADS)

Ye, Fan; Zhang, Lei; Wang, Bing-Hong; Liu, Lu; Zhang, Xing-Yi

The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency.

Social Capital for College: Network Composition and Access to Selective Institutions among Urban High School Students

ERIC Educational Resources Information Center

Hill, Lori Diane; Bregman, Allyson; Andrade, Fernando

2015-01-01

This study examines the relationship between networks that provide high school students with "social capital for college" (SCFC) and their access to selective institutions. It also explores the link between racial disparities in access to selective colleges and the composition of students' SCFC networks. Findings indicate that while…

Selective activation of p53-mediated tumour suppression in high-grade tumours.

PubMed

Junttila, Melissa R; Karnezis, Anthony N; Garcia, Daniel; Madriles, Francesc; Kortlever, Roderik M; Rostker, Fanya; Brown Swigart, Lamorna; Pham, David M; Seo, Youngho; Evan, Gerard I; Martins, Carla P

2010-11-25

Non-small cell lung carcinoma (NSCLC) is the leading cause of cancer-related death worldwide, with an overall 5-year survival rate of only 10-15%. Deregulation of the Ras pathway is a frequent hallmark of NSCLC, often through mutations that directly activate Kras. p53 is also frequently inactivated in NSCLC and, because oncogenic Ras can be a potent trigger of p53 (ref. 3), it seems likely that oncogenic Ras signalling has a major and persistent role in driving the selection against p53. Hence, pharmacological restoration of p53 is an appealing therapeutic strategy for treating this disease. Here we model the probable therapeutic impact of p53 restoration in a spontaneously evolving mouse model of NSCLC initiated by sporadic oncogenic activation of endogenous Kras. Surprisingly, p53 restoration failed to induce significant regression of established tumours, although it did result in a significant decrease in the relative proportion of high-grade tumours. This is due to selective activation of p53 only in the more aggressive tumour cells within each tumour. Such selective activation of p53 correlates with marked upregulation in Ras signal intensity and induction of the oncogenic signalling sensor p19(ARF)( )(ref. 6). Our data indicate that p53-mediated tumour suppression is triggered only when oncogenic Ras signal flux exceeds a critical threshold. Importantly, the failure of low-level oncogenic Kras to engage p53 reveals inherent limits in the capacity of p53 to restrain early tumour evolution and in the efficacy of therapeutic p53 restoration to eradicate cancers.

Selective suppression of the incorrect response implementation in choice behavior assessed by transcranial magnetic stimulation.

PubMed

Tandonnet, Christophe; Garry, Michael I; Summers, Jeffery J

2011-04-01

Selecting the adequate alternative in choice situations may involve an inhibition process. Here we assessed response implementation during the reaction time of a between-hand choice task with single- or paired-pulse (3 or 15 ms interstimulus intervals [ISIs]) transcranial magnetic stimulation of the motor cortex. The amplitude of the single-pulse motor evoked potential (MEP) initially increased for both hands. At around 130 ms, the single-pulse MEP kept increasing for the responding hand and decreased for the nonresponding hand. The paired-pulse MEP revealed a similar pattern for both ISIs with no effect on short intracortical inhibition and intracortical facilitation measures. The results suggest that the incorrect response implementation was selectively suppressed before execution of the correct response, preventing errors in choice context. The results favor models assuming that decision making involves an inhibition process. Copyright © 2010 Society for Psychophysiological Research.

BET bromodomain inhibition suppresses innate inflammatory and profibrotic transcriptional networks in heart failure

PubMed Central

Duan, Qiming; McMahon, Sarah; Anand, Priti; Shah, Hirsh; Thomas, Sean; Salunga, Hazel T.; Huang, Yu; Zhang, Rongli; Sahadevan, Aarathi; Lemieux, Madeleine E.; Brown, Jonathan D.; Srivastava, Deepak; Bradner, James E.; McKinsey, Timothy A.; Haldar, Saptarsi M.

2017-01-01

Despite current standard of care, the average 5-year mortality after an initial diagnosis of heart failure (HF) is about 40%, reflecting an urgent need for new therapeutic approaches. Previous studies demonstrated that the epigenetic reader protein bromodomain-containing protein 4 (BRD4), an emerging therapeutic target in cancer, functions as a critical coactivator of pathologic gene transactivation during cardiomyocyte hypertrophy. However, the therapeutic relevance of these findings to human disease remained unknown. We demonstrate that treatment with the BET bromodomain inhibitor JQ1 has therapeutic effects during severe, preestablished HF from prolonged pressure overload, as well as after a massive anterior myocardial infarction in mice. Furthermore, JQ1 potently blocks agonist-induced hypertrophy in human induced pluripotent stem cell–derived cardiomyocytes (iPSC-CMs). Integrated transcriptomic analyses across animal models and human iPSC-CMs reveal that BET inhibition preferentially blocks transactivation of a common pathologic gene regulatory program that is robustly enriched for NFκB and TGF-β signaling networks, typified by innate inflammatory and profibrotic myocardial genes. As predicted by these specific transcriptional mechanisms, we found that JQ1 does not suppress physiological cardiac hypertrophy in a mouse swimming model. These findings establish that pharmacologically targeting innate inflammatory and profibrotic myocardial signaling networks at the level of chromatin is effective in animal models and human cardiomyocytes, providing the critical rationale for further development of BET inhibitors and other epigenomic medicines for HF. PMID:28515341

Learning to ignore: acquisition of sustained attentional suppression.

PubMed

Dixon, Matthew L; Ruppel, Justin; Pratt, Jay; De Rosa, Eve

2009-04-01

We examined whether the selection mechanisms committed to the suppression of ignored stimuli can be modified by experience to produce a sustained, rather than transient, change in behavior. Subjects repeatedly ignored the shape of stimuli, while attending to their color. On subsequent attention to shape, there was a robust and sustained decrement in performance that was selective to when shape was ignored across multiple-color-target contexts, relative to a single-color-target context. Thus, amount of time ignored was not sufficient to induce a sustained performance decrement. Moreover, in this group, individual differences in initial color target selection were associated with the subsequent performance decrement when attending to previously ignored stimuli. Accompanying this sustained decrement in performance was a transfer in the locus of suppression from an exemplar (e.g., a circle) to a feature (i.e., shape) level of representation. These data suggest that learning can influence attentional selection by sustained attentional suppression of ignored stimuli.

Breeding and Genetics Symposium: networks and pathways to guide genomic selection.

PubMed

Snelling, W M; Cushman, R A; Keele, J W; Maltecca, C; Thomas, M G; Fortes, M R S; Reverter, A

2013-02-01

Many traits affecting profitability and sustainability of meat, milk, and fiber production are polygenic, with no single gene having an overwhelming influence on observed variation. No knowledge of the specific genes controlling these traits has been needed to make substantial improvement through selection. Significant gains have been made through phenotypic selection enhanced by pedigree relationships and continually improving statistical methodology. Genomic selection, recently enabled by assays for dense SNP located throughout the genome, promises to increase selection accuracy and accelerate genetic improvement by emphasizing the SNP most strongly correlated to phenotype although the genes and sequence variants affecting phenotype remain largely unknown. These genomic predictions theoretically rely on linkage disequilibrium (LD) between genotyped SNP and unknown functional variants, but familial linkage may increase effectiveness when predicting individuals related to those in the training data. Genomic selection with functional SNP genotypes should be less reliant on LD patterns shared by training and target populations, possibly allowing robust prediction across unrelated populations. Although the specific variants causing polygenic variation may never be known with certainty, a number of tools and resources can be used to identify those most likely to affect phenotype. Associations of dense SNP genotypes with phenotype provide a 1-dimensional approach for identifying genes affecting specific traits; in contrast, associations with multiple traits allow defining networks of genes interacting to affect correlated traits. Such networks are especially compelling when corroborated by existing functional annotation and established molecular pathways. The SNP occurring within network genes, obtained from public databases or derived from genome and transcriptome sequences, may be classified according to expected effects on gene products. As illustrated by

Prefrontal cortical network activity: Opposite effects of psychedelic hallucinogens and D1/D5 dopamine receptor activation

PubMed Central

Lambe, Evelyn K.; Aghajanian, George K.

2007-01-01

The fine-tuning of network activity provides a modulating influence on how information is processed and interpreted in the brain. Here, we use brain slices of rat prefrontal cortex to study how recurrent network activity is affected by neuromodulators known to alter normal cortical function. We previously determined that glutamate spillover and stimulation of extrasynaptic NMDA receptors are required to support hallucinogen-induced cortical network activity. Since microdialysis studies suggest that psychedelic hallucinogens and dopamine D1/D5 receptor agonists have opposite effects on extracellular glutamate in prefrontal cortex, we hypothesized that these two families of psychoactive drugs would have opposite effects on cortical network activity. We found that network activity can be enhanced by DOI (a psychedelic hallucinogen that is a partial agonist of serotonin 5-HT2A/2C receptors) and suppressed by the selective D1/D5 agonist SKF 38393. This suppression could be mimicked by direct activation of adenylyl cyclase with forskolin or by addition of a cAMP analog. These findings are consistent with previous work showing that activation of adenylyl cyclase can upregulate neuronal glutamate transporters, thereby decreasing synaptic spillover of glutamate. Consistent with this hypothesis, a low concentration of the glutamate transporter inhibitor TBOA restored electrically-evoked recurrent activity in the presence of a selective D1/D5 agonist, whereas recurrent activity in the presence of a low level of the GABAA antagonist bicuculline was not resistant to suppression by the D1/D5 agonist. The tempering of network UP states by D1/D5 receptor activation may have implications for the proposed use of D1/D5 agonists in the treatment of schizophrenia. PMID:17293055

The human burst suppression electroencephalogram of deep hypothermia.

PubMed

Westover, M Brandon; Ching, Shinung; Kumaraswamy, Vishakhadatta M; Akeju, Seun Oluwaseun; Pierce, Eric; Cash, Sydney S; Kilbride, Ronan; Brown, Emery N; Purdon, Patrick L

2015-10-01

Deep hypothermia induces 'burst suppression' (BS), an electroencephalogram pattern with low-voltage 'suppressions' alternating with high-voltage 'bursts'. Current understanding of BS comes mainly from anesthesia studies, while hypothermia-induced BS has received little study. We set out to investigate the electroencephalogram changes induced by cooling the human brain through increasing depths of BS through isoelectricity. We recorded scalp electroencephalograms from eleven patients undergoing deep hypothermia during cardiac surgery with complete circulatory arrest, and analyzed these using methods of spectral analysis. Within patients, the depth of BS systematically depends on the depth of hypothermia, though responses vary between patients except at temperature extremes. With decreasing temperature, burst lengths increase, and burst amplitudes and lengths decrease, while the spectral content of bursts remains constant. These findings support an existing theoretical model in which the common mechanism of burst suppression across diverse etiologies is the cyclical diffuse depletion of metabolic resources, and suggest the new hypothesis of local micro-network dropout to explain decreasing burst amplitudes at lower temperatures. These results pave the way for accurate noninvasive tracking of brain metabolic state during surgical procedures under deep hypothermia, and suggest new testable predictions about the network mechanisms underlying burst suppression. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Selecting public relations personnel of hospitals by analytic network process.

PubMed

Liao, Sen-Kuei; Chang, Kuei-Lun

2009-01-01

This study describes the use of analytic network process (ANP) in the Taiwanese hospital public relations personnel selection process. Starting with interviewing 48 practitioners and executives in north Taiwan, we collected selection criteria. Then, we retained the 12 critical criteria that were mentioned above 40 times by theses respondents, including: interpersonal skill, experience, negotiation, language, ability to follow orders, cognitive ability, adaptation to environment, adaptation to company, emotion, loyalty, attitude, and Response. Finally, we discussed with the 20 executives to take these important criteria into three perspectives to structure the hierarchy for hospital public relations personnel selection. After discussing with practitioners and executives, we find that selecting criteria are interrelated. The ANP, which incorporates interdependence relationships, is a new approach for multi-criteria decision-making. Thus, we apply ANP to select the most optimal public relations personnel of hospitals. An empirical study of public relations personnel selection problems in Taiwan hospitals is conducted to illustrate how the selection procedure works.

Human biallelic MFN2 mutations induce mitochondrial dysfunction, upper body adipose hyperplasia, and suppression of leptin expression.

PubMed

Rocha, Nuno; Bulger, David A; Frontini, Andrea; Titheradge, Hannah; Gribsholt, Sigrid Bjerge; Knox, Rachel; Page, Matthew; Harris, Julie; Payne, Felicity; Adams, Claire; Sleigh, Alison; Crawford, John; Gjesing, Anette Prior; Bork-Jensen, Jette; Pedersen, Oluf; Barroso, Inês; Hansen, Torben; Cox, Helen; Reilly, Mary; Rossor, Alex; Brown, Rebecca J; Taylor, Simeon I; McHale, Duncan; Armstrong, Martin; Oral, Elif A; Saudek, Vladimir; O'Rahilly, Stephen; Maher, Eamonn R; Richelsen, Bjørn; Savage, David B; Semple, Robert K

2017-04-19

MFN2 encodes mitofusin 2, a membrane-bound mediator of mitochondrial membrane fusion and inter-organelle communication. MFN2 mutations cause axonal neuropathy, with associated lipodystrophy only occasionally noted, however homozygosity for the p.Arg707Trp mutation was recently associated with upper body adipose overgrowth. We describe similar massive adipose overgrowth with suppressed leptin expression in four further patients with biallelic MFN2 mutations and at least one p.Arg707Trp allele. Overgrown tissue was composed of normal-sized, UCP1-negative unilocular adipocytes, with mitochondrial network fragmentation, disorganised cristae, and increased autophagosomes. There was strong transcriptional evidence of mitochondrial stress signalling, increased protein synthesis, and suppression of signatures of cell death in affected tissue, whereas mitochondrial morphology and gene expression were normal in skin fibroblasts. These findings suggest that specific MFN2 mutations cause tissue-selective mitochondrial dysfunction with increased adipocyte proliferation and survival, confirm a novel form of excess adiposity with paradoxical suppression of leptin expression, and suggest potential targeted therapies.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

PubMed Central

She, Ji; Wang, Fei; Zhou, Jianjiang

2016-01-01

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

Robust nonlinear variable selective control for networked systems

NASA Astrophysics Data System (ADS)

Rahmani, Behrooz

2016-10-01

This paper is concerned with the networked control of a class of uncertain nonlinear systems. In this way, Takagi-Sugeno (T-S) fuzzy modelling is used to extend the previously proposed variable selective control (VSC) methodology to nonlinear systems. This extension is based upon the decomposition of the nonlinear system to a set of fuzzy-blended locally linearised subsystems and further application of the VSC methodology to each subsystem. To increase the applicability of the T-S approach for uncertain nonlinear networked control systems, this study considers the asynchronous premise variables in the plant and the controller, and then introduces a robust stability analysis and control synthesis. The resulting optimal switching-fuzzy controller provides a minimum guaranteed cost on an H2 performance index. Simulation studies on three nonlinear benchmark problems demonstrate the effectiveness of the proposed method.

Using a two-phase evolutionary framework to select multiple network spreaders based on community structure

NASA Astrophysics Data System (ADS)

Fu, Yu-Hsiang; Huang, Chung-Yuan; Sun, Chuen-Tsai

2016-11-01

Using network community structures to identify multiple influential spreaders is an appropriate method for analyzing the dissemination of information, ideas and infectious diseases. For example, data on spreaders selected from groups of customers who make similar purchases may be used to advertise products and to optimize limited resource allocation. Other examples include community detection approaches aimed at identifying structures and groups in social or complex networks. However, determining the number of communities in a network remains a challenge. In this paper we describe our proposal for a two-phase evolutionary framework (TPEF) for determining community numbers and maximizing community modularity. Lancichinetti-Fortunato-Radicchi benchmark networks were used to test our proposed method and to analyze execution time, community structure quality, convergence, and the network spreading effect. Results indicate that our proposed TPEF generates satisfactory levels of community quality and convergence. They also suggest a need for an index, mechanism or sampling technique to determine whether a community detection approach should be used for selecting multiple network spreaders.

Selective Narrowing of Social Networks Across Adulthood is Associated With Improved Emotional Experience in Daily Life.

PubMed

English, Tammy; Carstensen, Laura L

2014-03-01

Past research has documented age differences in the size and composition of social networks that suggest that networks grow smaller with age and include an increasingly greater proportion of well-known social partners. According to socioemotional selectivity theory, such changes in social network composition serve an antecedent emotion regulatory function that supports an age-related increase in the priority that people place on emotional well-being. The present study employed a longitudinal design with a sample that spanned the full adult age range to examine whether there is evidence of within-individual (developmental) change in social networks and whether the characteristics of relationships predict emotional experiences in daily life. Using growth curve analyses, social networks were found to increase in size in young adulthood and then decline steadily throughout later life. As postulated by socioemotional selectivity theory, reductions were observed primarily in the number of peripheral partners; the number of close partners was relatively stable over time. In addition, cross-sectional analyses revealed that older adults reported that social network members elicited less negative emotion and more positive emotion. The emotional tone of social networks, particularly when negative emotions were associated with network members, also predicted experienced emotion of participants. Overall, findings were robust after taking into account demographic variables and physical health. The implications of these findings are discussed in the context of socioemotional selectivity theory and related theoretical models.

Camera network video summarization

NASA Astrophysics Data System (ADS)

Panda, Rameswar; Roy-Chowdhury, Amit K.

2017-05-01

Networks of vision sensors are deployed in many settings, ranging from security needs to disaster response to environmental monitoring. Many of these setups have hundreds of cameras and tens of thousands of hours of video. The difficulty of analyzing such a massive volume of video data is apparent whenever there is an incident that requires foraging through vast video archives to identify events of interest. As a result, video summarization, that automatically extract a brief yet informative summary of these videos, has attracted intense attention in the recent years. Much progress has been made in developing a variety of ways to summarize a single video in form of a key sequence or video skim. However, generating a summary from a set of videos captured in a multi-camera network still remains as a novel and largely under-addressed problem. In this paper, with the aim of summarizing videos in a camera network, we introduce a novel representative selection approach via joint embedding and capped l21-norm minimization. The objective function is two-fold. The first is to capture the structural relationships of data points in a camera network via an embedding, which helps in characterizing the outliers and also in extracting a diverse set of representatives. The second is to use a capped l21-norm to model the sparsity and to suppress the influence of data outliers in representative selection. We propose to jointly optimize both of the objectives, such that embedding can not only characterize the structure, but also indicate the requirements of sparse representative selection. Extensive experiments on standard multi-camera datasets well demonstrate the efficacy of our method over state-of-the-art methods.

Burstiness and tie activation strategies in time-varying social networks.

PubMed

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-13

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks' evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Joint Optimization of Receiver Placement and Illuminator Selection for a Multiband Passive Radar Network.

PubMed

Xie, Rui; Wan, Xianrong; Hong, Sheng; Yi, Jianxin

2017-06-14

The performance of a passive radar network can be greatly improved by an optimal radar network structure. Generally, radar network structure optimization consists of two aspects, namely the placement of receivers in suitable places and selection of appropriate illuminators. The present study investigates issues concerning the joint optimization of receiver placement and illuminator selection for a passive radar network. Firstly, the required radar cross section (RCS) for target detection is chosen as the performance metric, and the joint optimization model boils down to the partition p -center problem (PPCP). The PPCP is then solved by a proposed bisection algorithm. The key of the bisection algorithm lies in solving the partition set covering problem (PSCP), which can be solved by a hybrid algorithm developed by coupling the convex optimization with the greedy dropping algorithm. In the end, the performance of the proposed algorithm is validated via numerical simulations.

NASA Instep/mdmsc Jitter Suppression Experiment (JITTER)

NASA Technical Reports Server (NTRS)

White, Edward V.

1992-01-01

The objectives are the following: (1) to develop and demonstrate in-space performance of both passive and active damping systems for suppression of micro-amplitude vibration on an actual application structure and operate despite uncertain dynamics and uncertain disturbance characteristics; and (2) to correlate ground and in-space performance - the performance metric is vibration attenuation. The goals are to achieve vibration suppression equivalent to 5 percent passive damping in selected models and 15 percent active damping in selected modes. Various aspects of this experiment are presented in viewgraph form.

Optimal resource diffusion for suppressing disease spreading in multiplex networks

NASA Astrophysics Data System (ADS)

Chen, Xiaolong; Wang, Wei; Cai, Shimin; Stanley, H. Eugene; Braunstein, Lidia A.

2018-05-01

Resource diffusion is a ubiquitous phenomenon, but how it impacts epidemic spreading has received little study. We propose a model that couples epidemic spreading and resource diffusion in multiplex networks. The spread of disease in a physical contact layer and the recovery of the infected nodes are both strongly dependent upon resources supplied by their counterparts in the social layer. The generation and diffusion of resources in the social layer are in turn strongly dependent upon the state of the nodes in the physical contact layer. Resources diffuse preferentially or randomly in this model. To quantify the degree of preferential diffusion, a bias parameter that controls the resource diffusion is proposed. We conduct extensive simulations and find that the preferential resource diffusion can change phase transition type of the fraction of infected nodes. When the degree of interlayer correlation is below a critical value, increasing the bias parameter changes the phase transition from double continuous to single continuous. When the degree of interlayer correlation is above a critical value, the phase transition changes from multiple continuous to first discontinuous and then to hybrid. We find hysteresis loops in the phase transition. We also find that there is an optimal resource strategy at each fixed degree of interlayer correlation under which the threshold reaches a maximum and the disease can be maximally suppressed. In addition, the optimal controlling parameter increases as the degree of inter-layer correlation increases.

Narrow-band injection seeding of a terahertz frequency quantum cascade laser: Selection and suppression of longitudinal modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nong, Hanond, E-mail: Nong.Hanond@rub.de; Markmann, Sergej; Hekmat, Negar

2014-09-15

A periodically poled lithium niobate (PPLN) crystal with multiple poling periods is used to generate tunable narrow-bandwidth THz pulses for injection seeding a quantum cascade laser (QCL). We demonstrate that longitudinal modes of the quantum cascade laser close to the gain maximum can be selected or suppressed according to the seed spectrum. The QCL emission spectra obtained by electro-optic sampling from the quantum cascade laser, in the most favorable case, shows high selectivity and amplification of the longitudinal modes that overlap the frequency of the narrow-band seed. Proper selection of the narrow-band THz seed from the PPLN crystal discretely tunesmore » the longitudinal mode emission of the quantum cascade laser. Moreover, the THz wave build-up within the laser cavity is studied as a function of the round-trip time. When the seed frequency is outside the maximum of the gain spectrum the laser emission shifts to the preferential longitudinal mode.« less

Formation of nanoscale networks: selectively swelling amphiphilic block copolymers with CO2-expanded liquids

NASA Astrophysics Data System (ADS)

Gong, Jianliang; Zhang, Aijuan; Bai, Hua; Zhang, Qingkun; Du, Can; Li, Lei; Hong, Yanzhen; Li, Jun

2013-01-01

Polymeric films with nanoscale networks were prepared by selectively swelling an amphiphilic diblock copolymer, polystyrene-block-poly(4-vinylpyridine) (PS-b-P4VP), with the CO2-expanded liquid (CXL), CO2-methanol. The phase behavior of the CO2-methanol system was investigated by both theoretical calculation and experiments, revealing that methanol can be expanded by CO2, forming homogeneous CXL under the experimental conditions. When treated with the CO2-methanol system, the spin cast compact PS-b-P4VP film was transformed into a network with interconnected pores, in a pressure range of 12-20 MPa and a temperature range of 45-60 °C. The formation mechanism of the network, involving plasticization of PS and selective swelling of P4VP, was proposed. Because the diblock copolymer diffusion process is controlled by the activated hopping of individual block copolymer chains with the thermodynamic barrier for moving PVP segments from one to another, the formation of the network structures is achieved in a short time scale and shows ``thermodynamically restricted'' character. Furthermore, the resulting polymer networks were employed as templates, for the preparation of polypyrrole networks, by an electrochemical polymerization process. The prepared porous polypyrrole film was used to fabricate a chemoresistor-type gas sensor which showed high sensitivity towards ammonia.Polymeric films with nanoscale networks were prepared by selectively swelling an amphiphilic diblock copolymer, polystyrene-block-poly(4-vinylpyridine) (PS-b-P4VP), with the CO2-expanded liquid (CXL), CO2-methanol. The phase behavior of the CO2-methanol system was investigated by both theoretical calculation and experiments, revealing that methanol can be expanded by CO2, forming homogeneous CXL under the experimental conditions. When treated with the CO2-methanol system, the spin cast compact PS-b-P4VP film was transformed into a network with interconnected pores, in a pressure range of 12-20 MPa and a

Absence of positive selection on CenH3 in Luzula suggests that holokinetic chromosomes may suppress centromere drive.

PubMed

Zedek, František; Bureš, Petr

2016-12-01

The centromere drive theory explains diversity of eukaryotic centromeres as a consequence of the recurrent conflict between centromeric repeats and centromeric histone H3 (CenH3), in which selfish centromeres exploit meiotic asymmetry and CenH3 evolves adaptively to counterbalance deleterious consequences of driving centromeres. Accordingly, adaptively evolving CenH3 has so far been observed only in eukaryotes with asymmetric meiosis. However, if such evolution is a consequence of centromere drive, it should depend not only on meiotic asymmetry but also on monocentric or holokinetic chromosomal structure. Selective pressures acting on CenH3 have never been investigated in organisms with holokinetic meiosis despite the fact that holokinetic chromosomes have been hypothesized to suppress centromere drive. Therefore, the present study evaluates selective pressures acting on the CenH3 gene in holokinetic organisms for the first time, specifically in the representatives of the plant genus Luzula (Juncaceae), in which the kinetochore formation is not co-localized with any type of centromeric repeat. PCR, cloning and sequencing, and database searches were used to obtain coding CenH3 sequences from Luzula species. Codon substitution models were employed to infer selective regimes acting on CenH3 in Luzula KEY RESULTS: In addition to the two previously published CenH3 sequences from L. nivea, 16 new CenH3 sequences have been isolated from 12 Luzula species. Two CenH3 isoforms in Luzula that originated by a duplication event prior to the divergence of analysed species were found. No signs of positive selection acting on CenH3 in Luzula were detected. Instead, evidence was found that selection on CenH3 of Luzula might have been relaxed. The results indicate that holokinetism itself may suppress centromere drive and, therefore, holokinetic chromosomes might have evolved as a defence against centromere drive. © The Author 2016. Published by Oxford University Press on behalf of

Selective Narrowing of Social Networks Across Adulthood is Associated With Improved Emotional Experience in Daily Life

PubMed Central

English, Tammy; Carstensen, Laura L.

2014-01-01

Past research has documented age differences in the size and composition of social networks that suggest that networks grow smaller with age and include an increasingly greater proportion of well-known social partners. According to socioemotional selectivity theory, such changes in social network composition serve an antecedent emotion regulatory function that supports an age-related increase in the priority that people place on emotional well-being. The present study employed a longitudinal design with a sample that spanned the full adult age range to examine whether there is evidence of within-individual (developmental) change in social networks and whether the characteristics of relationships predict emotional experiences in daily life. Using growth curve analyses, social networks were found to increase in size in young adulthood and then decline steadily throughout later life. As postulated by socioemotional selectivity theory, reductions were observed primarily in the number of peripheral partners; the number of close partners was relatively stable over time. In addition, cross-sectional analyses revealed that older adults reported that social network members elicited less negative emotion and more positive emotion. The emotional tone of social networks, particularly when negative emotions were associated with network members, also predicted experienced emotion of participants. Overall, findings were robust after taking into account demographic variables and physical health. The implications of these findings are discussed in the context of socioemotional selectivity theory and related theoretical models. PMID:24910483

Applications of self-organizing neural networks in virtual screening and diversity selection.

PubMed

Selzer, Paul; Ertl, Peter

2006-01-01

Artificial neural networks provide a powerful technique for the analysis and modeling of nonlinear relationships between molecular structures and pharmacological activity. Many network types, including Kohonen and counterpropagation, also provide an intuitive method for the visual assessment of correspondence between the input and output data. This work shows how a combination of neural networks and radial distribution function molecular descriptors can be applied in various areas of industrial pharmaceutical research. These applications include the prediction of biological activity, the selection of screening candidates (cherry picking), and the extraction of representative subsets from large compound collections such as combinatorial libraries. The methods described have also been implemented as an easy-to-use Web tool, allowing chemists to perform interactive neural network experiments on the Novartis intranet.

Leptin Suppresses Mouse Taste Cell Responses to Sweet Compounds

PubMed Central

Noguchi, Kenshi; Shigemura, Noriatsu; Jyotaki, Masafumi; Takahashi, Ichiro; Margolskee, Robert F.

2015-01-01

Leptin is known to selectively suppress neural and behavioral responses to sweet-tasting compounds. However, the molecular basis for the effect of leptin on sweet taste is not known. Here, we report that leptin suppresses sweet taste via leptin receptors (Ob-Rb) and KATP channels expressed selectively in sweet-sensitive taste cells. Ob-Rb was more often expressed in taste cells that expressed T1R3 (a sweet receptor component) than in those that expressed glutamate-aspartate transporter (a marker for Type I taste cells) or GAD67 (a marker for Type III taste cells). Systemically administered leptin suppressed taste cell responses to sweet but not to bitter or sour compounds. This effect was blocked by a leptin antagonist and was absent in leptin receptor–deficient db/db mice and mice with diet-induced obesity. Blocking the KATP channel subunit sulfonylurea receptor 1, which was frequently coexpressed with Ob-Rb in T1R3-expressing taste cells, eliminated the effect of leptin on sweet taste. In contrast, activating the KATP channel with diazoxide mimicked the sweet-suppressing effect of leptin. These results indicate that leptin acts via Ob-Rb and KATP channels that are present in T1R3-expressing taste cells to selectively suppress their responses to sweet compounds. PMID:26116698

Decision-making in irrigation networks: Selecting appropriate canal structures using multi-attribute decision analysis.

PubMed

Hosseinzade, Zeinab; Pagsuyoin, Sheree A; Ponnambalam, Kumaraswamy; Monem, Mohammad J

2017-12-01

The stiff competition for water between agriculture and non-agricultural production sectors makes it necessary to have effective management of irrigation networks in farms. However, the process of selecting flow control structures in irrigation networks is highly complex and involves different levels of decision makers. In this paper, we apply multi-attribute decision making (MADM) methodology to develop a decision analysis (DA) framework for evaluating, ranking and selecting check and intake structures for irrigation canals. The DA framework consists of identifying relevant attributes for canal structures, developing a robust scoring system for alternatives, identifying a procedure for data quality control, and identifying a MADM model for the decision analysis. An application is illustrated through an analysis for automation purposes of the Qazvin irrigation network, one of the oldest and most complex irrigation networks in Iran. A survey questionnaire designed based on the decision framework was distributed to experts, managers, and operators of the Qazvin network and to experts from the Ministry of Power in Iran. Five check structures and four intake structures were evaluated. A decision matrix was generated from the average scores collected from the survey, and was subsequently solved using TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. To identify the most critical structure attributes for the selection process, optimal attribute weights were calculated using Entropy method. For check structures, results show that the duckbill weir is the preferred structure while the pivot weir is the least preferred. Use of the duckbill weir can potentially address the problem with existing Amil gates where manual intervention is required to regulate water levels during periods of flow extremes. For intake structures, the Neyrpic® gate and constant head orifice are the most and least preferred alternatives, respectively. Some advantages

DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs)

PubMed Central

Wadud, Zahid; Ullah, Khadem; Hussain, Sajjad; Yang, Xiaodong; Qazi, Abdul Baseer

2018-01-01

Underwater Wireless Sensor Networks (UWSNs) have intrinsic challenges that include long propagation delays, high mobility of sensor nodes due to water currents, Doppler spread, delay variance, multipath, attenuation and geometric spreading. The existing Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) protocol considers the weighting depth of the two hops in order to select the next Potential Forwarding Node (PFN). To improve the performance of WDFAD-DBR, we propose DOlphin and Whale Pod Routing protocol (DOW-PR). In this scheme, we divide the transmission range into a number of transmission power levels and at the same time select the next PFNs from forwarding and suppressed zones. In contrast to WDFAD-DBR, our scheme not only considers the packet upward advancement, but also takes into account the number of suppressed nodes and number of PFNs at the first and second hops. Consequently, reasonable energy reduction is observed while receiving and transmitting packets. Moreover, our scheme also considers the hops count of the PFNs from the sink. In the absence of PFNs, the proposed scheme will select the node from the suppressed region for broadcasting and thus ensures minimum loss of data. Besides this, we also propose another routing scheme (whale pod) in which multiple sinks are placed at water surface, but one sink is embedded inside the water and is physically connected with the surface sink through high bandwidth connection. Simulation results show that the proposed scheme has high Packet Delivery Ratio (PDR), low energy tax, reduced Accumulated Propagation Distance (APD) and increased the network lifetime. PMID:29757208

DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs).

PubMed

Wadud, Zahid; Ullah, Khadem; Hussain, Sajjad; Yang, Xiaodong; Qazi, Abdul Baseer

2018-05-12

Underwater Wireless Sensor Networks (UWSNs) have intrinsic challenges that include long propagation delays, high mobility of sensor nodes due to water currents, Doppler spread, delay variance, multipath, attenuation and geometric spreading. The existing Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) protocol considers the weighting depth of the two hops in order to select the next Potential Forwarding Node (PFN). To improve the performance of WDFAD-DBR, we propose DOlphin and Whale Pod Routing protocol (DOW-PR). In this scheme, we divide the transmission range into a number of transmission power levels and at the same time select the next PFNs from forwarding and suppressed zones. In contrast to WDFAD-DBR, our scheme not only considers the packet upward advancement, but also takes into account the number of suppressed nodes and number of PFNs at the first and second hops. Consequently, reasonable energy reduction is observed while receiving and transmitting packets. Moreover, our scheme also considers the hops count of the PFNs from the sink. In the absence of PFNs, the proposed scheme will select the node from the suppressed region for broadcasting and thus ensures minimum loss of data. Besides this, we also propose another routing scheme (whale pod) in which multiple sinks are placed at water surface, but one sink is embedded inside the water and is physically connected with the surface sink through high bandwidth connection. Simulation results show that the proposed scheme has high Packet Delivery Ratio (PDR), low energy tax, reduced Accumulated Propagation Distance (APD) and increased the network lifetime.

A lateralized functional auditory network is involved in anuran sexual selection.

PubMed

Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

2016-12-01

Right ear advantage (REA) exists in many land vertebrates in which the right ear and left hemisphere preferentially process conspecific acoustic stimuli such as those related to sexual selection. Although ecological and neural mechanisms for sexual selection have been widely studied, the brain networks involved are still poorly understood. In this study we used multi-channel electroencephalographic data in combination with Granger causal connectivity analysis to demonstrate, for the first time, that auditory neural network interconnecting the left and right midbrain and forebrain function asymmetrically in the Emei music frog (Babina daunchina), an anuran species which exhibits REA. The results showed the network was lateralized. Ascending connections between the mesencephalon and telencephalon were stronger in the left side while descending ones were stronger in the right, which matched with the REA in this species and implied that inhibition from the forebrainmay induce REA partly. Connections from the telencephalon to ipsilateral mesencephalon in response to white noise were the highest in the non-reproductive stage while those to advertisement calls were the highest in reproductive stage, implying the attention resources and living strategy shift when entered the reproductive season. Finally, these connection changes were sexually dimorphic, revealing sex differences in reproductive roles.

Selective Narrowing of Social Networks across Adulthood is Associated with Improved Emotional Experience in Daily Life

ERIC Educational Resources Information Center

English, Tammy; Carstensen, Laura L.

2014-01-01

Past research has documented age differences in the size and composition of social networks that suggest that networks grow smaller with age and include an increasingly greater proportion of well-known social partners. According to socioemotional selectivity theory, such changes in social network composition serve an antecedent emotion regulatory…

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

NASA Astrophysics Data System (ADS)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Frontal parietal control network regulates the anti-correlated default and dorsal attention networks.

PubMed

Gao, Wei; Lin, Weili

2012-01-01

Recent reports demonstrate the anti-correlated behaviors between the default (DF) and the dorsal attention (DA) networks. We aimed to investigate the roles of the frontal parietal control (FPC) network in regulating the two anti-correlated networks through three experimental conditions, including resting, continuous self-paced/attended sequential finger tapping (FT), and natural movie watching (MW), respectively. The two goal-directed tasks were chosen to engage either one of the two competing networks-FT for DA whereas MW for default. We hypothesized that FPC will selectively augment/suppress either network depending on how the task targets the specific network; FPC will positively correlate with the target network, but negatively correlate with the network anti-correlated with the target network. We further hypothesized that significant causal links from FPC to both DA and DF are present during all three experimental conditions, supporting the initiative regulating role of FPC over the two opposing systems. Consistent with our hypotheses, FPC exhibited a significantly higher positive correlation with DA (P = 0.0095) whereas significantly more negative correlation with default (P = 0.0025) during FT when compared to resting. Completely opposite to that observed during FT, the FPC was significantly anti-correlated with DA (P = 2.1e-6) whereas positively correlated with default (P = 0.0035) during MW. Furthermore, extensive causal links from FPC to both DA and DF were observed across all three experimental states. Together, our results strongly support the notion that the FPC regulates the anti-correlated default and DA networks. Copyright © 2011 Wiley Periodicals, Inc.

Secure and Fair Cluster Head Selection Protocol for Enhancing Security in Mobile Ad Hoc Networks

PubMed Central

Paramasivan, B.; Kaliappan, M.

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP. PMID:25143986

Secure and fair cluster head selection protocol for enhancing security in mobile ad hoc networks.

PubMed

Paramasivan, B; Kaliappan, M

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP.

Evolution and selection of river networks: Statics, dynamics, and complexity

PubMed Central

Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R.; Maritan, Amos; Rodriguez-Iturbe, Ignacio

2014-01-01

Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics—every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept. PMID:24550264

Suppression of extraneous thermal noise in cavity optomechanics.

PubMed

Zhao, Yi; Wilson, Dalziel J; Ni, K-K; Kimble, H J

2012-02-13

Extraneous thermal motion can limit displacement sensitivity and radiation pressure effects, such as optical cooling, in a cavity-optomechanical system. Here we present an active noise suppression scheme and its experimental implementation. The main challenge is to selectively sense and suppress extraneous thermal noise without affecting motion of the oscillator. Our solution is to monitor two modes of the optical cavity, each with different sensitivity to the oscillator's motion but similar sensitivity to the extraneous thermal motion. This information is used to imprint "anti-noise" onto the frequency of the incident laser field. In our system, based on a nano-mechanical membrane coupled to a Fabry-Pérot cavity, simulation and experiment demonstrate that extraneous thermal noise can be selectively suppressed and that the associated limit on optical cooling can be reduced.

Distributed estimation for adaptive sensor selection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

2014-05-01

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

Frontal Parietal Control Network Regulates the Anti-Correlated Default and Dorsal Attention Networks

PubMed Central

Gao, Wei; Lin, Weili

2011-01-01

Recent reports demonstrate the anti-correlated behaviors between the default and the dorsal attention (DA) networks. We aimed to investigate the roles of the frontal parietal control (FPC) network in regulating the two anti-correlated networks through three experimental conditions, including resting, continuous self-paced/attended sequential finger tapping (FT), and natural movie watching (MW), respectively. The two goal-directed tasks were chosen to engage either one of the two competing networks—FT for DA whereas MW for default. We hypothesized that FPC will selectively augment/suppress either network depending on how the task targets the specific network; FPC will positively correlate with the target network, but negatively correlate with the network anti-correlated with the target network. We further hypothesized that significant causal links from FPC to both DA and DF are present during all three experimental conditions, supporting the initiative regulating role of FPC over the two opposing systems. Consistent with our hypotheses, FPC exhibited a significantly higher positive correlation with DA (P = 0.0095) whereas significantly more negative correlation with default (P = 0.0025) during FT when compared to resting. Completely opposite to that observed during FT, the FPC was significantly anti-correlated with DA (P = 2.1e-6) whereas positively correlated with default (P = 0.0035) during MW. Furthermore, extensive causal links from FPC to both DA and DF were observed across all three experimental states. Together, our results strongly support the notion that the FPC regulates the anti-correlated default and DA networks. PMID:21391263

Selection of genetic variants of lymphocytic choriomeningitis virus in spleens of persistently infected mice. Role in suppression of cytotoxic T lymphocyte response and viral persistence

PubMed Central

1984-01-01

We studied the mechanism of lymphocytic choriomeningitis virus (LCMV) persistence and the suppression of cytotoxic T lymphocyte (CTL) responses in BALB/c WEHI mice infected at birth with LCMV Armstrong strain. Using adoptive transfer experiments we found that spleen cells from persistently infected (carrier) mice actively suppressed the expected LCMV-specific CTL response of spleen cells from normal adult mice. The suppression was specific for the CTL response and LCMV - specific antibody responses were not affected. Associated with the specific CTL suppression was the establishment of persistent LCMV infection. The transfer of spleen or lymph node cells containing LCMV - specific CTL resulted in virus clearance and prevented establishment of the carrier state. The suppression of LCMV -specific CTL responses by carrier spleen cells is not mediated by a suppressor cell, but is due to the presence of genetic variants of LCMV in spleens of carrier mice. Such virus variants selectively suppress LCMV-specific CTL responses and cause persistent infections in immunocompetent mice. In striking contrast, wild-type LCMV Armstrong, from which these variants were generated, induces a potent CTL response in immunocompetent mice and the LCMV infection is rapidly cleared. Our results show that LCMV variants that emerge during infection in vivo play a crucial role in the suppression of virus-specific CTL responses and in the maintenance of virus persistence. PMID:6332167

Topology-selective jamming of fully-connected, code-division random-access networks

NASA Technical Reports Server (NTRS)

Polydoros, Andreas; Cheng, Unjeng

1990-01-01

The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.

Burstiness and tie activation strategies in time-varying social networks

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-01

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks’ evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Set selection dynamical system neural networks with partial memories, with applications to Sudoku and KenKen puzzles.

PubMed

Boreland, B; Clement, G; Kunze, H

2015-08-01

After reviewing set selection and memory model dynamical system neural networks, we introduce a neural network model that combines set selection with partial memories (stored memories on subsets of states in the network). We establish that feasible equilibria with all states equal to ± 1 correspond to answers to a particular set theoretic problem. We show that KenKen puzzles can be formulated as a particular case of this set theoretic problem and use the neural network model to solve them; in addition, we use a similar approach to solve Sudoku. We illustrate the approach in examples. As a heuristic experiment, we use online or print resources to identify the difficulty of the puzzles and compare these difficulties to the number of iterations used by the appropriate neural network solver, finding a strong relationship. Copyright © 2015 Elsevier Ltd. All rights reserved.

A selection model for accounting for publication bias in a full network meta-analysis.

PubMed

Mavridis, Dimitris; Welton, Nicky J; Sutton, Alex; Salanti, Georgia

2014-12-30

Copas and Shi suggested a selection model to explore the potential impact of publication bias via sensitivity analysis based on assumptions for the probability of publication of trials conditional on the precision of their results. Chootrakool et al. extended this model to three-arm trials but did not fully account for the implications of the consistency assumption, and their model is difficult to generalize for complex network structures with more than three treatments. Fitting these selection models within a frequentist setting requires maximization of a complex likelihood function, and identification problems are common. We have previously presented a Bayesian implementation of the selection model when multiple treatments are compared with a common reference treatment. We now present a general model suitable for complex, full network meta-analysis that accounts for consistency when adjusting results for publication bias. We developed a design-by-treatment selection model to describe the mechanism by which studies with different designs (sets of treatments compared in a trial) and precision may be selected for publication. We fit the model in a Bayesian setting because it avoids the numerical problems encountered in the frequentist setting, it is generalizable with respect to the number of treatments and study arms, and it provides a flexible framework for sensitivity analysis using external knowledge. Our model accounts for the additional uncertainty arising from publication bias more successfully compared to the standard Copas model or its previous extensions. We illustrate the methodology using a published triangular network for the failure of vascular graft or arterial patency. Copyright © 2014 John Wiley & Sons, Ltd.

Adolescent Friendships, BMI, and Physical Activity: Untangling Selection and Influence Through Longitudinal Social Network Analysis

PubMed Central

Simpkins, Sandra D.; Schaefer, David R.; Price, Chara D.; Vest, Andrea E.

2012-01-01

Bioecological theory suggests that adolescents’ health is a result of selection and socialization processes occurring between adolescents and their microsettings. This study examines the association between adolescents’ friends and health using a social network model and data from the National Longitudinal Study of Adolescent Health (N = 1,896, mean age = 15.97 years). Results indicated evidence of friend influence on BMI and physical activity. Friendships were more likely among adolescents who engaged in greater physical activity and who were similar to one another in BMI and physical activity. These effects emerged after controlling for alternative friend selection factors, such as endogenous social network processes and propinquity through courses and activities. Some selection effects were moderated by gender, popularity, and reciprocity. PMID:24222971

Selective Self-Presentation and Social Comparison Through Photographs on Social Networking Sites.

PubMed

Fox, Jesse; Vendemia, Megan A

2016-10-01

Through social media and camera phones, users enact selective self-presentation as they choose, edit, and post photographs of themselves (such as selfies) to social networking sites for an imagined audience. Photos typically focus on users' physical appearance, which may compound existing sociocultural pressures about body image. We identified users of social networking sites among a nationally representative U.S. sample (N = 1,686) and examined women's and men's photo-related behavior, including posting photos, editing photos, and feelings after engaging in upward and downward social comparison with others' photos on social networking sites. We identified some sex differences: women edited photos more frequently and felt worse after upward social comparison than men. Body image and body comparison tendency mediated these effects.

Time Series Analysis for Spatial Node Selection in Environment Monitoring Sensor Networks

PubMed Central

Bhandari, Siddhartha; Jurdak, Raja; Kusy, Branislav

2017-01-01

Wireless sensor networks are widely used in environmental monitoring. The number of sensor nodes to be deployed will vary depending on the desired spatio-temporal resolution. Selecting an optimal number, position and sampling rate for an array of sensor nodes in environmental monitoring is a challenging question. Most of the current solutions are either theoretical or simulation-based where the problems are tackled using random field theory, computational geometry or computer simulations, limiting their specificity to a given sensor deployment. Using an empirical dataset from a mine rehabilitation monitoring sensor network, this work proposes a data-driven approach where co-integrated time series analysis is used to select the number of sensors from a short-term deployment of a larger set of potential node positions. Analyses conducted on temperature time series show 75% of sensors are co-integrated. Using only 25% of the original nodes can generate a complete dataset within a 0.5 °C average error bound. Our data-driven approach to sensor position selection is applicable for spatiotemporal monitoring of spatially correlated environmental parameters to minimize deployment cost without compromising data resolution. PMID:29271880

Decorrelation of Neural-Network Activity by Inhibitory Feedback

PubMed Central

Einevoll, Gaute T.; Diesmann, Markus

2012-01-01

Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between

Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

NASA Technical Reports Server (NTRS)

Stoenescu, Tudor M.; Woo, Simon S.

2009-01-01

In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

Data from selected U.S. Geological Survey National Stream Water-Quality Networks (WQN)

USGS Publications Warehouse

Alexander, Richard B.; Slack, J.R.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.; Briel, L.I.; Buttleman, K.P.

1996-01-01

This CD-ROM set contains data from two USGS national stream water-quality networks, the Hydrologic Benchmark Network (HBN) and the National Stream Quality Accounting Network (NASQAN), operated during the past 30 years. These networks were established to provide national and regional descriptions of stream water-quality conditions and trends, based on uniform monitoring of selected watersheds throughout the United States, and to improve our understanding of the effects of the natural environment and human activities on water quality. The HBN, consisting of 63 relatively small, minimally disturbed watersheds, provides data for investigating naturally induced changes in streamflow and water quality and the effects of airborne substances on water quality. NASQAN, consisting of 618 larger, more culturally influenced watersheds, provides information for tracking water-quality conditions in major U.S. rivers and streams.

Training voluntary motor suppression with real-time feedback of motor evoked potentials.

PubMed

Majid, D S Adnan; Lewis, Christina; Aron, Adam R

2015-05-01

Training people to suppress motor representations voluntarily could improve response control. We evaluated a novel training procedure of real-time feedback of motor evoked potentials (MEPs) generated by transcranial magnetic stimulation (TMS) over motor cortex. On each trial, a cue instructed participants to use a mental strategy to suppress a particular finger representation without overt movement. A single pulse of TMS was delivered over motor cortex, and an MEP-derived measure of hand motor excitability was delivered visually to the participant within 500 ms. In experiment 1, we showed that participants learned to reduce the excitability of a particular finger beneath baseline (selective motor suppression) within 30 min of practice. In experiment 2, we performed a double-blind study with 2 training groups (1 with veridical feedback and 1 with matched sham feedback) to show that selective motor suppression depends on the veridical feedback itself. Experiment 3 further demonstrated the importance of veridical feedback by showing that selective motor suppression did not arise from mere mental imagery, even when incentivized with reward. Thus participants can use real-time feedback of TMS-induced MEPs to discover an effective mental strategy for selective motor suppression. This high-temporal-resolution, trial-by-trial-feedback training method could be used to help people better control response tendencies and may serve as a potential therapy for motor disorders such as Tourette's and dystonia. Copyright © 2015 the American Physiological Society.

The production route selection algorithm in virtual manufacturing networks

NASA Astrophysics Data System (ADS)

Krenczyk, D.; Skolud, B.; Olender, M.

2017-08-01

The increasing requirements and competition in the global market are challenges for the companies profitability in production and supply chain management. This situation became the basis for construction of virtual organizations, which are created in response to temporary needs. The problem of the production flow planning in virtual manufacturing networks is considered. In the paper the algorithm of the production route selection from the set of admissible routes, which meets the technology and resource requirements and in the context of the criterion of minimum cost is proposed.

a Weighted Local-World Evolving Network Model Based on the Edge Weights Preferential Selection

NASA Astrophysics Data System (ADS)

Li, Ping; Zhao, Qingzhen; Wang, Haitang

2013-05-01

In this paper, we use the edge weights preferential attachment mechanism to build a new local-world evolutionary model for weighted networks. It is different from previous papers that the local-world of our model consists of edges instead of nodes. Each time step, we connect a new node to two existing nodes in the local-world through the edge weights preferential selection. Theoretical analysis and numerical simulations show that the scale of the local-world affect on the weight distribution, the strength distribution and the degree distribution. We give the simulations about the clustering coefficient and the dynamics of infectious diseases spreading. The weight dynamics of our network model can portray the structure of realistic networks such as neural network of the nematode C. elegans and Online Social Network.

Default network activation during episodic and semantic memory retrieval: A selective meta-analytic comparison.

PubMed

Kim, Hongkeun

2016-01-08

It remains unclear whether and to what extent the default network subregions involved in episodic memory (EM) and semantic memory (SM) processes overlap or are separated from one another. This study addresses this issue through a controlled meta-analysis of functional neuroimaging studies involving healthy participants. Various EM and SM task paradigms differ widely in the extent of default network involvement. Therefore, the issue at hand cannot be properly addressed without some control for this factor. In this regard, this study employs a two-stage analysis: a preliminary meta-analysis to select EM and SM task paradigms that recruit relatively extensive default network regions and a main analysis to compare the selected task paradigms. Based on a within-EM comparison, the default network contributed more to recollection/familiarity effects than to old/new effects, and based on a within-SM comparison, it contributed more to word/pseudoword effects than to semantic/phonological effects. According to a direct comparison of recollection/familiarity and word/pseudoword effects, each involving a range of default network regions, there were more overlaps than separations in default network subregions involved in these two effects. More specifically, overlaps included the bilateral posterior cingulate/retrosplenial cortex, left inferior parietal lobule, and left anteromedial prefrontal regions, whereas separations included only the hippocampal formation and the parahippocampal cortex region, which was unique to recollection/familiarity effects. These results indicate that EM and SM retrieval processes involving strong memory signals recruit extensive and largely overlapping default network regions and differ mainly in distinct contributions of hippocampus and parahippocampal regions to EM retrieval. Copyright © 2015 Elsevier Ltd. All rights reserved.

A uniform energy consumption algorithm for wireless sensor and actuator networks based on dynamic polling point selection.

PubMed

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2013-12-19

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation.

Alpha-band rhythm suppression during memory recall reflecting memory performance.

PubMed

Yokosawa, Koichi; Kimura, Keisuke; Chitose, Ryota; Momiki, Takuya; Kuriki, Shinya

2016-08-01

Alpha-band rhythm is thought to be involved in memory processes, similarly to other spontaneous brain rhythms. Ten right-handed healthy volunteers participated in our proposed sequential short-term memory task that provides a serial position effect in accuracy rate. We recorded alpha-band rhythms by magnetoencephalography during performance of the task and observed that the amplitude of the rhythm was suppressed dramatically in the memory recall period. The suppressed region was estimated to be in the occipital lobe, suggesting that alpha-band rhythm is suppressed by activation of the occipital attentional network. Additionally, the alpha-band suppression reflected accuracy rate, that is, the amplitude was suppressed more when recalling items with higher accuracy rate. The sensors with a significant correlation between alpha-band amplitude and accuracy rate were located widely from the frontal to occipital regions mainly in the right hemisphere. The results suggests that alpha-band rhythm is involved in memory recall and can be index of memory performance.

Selective suppression of harmful cyanobacteria in an entire lake with hydrogen peroxide.

PubMed

Matthijs, Hans C P; Visser, Petra M; Reeze, Bart; Meeuse, Jeroen; Slot, Pieter C; Wijn, Geert; Talens, Renée; Huisman, Jef

2012-04-01

Although harmful cyanobacteria form a major threat to water quality, few methods exist for the rapid suppression of cyanobacterial blooms. Since laboratory studies indicated that cyanobacteria are more sensitive to hydrogen peroxide (H(2)O(2)) than eukaryotic phytoplankton, we tested the application of H(2)O(2) in natural waters. First, we exposed water samples from a recreational lake dominated by the toxic cyanobacterium Planktothrix agardhii to dilute H(2)O(2). This reduced the photosynthetic vitality by more than 70% within a few hours. Next, we installed experimental enclosures in the lake, which revealed that H(2)O(2) selectively killed the cyanobacteria without major impacts on eukaryotic phytoplankton, zooplankton, or macrofauna. Based on these tests, we introduced 2 mg L(-1) (60 μM) of H(2)O(2) homogeneously into the entire water volume of the lake with a special dispersal device, called the water harrow. The cyanobacterial population as well as the microcystin concentration collapsed by 99% within a few days. Eukaryotic phytoplankton (including green algae, cryptophytes, chrysophytes and diatoms), zooplankton and macrofauna remained largely unaffected. Following the treatment, cyanobacterial abundances remained low for 7 weeks. Based on these results, we propose the use of dilute H(2)O(2) for the selective elimination of harmful cyanobacteria from recreational lakes and drinking water reservoirs, especially when immediate action is urgent and/or cyanobacterial control by reduction of eutrophication is currently not feasible. A key advantage of this method is that the added H(2)O(2) degrades to water and oxygen within a few days, and thus leaves no long-term chemical traces in the environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks

NASA Technical Reports Server (NTRS)

Scott, Robert C.

2000-01-01

NASA Langley Research Center, Hampton, VA 23681 Under a joint research and development effort conducted by the National Aeronautics and Space Administration and The Boeing Company (formerly McDonnell Douglas) three neural-network based control systems were developed and tested. The control systems were experimentally evaluated using a transonic wind-tunnel model in the Langley Transonic Dynamics Tunnel. One system used a neural network to schedule flutter suppression control laws, another employed a neural network in a predictive control scheme, and the third employed a neural network in an inverse model control scheme. All three of these control schemes successfully suppressed flutter to or near the limits of the testing apparatus, and represent the first experimental applications of neural networks to flutter suppression. This paper will summarize the findings of this project.

Outage Performance Analysis of Relay Selection Schemes in Wireless Energy Harvesting Cooperative Networks over Non-Identical Rayleigh Fading Channels.

PubMed

Do, Nhu Tri; Bao, Vo Nguyen Quoc; An, Beongku

2016-02-26

In this paper, we study relay selection in decode-and-forward wireless energy harvesting cooperative networks. In contrast to conventional cooperative networks, the relays harvest energy from the source's radio-frequency radiation and then use that energy to forward the source information. Considering power splitting receiver architecture used at relays to harvest energy, we are concerned with the performance of two popular relay selection schemes, namely, partial relay selection (PRS) scheme and optimal relay selection (ORS) scheme. In particular, we analyze the system performance in terms of outage probability (OP) over independent and non-identical (i.n.i.d.) Rayleigh fading channels. We derive the closed-form approximations for the system outage probabilities of both schemes and validate the analysis by the Monte-Carlo simulation. The numerical results provide comprehensive performance comparison between the PRS and ORS schemes and reveal the effect of wireless energy harvesting on the outage performances of both schemes. Additionally, we also show the advantages and drawbacks of the wireless energy harvesting cooperative networks and compare to the conventional cooperative networks.

Treatment with selective estrogen receptor modulators regulates myelin specific T-cells and suppresses experimental autoimmune encephalomyelitis.

PubMed

Bebo, Bruce F; Dehghani, Babak; Foster, Scott; Kurniawan, Astrid; Lopez, Francisco J; Sherman, Larry S

2009-05-01

Steroidal estrogens can regulate inflammatory immune responses and may be involved in the suppression of multiple sclerosis (MS) during pregnancy. However, the risks and side effects associated with steroidal estrogens may limit their usefulness for long-term MS therapy. Selective estrogen receptor modulators (SERMs) could provide an alternative therapeutic strategy, because they behave as estrogen agonists in some tissues, but are either inert or behave like estrogen antagonists in other tissues. In this study, we investigated the ability of two commercially available SERMs (tamoxifen and raloxifene) to regulate myelin specific immunity and experimental autoimmune encephalomyelitis (EAE) in mice. Both tamoxifen and raloxifene suppressed myelin antigen specific T-cell proliferation. However, tamoxifen was more effective in this regard. Tamoxifen treatment reduced the induction of major histocompatibility complex II by lipopolysaccharide stimulated dendritic cells and decreased their ability to activate myelin specific T-cells. At lower doses, tamoxifen was found to increase the levels of Th2 transcription factors and induce a Th2 bias in cultures of myelin-specific splenocytes. EAE symptoms and the degree of demyelination were less severe in mice treated with tamoxifen than in control mice. These findings support the notion that tamoxifen or related SERMs are potential agents that could be used in the treatment of inflammatory autoimmune disorders that affect the central nervous system.

Environmentally induced changes in correlated responses to selection reveal variable pleiotropy across a complex genetic network.

PubMed

Sikkink, Kristin L; Reynolds, Rose M; Cresko, William A; Phillips, Patrick C

2015-05-01

Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. © 2015 The Author(s).

ENVIRONMENTALLY INDUCED CHANGES IN CORRELATED RESPONSES TO SELECTION REVEAL VARIABLE PLEIOTROPY ACROSS A COMPLEX GENETIC NETWORK

PubMed Central

Sikkink, Kristin L.; Reynolds, Rose M.; Cresko, William A.; Phillips, Patrick C.

2017-01-01

Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. PMID:25809411

Green supply chain management strategy selection using analytic network process: case study at PT XYZ

NASA Astrophysics Data System (ADS)

Adelina, W.; Kusumastuti, R. D.

2017-01-01

This study is about business strategy selection for green supply chain management (GSCM) for PT XYZ by using Analytic Network Process (ANP). GSCM is initiated as a response to reduce environmental impacts from industrial activities. The purposes of this study are identifying criteria and sub criteria in selecting GSCM Strategy, and analysing a suitable GSCM strategy for PT XYZ. This study proposes ANP network with 6 criteria and 29 sub criteria, which are obtained from the literature and experts’ judgements. One of the six criteria contains GSCM strategy options, namely risk-based strategy, efficiency-based strategy, innovation-based strategy, and closed loop strategy. ANP solves complex GSCM strategy-selection by using a more structured process and considering green perspectives from experts. The result indicates that innovation-based strategy is the most suitable green supply chain management strategy for PT XYZ.

Path selection rules for droplet trains in single-lane microfluidic networks

NASA Astrophysics Data System (ADS)

Amon, A.; Schmit, A.; Salkin, L.; Courbin, L.; Panizza, P.

2013-07-01

We investigate the transport of periodic trains of droplets through microfluidic networks having one inlet, one outlet, and nodes consisting of T junctions. Variations of the dilution of the trains, i.e., the distance between drops, reveal the existence of various hydrodynamic regimes characterized by the number of preferential paths taken by the drops. As the dilution increases, this number continuously decreases until only one path remains explored. Building on a continuous approach used to treat droplet traffic through a single asymmetric loop, we determine selection rules for the paths taken by the drops and we predict the variations of the fraction of droplets taking these paths with the parameters at play including the dilution. Our results show that as dilution decreases, the paths are selected according to the ascending order of their hydrodynamic resistance in the absence of droplets. The dynamics of these systems controlled by time-delayed feedback is complex: We observe a succession of periodic regimes separated by a wealth of bifurcations as the dilution is varied. In contrast to droplet traffic in single asymmetric loops, the dynamical behavior in networks of loops is sensitive to initial conditions because of extra degrees of freedom.

Data-driven confounder selection via Markov and Bayesian networks.

PubMed

Häggström, Jenny

2018-06-01

To unbiasedly estimate a causal effect on an outcome unconfoundedness is often assumed. If there is sufficient knowledge on the underlying causal structure then existing confounder selection criteria can be used to select subsets of the observed pretreatment covariates, X, sufficient for unconfoundedness, if such subsets exist. Here, estimation of these target subsets is considered when the underlying causal structure is unknown. The proposed method is to model the causal structure by a probabilistic graphical model, for example, a Markov or Bayesian network, estimate this graph from observed data and select the target subsets given the estimated graph. The approach is evaluated by simulation both in a high-dimensional setting where unconfoundedness holds given X and in a setting where unconfoundedness only holds given subsets of X. Several common target subsets are investigated and the selected subsets are compared with respect to accuracy in estimating the average causal effect. The proposed method is implemented with existing software that can easily handle high-dimensional data, in terms of large samples and large number of covariates. The results from the simulation study show that, if unconfoundedness holds given X, this approach is very successful in selecting the target subsets, outperforming alternative approaches based on random forests and LASSO, and that the subset estimating the target subset containing all causes of outcome yields smallest MSE in the average causal effect estimation. © 2017, The International Biometric Society.

Neural network models for spatial data mining, map production, and cortical direction selectivity

NASA Astrophysics Data System (ADS)

Parsons, Olga

A family of ARTMAP neural networks for incremental supervised learning has been developed over the last decade. The Sensor Exploitation Group of MIT Lincoln Laboratory (LL) has incorporated an early version of this network as the recognition engine of a hierarchical system for fusion and data mining of multiple registered geospatial images. The LL system has been successfully fielded, but it is limited to target vs. non-target identifications and does not produce whole maps. This dissertation expands the capabilities of the LL system so that it learns to identify arbitrarily many target classes at once and can thus produce a whole map. This new spatial data mining system is designed particularly to cope with the highly skewed class distributions of typical mapping problems. Specification of a consistent procedure and a benchmark testbed has permitted the evaluation of candidate recognition networks as well as pre- and post-processing and feature extraction options. The resulting default ARTMAP network and mapping methodology set a standard for a variety of related mapping problems and application domains. The second part of the dissertation investigates the development of cortical direction selectivity. The possible role of visual experience and oculomotor behavior in the maturation of cells in the primary visual cortex is studied. The responses of neurons in the thalamus and cortex of the cat are modeled when natural scenes are scanned by several types of eye movements. Inspired by the Hebbian-like synaptic plasticity, which is based upon correlations between cell activations, the second-order statistical structure of thalamo-cortical activity is examined. In the simulations, patterns of neural activity that lead to a correct refinement of cell responses are observed during visual fixation, when small ocular movements occur, but are not observed in the presence of large saccades. Simulations also replicate experiments in which kittens are reared under stroboscopic

Appearance of Unstable Monopoly State Caused by Selective and Concentrative Mergers in Business Networks.

PubMed

Goto, Hayato; Viegas, Eduardo; Jensen, Henrik Jeldtoft; Takayasu, Hideki; Takayasu, Misako

2017-07-11

Recently, growth mechanism of firms in complex business networks became new targets of scientific study owing to increasing availability of high quality business firms' data. Here, we paid attention to comprehensive data of M&A events for 40 years and derived empirical laws by applying methods and concepts of aggregation dynamics of aerosol physics. It is found that the probability of merger between bigger firms is bigger than that between smaller ones, and such tendency is enhancing year by year. We introduced a numerical model simulating the whole ecosystem of firms and showed that the system is already in an unstable monopoly state in which growth of middle sized firms are suppressed.

Spatially dynamic recurrent information flow across long-range dorsal motor network encodes selective motor goals.

PubMed

Yoo, Peter E; Hagan, Maureen A; John, Sam E; Opie, Nicholas L; Ordidge, Roger J; O'Brien, Terence J; Oxley, Thomas J; Moffat, Bradford A; Wong, Yan T

2018-06-01

Performing voluntary movements involves many regions of the brain, but it is unknown how they work together to plan and execute specific movements. We recorded high-resolution ultra-high-field blood-oxygen-level-dependent signal during a cued ankle-dorsiflexion task. The spatiotemporal dynamics and the patterns of task-relevant information flow across the dorsal motor network were investigated. We show that task-relevant information appears and decays earlier in the higher order areas of the dorsal motor network then in the primary motor cortex. Furthermore, the results show that task-relevant information is encoded in general initially, and then selective goals are subsequently encoded in specifics subregions across the network. Importantly, the patterns of recurrent information flow across the network vary across different subregions depending on the goal. Recurrent information flow was observed across all higher order areas of the dorsal motor network in the subregions encoding for the current goal. In contrast, only the top-down information flow from the supplementary motor cortex to the frontoparietal regions, with weakened recurrent information flow between the frontoparietal regions and bottom-up information flow from the frontoparietal regions to the supplementary cortex were observed in the subregions encoding for the opposing goal. We conclude that selective motor goal encoding and execution rely on goal-dependent differences in subregional recurrent information flow patterns across the long-range dorsal motor network areas that exhibit graded functional specialization. © 2018 Wiley Periodicals, Inc.

Reflection/suppression coatings for 900 - 1200 A radiation

NASA Technical Reports Server (NTRS)

Edelstein, Jerry

1989-01-01

The design and performance of multiple-layer, selective-reflection, selective-suppression coatings for the 900 - 1200 A band are described. These coatings are designed to optimize both high reflectivity at a desirable wavelength and low reflectivity at an undesirable wavelength. The minimum structure for a selective coating consists of a thin metal or metal oxide layer (50 - 150 A thickness) over an aluminum substrate protected with a semi-transparent dielectric (100 - 1000 A thickness). Predicted coating performance is strongly effected by varying the layer combination and thickness. A graphical method of optimizing the coating layer structure is developed. Aluminum, silicon, their oxides, and gold have been investigated as coating layer materials. A very simple coating with a 1026 to 1216 A reflectivity ratio greater than 100 was fabricated. Such reflection/suppression coatings may be of great utility to spaceborne EUV spectrographs.

Simultaneously selecting appropriate partners for gaming and strategy adaptation to enhance network reciprocity in the prisoner's dilemma

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-01-01

Network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium in 2 × 2 prisoner's dilemma games. Previous studies have shown that cooperation can be enhanced by using a skewed, rather than a random, selection of partners for either strategy adaptation or the gaming process. Here we show that combining both processes for selecting a gaming partner and an adaptation partner further enhances cooperation, provided that an appropriate selection rule and parameters are adopted. We also show that this combined model significantly enhances cooperation by reducing the degree of activity in the underlying network; we measure the degree of activity with a quantity called effective degree. More precisely, during the initial evolutionary stage in which the global cooperation fraction declines because initially allocated cooperators becoming defectors, the model shows that weak cooperative clusters perish and only a few strong cooperative clusters survive. This finding is the most important key to attaining significant network reciprocity.

Using Nonlinear Stochastic Evolutionary Game Strategy to Model an Evolutionary Biological Network of Organ Carcinogenesis Under a Natural Selection Scheme

PubMed Central

Chen, Bor-Sen; Tsai, Kun-Wei; Li, Cheng-Wei

2015-01-01

Molecular biologists have long recognized carcinogenesis as an evolutionary process that involves natural selection. Cancer is driven by the somatic evolution of cell lineages. In this study, the evolution of somatic cancer cell lineages during carcinogenesis was modeled as an equilibrium point (ie, phenotype of attractor) shifting, the process of a nonlinear stochastic evolutionary biological network. This process is subject to intrinsic random fluctuations because of somatic genetic and epigenetic variations, as well as extrinsic disturbances because of carcinogens and stressors. In order to maintain the normal function (ie, phenotype) of an evolutionary biological network subjected to random intrinsic fluctuations and extrinsic disturbances, a network robustness scheme that incorporates natural selection needs to be developed. This can be accomplished by selecting certain genetic and epigenetic variations to modify the network structure to attenuate intrinsic fluctuations efficiently and to resist extrinsic disturbances in order to maintain the phenotype of the evolutionary biological network at an equilibrium point (attractor). However, during carcinogenesis, the remaining (or neutral) genetic and epigenetic variations accumulate, and the extrinsic disturbances become too large to maintain the normal phenotype at the desired equilibrium point for the nonlinear evolutionary biological network. Thus, the network is shifted to a cancer phenotype at a new equilibrium point that begins a new evolutionary process. In this study, the natural selection scheme of an evolutionary biological network of carcinogenesis was derived from a robust negative feedback scheme based on the nonlinear stochastic Nash game strategy. The evolvability and phenotypic robustness criteria of the evolutionary cancer network were also estimated by solving a Hamilton–Jacobi inequality – constrained optimization problem. The simulation revealed that the phenotypic shift of the lung cancer

A Uniform Energy Consumption Algorithm for Wireless Sensor and Actuator Networks Based on Dynamic Polling Point Selection

PubMed Central

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2014-01-01

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455

Computer-Based Information Networks: Selected Examples.

ERIC Educational Resources Information Center

Hardesty, Larry

The history, purpose, and operation of six computer-based information networks are described in general and nontechnical terms. In the introduction the many definitions of an information network are explored. Ohio College Library Center's network (OCLC) is the first example. OCLC began in 1963, and since early 1973 has been extending its services…

Selective Disclosure of HIV Status in Egocentric Support Networks of People Living with HIV/AIDS

PubMed Central

Zang, Chunpeng; He, Xin

2014-01-01

The objective of this study was to investigate HIV disclosure activities in social support networks of people living with HIV/AIDS (PLWHAs). An egocentric network study was conducted in Nanning, China. A sample of 147 PLWHAs (egos) nominated 922 network members (alters) who would provide egos with social support. All egos disclosed their HIV status to at least one alter in their support networks and 26.5 % disclosed to all alters. Among network alters, 95.7 % of spouse alters, 59.9 % of other family member alters, and 29.7 % of friend alters were aware of egos’ HIV status. PLWHA egos were more likely to disclose their HIV status to their spouse and other family members, frequently-contacted alters, and alters who provided more social support. In addition, older egos and unmarried egos were more likely to disclose their HIV status. The findings indicate that network-based HIV intervention programs should take into consideration selective disclosure in social networks. PMID:24996393

Polymerization speed and diffractive experiments in polymer network LC test cells

NASA Astrophysics Data System (ADS)

Braun, Larissa; Gong, Zhen; Habibpourmoghadam, Atefeh; Schafforz, Samuel L.; Wolfram, Lukas; Lorenz, Alexander

2018-02-01

Polymer-network liquid crystals (LCs), where the response properties of a LC can be enhanced by the presence of a porous polymer network, are investigated. In the reported experiments, liquid crystals were doped with a small amount (< 10%) of photo-curable acrylate monomers. Samples with surface grafted photoinitiators, dissolvable photoinitiators, and samples with both kinds of photoinitiators were prepared. Both conventional (planar electrodes) and diffractive (interdigitated electrodes) test cells were used. These samples were exposed with a UV light source and changes of their capacitance were investigated with an LCR meter during exposure. Due to the presence of the in-situ generated polymer network, the electro-optic response properties of photo cured samples were enhanced. For example, their continuous phase modulation properties led to more localized responses in samples with interdigitated electrodes, which caused suppression of selected diffraction orders in the diffraction patterns recorded in polymer network LC samples. Moreover, capacitance changes were investigated during photopolymerization of a blue phase LC.

Functional Connectivity of the Dorsal Attention Network Predicts Selective Attention in 4-7 year-old Girls.

PubMed

Rohr, Christiane S; Vinette, Sarah A; Parsons, Kari A L; Cho, Ivy Y K; Dimond, Dennis; Benischek, Alina; Lebel, Catherine; Dewey, Deborah; Bray, Signe

2017-09-01

Early childhood is a period of profound neural development and remodeling during which attention skills undergo rapid maturation. Attention networks have been extensively studied in the adult brain, yet relatively little is known about changes in early childhood, and their relation to cognitive development. We investigated the association between age and functional connectivity (FC) within the dorsal attention network (DAN) and the association between FC and attention skills in early childhood. Functional magnetic resonance imaging data was collected during passive viewing in 44 typically developing female children between 4 and 7 years whose sustained, selective, and executive attention skills were assessed. FC of the intraparietal sulcus (IPS) and the frontal eye fields (FEF) was computed across the entire brain and regressed against age. Age was positively associated with FC between core nodes of the DAN, the IPS and the FEF, and negatively associated with FC between the DAN and regions of the default-mode network. Further, controlling for age, FC between the IPS and FEF was significantly associated with selective attention. These findings add to our understanding of early childhood development of attention networks and suggest that greater FC within the DAN is associated with better selective attention skills. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The use of a selective saturation pulse to suppress t1 noise in two-dimensional 1H fast magic angle spinning solid-state NMR spectroscopy

NASA Astrophysics Data System (ADS)

Robertson, Aiden J.; Pandey, Manoj Kumar; Marsh, Andrew; Nishiyama, Yusuke; Brown, Steven P.

2015-11-01

A selective saturation pulse at fast magic angle spinning (MAS) frequencies (60+ kHz) suppresses t1 noise in the indirect dimension of two-dimensional 1H MAS NMR spectra. The method is applied to a synthetic nucleoside with an intense methyl 1H signal due to triisopropylsilyl (TIPS) protecting groups. Enhanced performance in terms of suppressing the methyl signal while minimising the loss of signal intensity of nearby resonances of interest relies on reducing spin diffusion - this is quantified by comparing two-dimensional 1H NOESY-like spin diffusion spectra recorded at 30-70 kHz MAS. For a saturation pulse centred at the methyl resonance, the effect of changing the nutation frequency at different MAS frequencies as well as the effect of changing the pulse duration is investigated. By applying a pulse of duration 30 ms and nutation frequency 725 Hz at 70 kHz MAS, a good compromise of significant suppression of the methyl resonance combined with the signal intensity of resonances greater than 5 ppm away from the methyl resonance being largely unaffected is achieved. The effectiveness of using a selective saturation pulse is demonstrated for both homonuclear 1H-1H double quantum (DQ)/single quantum (SQ) MAS and 14N-1H heteronuclear multiple quantum coherence (HMQC) two-dimensional solid-state NMR experiments.

The use of a selective saturation pulse to suppress t1 noise in two-dimensional (1)H fast magic angle spinning solid-state NMR spectroscopy.

PubMed

Robertson, Aiden J; Pandey, Manoj Kumar; Marsh, Andrew; Nishiyama, Yusuke; Brown, Steven P

2015-11-01

A selective saturation pulse at fast magic angle spinning (MAS) frequencies (60+kHz) suppresses t1 noise in the indirect dimension of two-dimensional (1)H MAS NMR spectra. The method is applied to a synthetic nucleoside with an intense methyl (1)H signal due to triisopropylsilyl (TIPS) protecting groups. Enhanced performance in terms of suppressing the methyl signal while minimising the loss of signal intensity of nearby resonances of interest relies on reducing spin diffusion--this is quantified by comparing two-dimensional (1)H NOESY-like spin diffusion spectra recorded at 30-70 kHz MAS. For a saturation pulse centred at the methyl resonance, the effect of changing the nutation frequency at different MAS frequencies as well as the effect of changing the pulse duration is investigated. By applying a pulse of duration 30 ms and nutation frequency 725 Hz at 70 kHz MAS, a good compromise of significant suppression of the methyl resonance combined with the signal intensity of resonances greater than 5 ppm away from the methyl resonance being largely unaffected is achieved. The effectiveness of using a selective saturation pulse is demonstrated for both homonuclear (1)H-(1)H double quantum (DQ)/single quantum (SQ) MAS and (14)N-(1)H heteronuclear multiple quantum coherence (HMQC) two-dimensional solid-state NMR experiments. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Human behavior in Prisoner's Dilemma experiments suppresses network reciprocity

NASA Astrophysics Data System (ADS)

Gracia-Lázaro, Carlos; Cuesta, José A.; Sánchez, Angel; Moreno, Yamir

2012-03-01

During the last few years, much research has been devoted to strategic interactions on complex networks. In this context, the Prisoner's Dilemma has become a paradigmatic model, and it has been established that imitative evolutionary dynamics lead to very different outcomes depending on the details of the network. We here report that when one takes into account the real behavior of people observed in the experiments, both at the mean-field level and on utterly different networks, the observed level of cooperation is the same. We thus show that when human subjects interact in a heterogeneous mix including cooperators, defectors and moody conditional cooperators, the structure of the population does not promote or inhibit cooperation with respect to a well mixed population.

A Study for the Feature Selection to Identify GIEMSA-Stained Human Chromosomes Based on Artificial Neural Network

DTIC Science & Technology

2001-10-25

neural network (ANN) has been adopted for the human chromosome classification. It is important to select optimum features for training neural network...Many studies for computer-based chromosome analysis have shown that it is possible to classify chromosomes into 24 subgroups. In addition, artificial

Application of ecological criteria in selecting marine reserves and developing reserve networks

USGS Publications Warehouse

Roberts, Callum M.; Branch, George; Bustamante, Rodrigo H.; Castilla, Juan Carlos; Dugan, Jenifer; Halpern, Benjamin S.; Lafferty, Kevin D.; Leslie, Heather; McArdle, Deborah; Ruckelshaus, Mary; Warner, Robert R.

2003-01-01

Marine reserves are being established worldwide in response to a growing recognition of the conservation crisis that is building in the oceans. However, designation of reserves has been largely opportunistic, or protective measures have been implemented (often overlapping and sometimes in conflict) by different entities seeking to achieve different ends. This has created confusion among both users and enforcers, and the proliferation of different measures provides a false sense of protection where little is offered. This paper sets out a procedure grounded in current understanding of ecological processes, that allows the evaluation and selection of reserve sites in order to develop functional, interconnected networks of fully protected reserves that will fulfill multiple objectives. By fully protected we mean permanently closed to fishing and other resource extraction. We provide a framework that unifies the central aims of conservation and fishery management, while also meeting other human needs such as the provision of ecosystem services (e.g., maintenance of coastal water quality, shoreline protection, and recreational opportunities). In our scheme, candidate sites for reserves are evaluated against 12 criteria focused toward sustaining the biological integrity and productivity of marine systems at both local and regional scales. While a limited number of sites will be indispensable in a network, many will be of similar value as reserves, allowing the design of numerous alternative, biologically adequate networks. Devising multiple network designs will help ensure that ecological functionality is preserved throughout the socioeconomic evaluation process. Too often, socioeconomic criteria have dominated the process of reserve selection, potentially undermining their efficacy. We argue that application of biological criteria must precede and inform socioeconomic evaluation, since maintenance of ecosystem functioning is essential for meeting all of the goals for

Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study

NASA Astrophysics Data System (ADS)

Pfeil, Thomas; Jordan, Jakob; Tetzlaff, Tom; Grübl, Andreas; Schemmel, Johannes; Diesmann, Markus; Meier, Karlheinz

2016-04-01

High-level brain function, such as memory, classification, or reasoning, can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy-efficient substrate for the implementation of such neural computing architectures in technical applications and neuroscientific research. The functional performance of neural networks is often critically dependent on the level of correlations in the neural activity. In finite networks, correlations are typically inevitable due to shared presynaptic input. Recent theoretical studies have shown that inhibitory feedback, abundant in biological neural networks, can actively suppress these shared-input correlations and thereby enable neurons to fire nearly independently. For networks of spiking neurons, the decorrelating effect of inhibitory feedback has so far been explicitly demonstrated only for homogeneous networks of neurons with linear subthreshold dynamics. Theory, however, suggests that the effect is a general phenomenon, present in any system with sufficient inhibitory feedback, irrespective of the details of the network structure or the neuronal and synaptic properties. Here, we investigate the effect of network heterogeneity on correlations in sparse, random networks of inhibitory neurons with nonlinear, conductance-based synapses. Emulations of these networks on the analog neuromorphic-hardware system Spikey allow us to test the efficiency of decorrelation by inhibitory feedback in the presence of hardware-specific heterogeneities. The configurability of the hardware substrate enables us to modulate the extent of heterogeneity in a systematic manner. We selectively study the effects of shared input and recurrent connections on correlations in membrane potentials and spike trains. Our results confirm that shared-input correlations are actively suppressed by inhibitory feedback also in highly heterogeneous networks exhibiting broad, heavy-tailed firing

Hop Optimization and Relay Node Selection in Multi-hop Wireless Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Li, Xiaohua(Edward)

In this paper we propose an efficient approach to determine the optimal hops for multi-hop ad hoc wireless networks. Based on the assumption that nodes use successive interference cancellation (SIC) and maximal ratio combining (MRC) to deal with mutual interference and to utilize all the received signal energy, we show that the signal-to-interference-plus-noise ratio (SINR) of a node is determined only by the nodes before it, not the nodes after it, along a packet forwarding path. Based on this observation, we propose an iterative procedure to select the relay nodes and to calculate the path SINR as well as capacity of an arbitrary multi-hop packet forwarding path. The complexity of the algorithm is extremely low, and scaling well with network size. The algorithm is applicable in arbitrarily large networks. Its performance is demonstrated as desirable by simulations. The algorithm can be helpful in analyzing the performance of multi-hop wireless networks.

U1snRNP-mediated suppression of polyadenylation in conjunction with the RNA structure controls poly (A) site selection in foamy viruses

PubMed Central

2013-01-01

Background During reverse transcription, retroviruses duplicate the long terminal repeats (LTRs). These identical LTRs carry both promoter regions and functional polyadenylation sites. To express full-length transcripts, retroviruses have to suppress polyadenylation in the 5′LTR and activate polyadenylation in the 3′LTR. Foamy viruses have a unique LTR structure with respect to the location of the major splice donor (MSD), which is located upstream of the polyadenylation signal. Results Here, we describe the mechanisms of foamy viruses regulating polyadenylation. We show that binding of the U1 small nuclear ribonucleoprotein (U1snRNP) to the MSD suppresses polyadenylation at the 5′LTR. In contrast, polyadenylation at the 3′LTR is achieved by adoption of a different RNA structure at the MSD region, which blocks U1snRNP binding and furthers RNA cleavage and subsequent polyadenylation. Conclusion Recently, it was shown that U1snRNP is able to suppress the usage of intronic cryptic polyadenylation sites in the cellular genome. Foamy viruses take advantage of this surveillance mechanism to suppress premature polyadenylation at the 5’end of their RNA. At the 3’end, Foamy viruses use a secondary structure to presumably block access of U1snRNP and thereby activate polyadenylation at the end of the genome. Our data reveal a contribution of U1snRNP to cellular polyadenylation site selection and to the regulation of gene expression. PMID:23718736

Outage Performance Analysis of Relay Selection Schemes in Wireless Energy Harvesting Cooperative Networks over Non-Identical Rayleigh Fading Channels †

PubMed Central

Do, Nhu Tri; Bao, Vo Nguyen Quoc; An, Beongku

2016-01-01

In this paper, we study relay selection in decode-and-forward wireless energy harvesting cooperative networks. In contrast to conventional cooperative networks, the relays harvest energy from the source’s radio-frequency radiation and then use that energy to forward the source information. Considering power splitting receiver architecture used at relays to harvest energy, we are concerned with the performance of two popular relay selection schemes, namely, partial relay selection (PRS) scheme and optimal relay selection (ORS) scheme. In particular, we analyze the system performance in terms of outage probability (OP) over independent and non-identical (i.n.i.d.) Rayleigh fading channels. We derive the closed-form approximations for the system outage probabilities of both schemes and validate the analysis by the Monte-Carlo simulation. The numerical results provide comprehensive performance comparison between the PRS and ORS schemes and reveal the effect of wireless energy harvesting on the outage performances of both schemes. Additionally, we also show the advantages and drawbacks of the wireless energy harvesting cooperative networks and compare to the conventional cooperative networks. PMID:26927119

Selective fertilization with phosphite allows unhindered growth of cotton plants expressing the ptxD gene while suppressing weeds.

PubMed

Pandeya, Devendra; López-Arredondo, Damar L; Janga, Madhusudhana R; Campbell, LeAnne M; Estrella-Hernández, Priscila; Bagavathiannan, Muthukumar V; Herrera-Estrella, Luis; Rathore, Keerti S

2018-06-04

Weeds, which have been the bane of agriculture since the beginning of civilization, are managed manually, mechanically, and, more recently, by chemicals. However, chemical control options are rapidly shrinking due to the recent rise in the number of herbicide-resistant weeds in crop fields, with few alternatives on the horizon. Therefore, there is an urgent need for alternative weed suppression systems to sustain crop productivity while reducing our dependence on herbicides and tillage. Such a development will also allay some of the negative perceptions associated with the use of herbicide-resistance genes and heavy dependence on herbicides. Transgenic plants expressing the bacterial phosphite dehydrogenase ( ptxD ) gene gain an ability to convert phosphite (Phi) into orthophosphate [Pi, the metabolizable form of phosphorus (P)]. Such plants allow for a selective fertilization scheme, based on Phi as the sole source of P for the crop, while offering an effective alternative for suppressing weed growth. Here, we show that, when P is supplied in the form of Phi, ptxD -expressing cotton ( Gossypium hirsutum L.) plants outcompete, in both artificial substrates and natural soils from agricultural fields, three different monocot and dicot weed species intentionally introduced in the experiments, as well as weeds naturally present in the tested soils. Importantly, the ptxD /Phi system proved highly efficacious in inhibiting the growth of glyphosate-resistant Palmer amaranth. With over 250 weed species resistant to currently available herbicides, ptxD -transgenic plants fertilized with Phi could provide an effective alternative to suppressing the growth of these weeds while providing adequate nutrition to the crop. Copyright © 2018 the Author(s). Published by PNAS.

Analyzing heterogeneity in the effects of physical activity in children on social network structure and peer selection dynamics

PubMed Central

Henry, Teague; Gesell, Sabina B.; Ip, Edward H.

2016-01-01

Background Social networks influence children and adolescents’ physical activity. The focus of this paper is to examine the differences in the effects of physical activity on friendship selection, with eye to the implications on physical activity interventions for young children. Network interventions to increase physical activity are warranted but have not been conducted. Prior to implementing a network intervention in the field, it is important to understand potential heterogeneities in the effects that activity level have on network structure. In this study, the associations between activity level and cross sectional network structure, and activity level and change in network structure are assessed. Methods We studied a real-world friendship network among 81 children (average age 7.96 years) who lived in low SES neighborhoods, attended public schools, and attended one of two structured aftercare programs, of which one has existed and the other was new. We used the exponential random graph model (ERGMs) and its longitudinal extension to evaluate the association between activity level and various demographic factors in having, forming, and dissolving friendship. Due to heterogeneity between the friendship networks within the aftercare programs, separate analyses were conducted for each network. Results There was heterogeneity in the effect of physical activity on both cross sectional network structure and the formation and dissolution processes, both across time and between networks. Conclusions Network analysis could be used to assess the unique structure and dynamics of a social network before an intervention is implemented, so as to optimize the effects of the network intervention for increasing childhood physical activity. Additionally, if peer selection processes are changing within a network, a static network intervention strategy for childhood physical activity could become inefficient as the network evolves. PMID:27867518

Parallel Regulation of Memory and Emotion Supports the Suppression of Intrusive Memories

PubMed Central

Anderson, Michael C.

2017-01-01

Intrusive memories often take the form of distressing images that emerge into a person's awareness, unbidden. A fundamental goal of clinical neuroscience is to understand the mechanisms allowing people to control these memory intrusions and reduce their emotional impact. Mnemonic control engages a right frontoparietal network that interrupts episodic retrieval by modulating hippocampal activity; less is known, however, about how this mechanism contributes to affect regulation. Here we report evidence in humans (males and females) that stopping episodic retrieval to suppress an unpleasant image triggers parallel inhibition of mnemonic and emotional content. Using fMRI, we found that regulation of both mnemonic and emotional content was driven by a shared frontoparietal inhibitory network and was predicted by a common profile of medial temporal lobe downregulation involving the anterior hippocampus and the amygdala. Critically, effective connectivity analysis confirmed that reduced amygdala activity was not merely an indirect consequence of hippocampal suppression; rather, both the hippocampus and the amygdala were targeted by a top-down inhibitory control signal originating from the dorsolateral prefrontal cortex. This negative coupling was greater when unwanted memories intruded into awareness and needed to be purged. Together, these findings support the broad principle that retrieval suppression is achieved by regulating hippocampal processes in tandem with domain-specific brain regions involved in reinstating specific content, in an activity-dependent fashion. SIGNIFICANCE STATEMENT Upsetting events sometimes trigger intrusive images that cause distress and that may contribute to psychiatric disorders. People often respond to intrusions by suppressing their retrieval, excluding them from awareness. Here we examined whether suppressing aversive images might also alter emotional responses to them, and the mechanisms underlying such changes. We found that the better

A Novel Complex-Coefficient In-Band Interference Suppression Algorithm for Cognitive Ultra-Wide Band Wireless Sensors Networks.

PubMed

Xiong, Hailiang; Zhang, Wensheng; Xu, Hongji; Du, Zhengfeng; Tang, Huaibin; Li, Jing

2017-05-25

With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been considered as significant solutions to solve the harmonious coexistence issues. UWB wireless sensors can share the spectrum with primary user (PU) systems without harmful interference. The in-band interference of UWB systems should be considered because such interference can severely affect the transmissions of UWB wireless systems. In order to solve the in-band interference issues for UWB wireless sensor networks (WSN), a novel in-band narrow band interferences (NBIs) elimination scheme is proposed in this paper. The proposed narrow band interferences suppression scheme is based on a novel complex-coefficient adaptive notch filter unit with a single constrained zero-pole pair. Moreover, in order to reduce the computation complexity of the proposed scheme, an adaptive complex-coefficient iterative method based on two-order Taylor series is designed. To cope with multiple narrow band interferences, a linear cascaded high order adaptive filter and a cyclic cascaded high order matrix adaptive filter (CCHOMAF) interference suppression algorithm based on the basic adaptive notch filter unit are also presented. The theoretical analysis and numerical simulation results indicate that the proposed CCHOMAF algorithm can achieve better performance in terms of average bit error rate for UWB WSNs. The proposed in-band NBIs elimination scheme can significantly improve the reception performance of low-cost and low-power UWB wireless systems.

A Novel Complex-Coefficient In-Band Interference Suppression Algorithm for Cognitive Ultra-Wide Band Wireless Sensors Networks

PubMed Central

Xiong, Hailiang; Zhang, Wensheng; Xu, Hongji; Du, Zhengfeng; Tang, Huaibin; Li, Jing

2017-01-01

With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been considered as significant solutions to solve the harmonious coexistence issues. UWB wireless sensors can share the spectrum with primary user (PU) systems without harmful interference. The in-band interference of UWB systems should be considered because such interference can severely affect the transmissions of UWB wireless systems. In order to solve the in-band interference issues for UWB wireless sensor networks (WSN), a novel in-band narrow band interferences (NBIs) elimination scheme is proposed in this paper. The proposed narrow band interferences suppression scheme is based on a novel complex-coefficient adaptive notch filter unit with a single constrained zero-pole pair. Moreover, in order to reduce the computation complexity of the proposed scheme, an adaptive complex-coefficient iterative method based on two-order Taylor series is designed. To cope with multiple narrow band interferences, a linear cascaded high order adaptive filter and a cyclic cascaded high order matrix adaptive filter (CCHOMAF) interference suppression algorithm based on the basic adaptive notch filter unit are also presented. The theoretical analysis and numerical simulation results indicate that the proposed CCHOMAF algorithm can achieve better performance in terms of average bit error rate for UWB WSNs. The proposed in-band NBIs elimination scheme can significantly improve the reception performance of low-cost and low-power UWB wireless systems. PMID:28587085

Suppressing epidemics with a limited amount of immunization units.

PubMed

Schneider, Christian M; Mihaljev, Tamara; Havlin, Shlomo; Herrmann, Hans J

2011-12-01

The way diseases spread through schools, epidemics through countries, and viruses through the internet is crucial in determining their risk. Although each of these threats has its own characteristics, its underlying network determines the spreading. To restrain the spreading, a widely used approach is the fragmentation of these networks through immunization, so that epidemics cannot spread. Here we develop an immunization approach based on optimizing the susceptible size, which outperforms the best known strategy based on immunizing the highest-betweenness links or nodes. We find that the network's vulnerability can be significantly reduced, demonstrating this on three different real networks: the global flight network, a school friendship network, and the internet. In all cases, we find that not only is the average infection probability significantly suppressed, but also for the most relevant case of a small and limited number of immunization units the infection probability can be reduced by up to 55%.

Detection of burst suppression patterns in EEG using recurrence rate.

PubMed

Liang, Zhenhu; Wang, Yinghua; Ren, Yongshao; Li, Duan; Voss, Logan; Sleigh, Jamie; Li, Xiaoli

2014-01-01

Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severely reduced brain activity such as overdose of general anesthesia. It is important to detect burst suppression reliably during the administration of anesthetic or sedative agents, especially for cerebral-protective treatments in various neurosurgical diseases. This study investigates recurrent plot (RP) analysis for the detection of the burst suppression pattern (BSP) in EEG. The RP analysis is applied to EEG data containing BSPs collected from 14 patients. Firstly we obtain the best selection of parameters for RP analysis. Then, the recurrence rate (RR), determinism (DET), and entropy (ENTR) are calculated. Then RR was selected as the best BSP index one-way analysis of variance (ANOVA) and multiple comparison tests. Finally, the performance of RR analysis is compared with spectral analysis, bispectral analysis, approximate entropy, and the nonlinear energy operator (NLEO). ANOVA and multiple comparison tests showed that the RR could detect BSP and that it was superior to other measures with the highest sensitivity of suppression detection (96.49%, P = 0.03). Tracking BSP patterns is essential for clinical monitoring in critically ill and anesthetized patients. The purposed RR may provide an effective burst suppression detector for developing new patient monitoring systems.

Non-disruptive tactics of suppression are superior in countering terrorism, insurgency, and financial panics.

PubMed

Siegel, David A

2011-04-13

Suppressing damaging aggregate behaviors such as insurgency, terrorism, and financial panics are important tasks of the state. Each outcome of these aggregate behaviors is an emergent property of a system in which each individual's action depends on a subset of others' actions, given by each individual's network of interactions. Yet there are few explicit comparisons of strategies for suppression, and none that fully incorporate the interdependence of individual behavior. Here I show that suppression tactics that do not require the removal of individuals from networks of interactions are nearly always more effective than those that do. I find using simulation analysis of a general model of interdependent behavior that the degree to which such less disruptive suppression tactics are superior to more disruptive ones increases in the propensity of individuals to engage in the behavior in question. Thus, hearts-and-minds approaches are generally more effective than force in counterterrorism and counterinsurgency, and partial insurance is usually a better tactic than gag rules in quelling financial panics. Differences between suppression tactics are greater when individual incentives to support terrorist or insurgent groups, or susceptibilities to financial panic, are higher. These conclusions have utility for policy-makers seeking to end bloody conflicts and prevent financial panics. As the model also applies to mass protest, its conclusions provide insight as well into the likely effects of different suppression strategies undertaken by authoritarian regimes seeking to hold on to power in the face of mass movements seeking to end them.

Age-related differences in enhancement and suppression of neural activity underlying selective attention in matched young and old adults.

PubMed

Haring, A E; Zhuravleva, T Y; Alperin, B R; Rentz, D M; Holcomb, P J; Daffner, K R

2013-03-07

Selective attention reflects the top-down control of sensory processing that is mediated by enhancement or inhibition of neural activity. ERPs were used to investigate age-related differences in neural activity in an experiment examining selective attention to color under Attend and Ignore conditions, as well as under a Neutral condition in which color was task-irrelevant. We sought to determine whether differences in neural activity between old and young adult subjects were due to differences in age rather than executive capacity. Old subjects were matched to two groups of young subjects on the basis of neuropsychological test performance: one using age-appropriate norms and the other using test scores not adjusted for age. We found that old and young subject groups did not differ in the overall modulation of selective attention between Attend and Ignore conditions, as indexed by the size of the anterior Selection Positivity. However, in contrast to either young adult group, old subjects did not exhibit reduced neural activity under the Ignore relative to Neutral condition, but showed enhanced activity under the Attend condition. The onset and peak of the Selection Positivity occurred later for old than young subjects. In summary, older adults execute selective attention less efficiently than matched younger subjects, with slowed processing and failed suppression under Ignore. Increased enhancement under Attend may serve as a compensatory mechanism. Copyright © 2013 Elsevier B.V. All rights reserved.

Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

USGS Publications Warehouse

Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.

2011-01-01

Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

Expression level, cellular compartment and metabolic network position all influence the average selective constraint on mammalian enzymes

PubMed Central

2011-01-01

Background A gene's position in regulatory, protein interaction or metabolic networks can be predictive of the strength of purifying selection acting on it, but these relationships are neither universal nor invariably strong. Following work in bacteria, fungi and invertebrate animals, we explore the relationship between selective constraint and metabolic function in mammals. Results We measure the association between selective constraint, estimated by the ratio of nonsynonymous (Ka) to synonymous (Ks) substitutions, and several, primarily metabolic, measures of gene function. We find significant differences between the selective constraints acting on enzyme-coding genes from different cellular compartments, with the nucleus showing higher constraint than genes from either the cytoplasm or the mitochondria. Among metabolic genes, the centrality of an enzyme in the metabolic network is significantly correlated with Ka/Ks. In contrast to yeasts, gene expression magnitude does not appear to be the primary predictor of selective constraint in these organisms. Conclusions Our results imply that the relationship between selective constraint and enzyme centrality is complex: the strength of selective constraint acting on mammalian genes is quite variable and does not appear to exclusively follow patterns seen in other organisms. PMID:21470417

A neural network-based input shaping for swing suppression of an overhead crane under payload hoisting and mass variations

NASA Astrophysics Data System (ADS)

Ramli, Liyana; Mohamed, Z.; Jaafar, H. I.

2018-07-01

This paper proposes an improved input shaping for minimising payload swing of an overhead crane with payload hoisting and payload mass variations. A real time unity magnitude zero vibration (UMZV) shaper is designed by using an artificial neural network trained by particle swarm optimisation. The proposed technique could predict and directly update the shaper's parameters in real time to handle the effects of time-varying parameters during the crane operation with hoisting. To evaluate the performances of the proposed method, experiments are conducted on a laboratory overhead crane with a payload hoisting, different payload masses and two different crane motions. The superiority of the proposed method is confirmed by reductions of at least 38.9% and 91.3% in the overall and residual swing responses, respectively over a UMZV shaper designed using an average operating frequency and a robust shaper namely Zero Vibration Derivative-Derivative (ZVDD). The proposed method also demonstrates a significant residual swing suppression as compared to a ZVDD shaper designed based on varying frequency. In addition, the significant reductions are achieved with a less shaper duration resulting in a satisfactory speed of response. It is envisaged that the proposed method can be used for designing effective input shapers for payload swing suppression of a crane with time-varying parameters and for a crane that employ finite actuation states.

Resilience of networks to environmental stress: From regular to random networks

NASA Astrophysics Data System (ADS)

Eom, Young-Ho

2018-04-01

Despite the huge interest in network resilience to stress, most of the studies have concentrated on internal stress damaging network structure (e.g., node removals). Here we study how networks respond to environmental stress deteriorating their external conditions. We show that, when regular networks gradually disintegrate as environmental stress increases, disordered networks can suddenly collapse at critical stress with hysteresis and vulnerability to perturbations. We demonstrate that this difference results from a trade-off between node resilience and network resilience to environmental stress. The nodes in the disordered networks can suppress their collapses due to the small-world topology of the networks but eventually collapse all together in return. Our findings indicate that some real networks can be highly resilient against environmental stress to a threshold yet extremely vulnerable to the stress above the threshold because of their small-world topology.

Pressure to drink but not to smoke: disentangling selection and socialization in adolescent peer networks and peer groups.

PubMed

Kiuru, Noona; Burk, William J; Laursen, Brett; Salmela-Aro, Katariina; Nurmi, Jari-Erik

2010-12-01

This paper examined the relative influence of selection and socialization on alcohol and tobacco use in adolescent peer networks and peer groups. The sample included 1419 Finnish secondary education students (690 males and 729 females, mean age 16 years at the outset) from nine schools. Participants identified three school friends and described their alcohol and tobacco use on two occasions one year apart. Actor-based models simultaneously examined changes in peer network ties and changes in individual behaviors for all participants within each school. Multi-level analyses examined changes in individual behaviors for adolescents entering new peer groups and adolescents in stable peer groups, both of which were embedded within the school-based peer networks. Similar results emerged from both analytic methods: Selection and socialization contributed to similarity of alcohol use, but only selection was a factor in tobacco use. Copyright © 2010 The Association for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Optical signal suppression by a cascaded SOA/RSOA for wavelength reusing reflective PON upstream transmission.

PubMed

Jung, Sang Min; Mun, Kyoung Hak; Kang, Soo Min; Han, Sang Kook

2017-09-18

An optical signal suppression technique based on a cascaded SOA and RSOA is proposed for the reflective passive optical networks (PONs) with wavelength division multiplexing (WDM). By suppressing the downstream signal of the optical carrier, the proposed reflective PON effectively reuses the downstream optical carrier for upstream signal transmission. As an experimental demonstration, we show that the proposed optical signal suppression technique is effective in terms of the signal bandwidth and bit-error-rate (BER) performance of the remodulated upstream transmission.

Visual short-term memory load suppresses temporo-parietal junction activity and induces inattentional blindness.

PubMed

Todd, J Jay; Fougnie, Daryl; Marois, René

2005-12-01

The right temporo-parietal junction (TPJ) is critical for stimulus-driven attention and visual awareness. Here we show that as the visual short-term memory (VSTM) load of a task increases, activity in this region is increasingly suppressed. Correspondingly, increasing VSTM load impairs the ability of subjects to consciously detect the presence of a novel, unexpected object in the visual field. These results not only demonstrate that VSTM load suppresses TPJ activity and induces inattentional blindness, but also offer a plausible neural mechanism for this perceptual deficit: suppression of the stimulus-driven attentional network.

The modification of siRNA with 3' cholesterol to increase nuclease protection and suppression of native mRNA by select siRNA polyplexes.

PubMed

Ambardekar, Vishakha V; Han, Huai-Yun; Varney, Michelle L; Vinogradov, Serguei V; Singh, Rakesh K; Vetro, Joseph A

2011-02-01

Polymer-siRNA complexes (siRNA polyplexes) are being actively developed to improve the therapeutic application of siRNA. A major limitation for many siRNA polyplexes, however, is insufficient mRNA suppression. Given that modifying the sense strand of siRNA with 3' cholesterol (chol-siRNA) increases the activity of free nuclease-resistant siRNA in vitro and in vivo, we hypothesized that complexation of chol-siRNA can increase mRNA suppression by siRNA polyplexes. In this study, the characteristics and siRNA activity of self assembled polyplexes formed with chol-siRNA or unmodified siRNA were compared using three types of conventional, positively charged polymers: (i) biodegradable, cross-linked nanogels (BDNG) (ii) graft copolymers (PEI-PEG), and (iii) linear block copolymers (PLL10-PEG, and PLL50-PEG). Chol-siRNA did not alter complex formation or the resistance of polyplexes to siRNA displacement by heparin but increased nuclease protection by BDNG, PLL10-PEG, and PLL50-PEG polyplexes over polyplexes with unmodified siRNA. Chol-CYPB siRNA increased suppression of native CYPB mRNA in mammary microvascular endothelial cells (MVEC) by BDNG polyplexes (35%) and PLL10-PEG polyplexes (69%) over comparable CYPB siRNA polyplexes but had no effect on PEI-PEG or PLL50-PEG polyplexes. Overall, these results indicate that complexation of chol-siRNA increases nuclease protection and mRNA suppression by select siRNA polyplexes. These results also suggest that polycationic block length is an important factor in increasing mRNA suppression by PLL-PEG chol-siRNA polyplexes in mammary MVEC. Copyright © 2010 Elsevier Ltd. All rights reserved.

Characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts

NASA Astrophysics Data System (ADS)

Chen, Siyue; Leung, Henry; Dondo, Maxwell

2014-05-01

As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.

Moving stimuli are less effectively masked using traditional continuous flash suppression (CFS) compared to a moving Mondrian mask (MMM): a test case for feature-selective suppression and retinotopic adaptation.

PubMed

Moors, Pieter; Wagemans, Johan; de-Wit, Lee

2014-01-01

Continuous flash suppression (CFS) is a powerful interocular suppression technique, which is often described as an effective means to reliably suppress stimuli from visual awareness. Suppression through CFS has been assumed to depend upon a reduction in (retinotopically specific) neural adaptation caused by the continual updating of the contents of the visual input to one eye. In this study, we started from the observation that suppressing a moving stimulus through CFS appeared to be more effective when using a mask that was actually more prone to retinotopically specific neural adaptation, but in which the properties of the mask were more similar to those of the to-be-suppressed stimulus. In two experiments, we find that using a moving Mondrian mask (i.e., one that includes motion) is more effective in suppressing a moving stimulus than a regular CFS mask. The observed pattern of results cannot be explained by a simple simulation that computes the degree of retinotopically specific neural adaptation over time, suggesting that this kind of neural adaptation does not play a large role in predicting the differences between conditions in this context. We also find some evidence consistent with the idea that the most effective CFS mask is the one that matches the properties (speed) of the suppressed stimulus. These results question the general importance of retinotopically specific neural adaptation in CFS, and potentially help to explain an implicit trend in the literature to adapt one's CFS mask to match one's to-be-suppressed stimuli. Finally, the results should help to guide the methodological development of future research where continuous suppression of moving stimuli is desired.

How to inhibit a distractor location? Statistical learning versus active, top-down suppression.

PubMed

Wang, Benchi; Theeuwes, Jan

2018-05-01

Recently, Wang and Theeuwes (Journal of Experimental Psychology: Human Perception and Performance, 44(1), 13-17, 2018a) demonstrated the role of lingering selection biases in an additional singleton search task in which the distractor singleton appeared much more often in one location than in all other locations. For this location, there was less capture and selection efficiency was reduced. It was argued that statistical learning induces plasticity within the spatial priority map such that particular locations that are high likely to contain a distractor are suppressed relative to all other locations. The current study replicated these findings regarding statistical learning (Experiment 1) and investigated whether similar effects can be obtained by cueing the distractor location in a top-down way on a trial-by-trial basis. The results show that top-down cueing of the distractor location with long (1,500 ms; Experiment 2) and short stimulus-onset symmetries (SOAs) (600 ms; Experiment 3) does not result in suppression: The amount of capture nor the efficiency of selection was affected by the cue. If anything, we found an attentional benefit (instead of the suppression) for the short SOA. We argue that through statistical learning, weights within the attentional priority map are changed such that one location containing a salient distractor is suppressed relative to all other locations. Our cueing experiments show that this effect cannot be accomplished by active, top-down suppression. Consequences for recent theories of distractor suppression are discussed.

Lateral and feedforward inhibition suppress asynchronous activity in a large, biophysically-detailed computational model of the striatal network

PubMed Central

Moyer, Jason T.; Halterman, Benjamin L.; Finkel, Leif H.; Wolf, John A.

2014-01-01

Striatal medium spiny neurons (MSNs) receive lateral inhibitory projections from other MSNs and feedforward inhibitory projections from fast-spiking, parvalbumin-containing striatal interneurons (FSIs). The functional roles of these connections are unknown, and difficult to study in an experimental preparation. We therefore investigated the functionality of both lateral (MSN-MSN) and feedforward (FSI-MSN) inhibition using a large-scale computational model of the striatal network. The model consists of 2744 MSNs comprised of 189 compartments each and 121 FSIs comprised of 148 compartments each, with dendrites explicitly represented and almost all known ionic currents included and strictly constrained by biological data as appropriate. Our analysis of the model indicates that both lateral inhibition and feedforward inhibition function at the population level to limit non-ensemble MSN spiking while preserving ensemble MSN spiking. Specifically, lateral inhibition enables large ensembles of MSNs firing synchronously to strongly suppress non-ensemble MSNs over a short time-scale (10–30 ms). Feedforward inhibition enables FSIs to strongly inhibit weakly activated, non-ensemble MSNs while moderately inhibiting activated ensemble MSNs. Importantly, FSIs appear to more effectively inhibit MSNs when FSIs fire asynchronously. Both types of inhibition would increase the signal-to-noise ratio of responding MSN ensembles and contribute to the formation and dissolution of MSN ensembles in the striatal network. PMID:25505406

Computerized stratified random site-selection approaches for design of a ground-water-quality sampling network

USGS Publications Warehouse

Scott, J.C.

1990-01-01

Computer software was written to randomly select sites for a ground-water-quality sampling network. The software uses digital cartographic techniques and subroutines from a proprietary geographic information system. The report presents the approaches, computer software, and sample applications. It is often desirable to collect ground-water-quality samples from various areas in a study region that have different values of a spatial characteristic, such as land-use or hydrogeologic setting. A stratified network can be used for testing hypotheses about relations between spatial characteristics and water quality, or for calculating statistical descriptions of water-quality data that account for variations that correspond to the spatial characteristic. In the software described, a study region is subdivided into areal subsets that have a common spatial characteristic to stratify the population into several categories from which sampling sites are selected. Different numbers of sites may be selected from each category of areal subsets. A population of potential sampling sites may be defined by either specifying a fixed population of existing sites, or by preparing an equally spaced population of potential sites. In either case, each site is identified with a single category, depending on the value of the spatial characteristic of the areal subset in which the site is located. Sites are selected from one category at a time. One of two approaches may be used to select sites. Sites may be selected randomly, or the areal subsets in the category can be grouped into cells and sites selected randomly from each cell.

Evolution of Boolean networks under selection for a robust response to external inputs yields an extensive neutral space

NASA Astrophysics Data System (ADS)

Szejka, Agnes; Drossel, Barbara

2010-02-01

We study the evolution of Boolean networks as model systems for gene regulation. Inspired by biological networks, we select simultaneously for robust attractors and for the ability to respond to external inputs by changing the attractor. Mutations change the connections between the nodes and the update functions. In order to investigate the influence of the type of update functions, we perform our simulations with canalizing as well as with threshold functions. We compare the properties of the fitness landscapes that result for different versions of the selection criterion and the update functions. We find that for all studied cases the fitness landscape has a plateau with maximum fitness resulting in the fact that structurally very different networks are able to fulfill the same task and are connected by neutral paths in network (“genotype”) space. We find furthermore a connection between the attractor length and the mutational robustness, and an extremely long memory of the initial evolutionary stage.

Suppression of Rayleigh backscattering noise using cascaded-SOA and microwave photonic filter for 10 Gb/s loop-back WDM-PON.

PubMed

Feng, Hanlin; Ge, Jia; Xiao, Shilin; Fok, Mable P

2014-05-19

In this paper, we present a novel Rayleigh backscattering (RB) noise mitigation scheme based on central carrier suppression for 10 Gb/s loop-back wavelength division multiplexing passive optical network (WDM-PON). Microwave modulated multi-subcarrier optical signal is used as downstream seeding light, while cascaded semiconductor optical amplifier (SOA) are used in the optical network unit (ONU) for suppressing the central carrier of the multi-subcarrier upstream signal. With central carrier suppression, interference generated by carrier RB noise at low frequency region is eliminated successfully. Transmission performance over 45 km single mode fiber (SMF) is studied experimentally, and the optical-signal-to-Rayleigh-noise-ratio (OSRNR) can be reduced to 15 dB with central carrier suppression ratio (CCSR) of 21 dB. Receiver sensitivity is further improved by 6 dB with the use of microwave photonic filter (MPF) for suppressing residual upstream microwave signal and residual carrier RB at high frequency region.

Sample selection via angular distance in the space of the arguments of an artificial neural network

NASA Astrophysics Data System (ADS)

Fernández Jaramillo, J. M.; Mayerle, R.

2018-05-01

In the construction of an artificial neural network (ANN) a proper data splitting of the available samples plays a major role in the training process. This selection of subsets for training, testing and validation affects the generalization ability of the neural network. Also the number of samples has an impact in the time required for the design of the ANN and the training. This paper introduces an efficient and simple method for reducing the set of samples used for training a neural network. The method reduces the required time to calculate the network coefficients, while keeping the diversity and avoiding overtraining the ANN due the presence of similar samples. The proposed method is based on the calculation of the angle between two vectors, each one representing one input of the neural network. When the angle formed among samples is smaller than a defined threshold only one input is accepted for the training. The accepted inputs are scattered throughout the sample space. Tidal records are used to demonstrate the proposed method. The results of a cross-validation show that with few inputs the quality of the outputs is not accurate and depends on the selection of the first sample, but as the number of inputs increases the accuracy is improved and differences among the scenarios with a different starting sample have and important reduction. A comparison with the K-means clustering algorithm shows that for this application the proposed method with a smaller number of samples is producing a more accurate network.

Non-Disruptive Tactics of Suppression Are Superior in Countering Terrorism, Insurgency, and Financial Panics

PubMed Central

Siegel, David A.

2011-01-01

Background Suppressing damaging aggregate behaviors such as insurgency, terrorism, and financial panics are important tasks of the state. Each outcome of these aggregate behaviors is an emergent property of a system in which each individual's action depends on a subset of others' actions, given by each individual's network of interactions. Yet there are few explicit comparisons of strategies for suppression, and none that fully incorporate the interdependence of individual behavior. Methods and Findings Here I show that suppression tactics that do not require the removal of individuals from networks of interactions are nearly always more effective than those that do. I find using simulation analysis of a general model of interdependent behavior that the degree to which such less disruptive suppression tactics are superior to more disruptive ones increases in the propensity of individuals to engage in the behavior in question. Conclusions Thus, hearts-and-minds approaches are generally more effective than force in counterterrorism and counterinsurgency, and partial insurance is usually a better tactic than gag rules in quelling financial panics. Differences between suppression tactics are greater when individual incentives to support terrorist or insurgent groups, or susceptibilities to financial panic, are higher. These conclusions have utility for policy-makers seeking to end bloody conflicts and prevent financial panics. As the model also applies to mass protest, its conclusions provide insight as well into the likely effects of different suppression strategies undertaken by authoritarian regimes seeking to hold on to power in the face of mass movements seeking to end them. PMID:21533247

Altered characteristic of brain networks in mild cognitive impairment during a selective attention task: An EEG study.

PubMed

Wei, Ling; Li, Yingjie; Yang, Xiaoli; Xue, Qing; Wang, Yuping

2015-10-01

The present study evaluated the topological properties of whole brain networks using graph theoretical concepts and investigated the time-evolution characteristic of brain network in mild cognitive impairment patients during a selective attention task. Electroencephalography (EEG) activities were recorded in 10 MCI patients and 17 healthy subjects when they performed a color match task. We calculated the phase synchrony index between each possible pairs of EEG channels in alpha and beta frequency bands and analyzed the local interconnectedness, overall connectedness and small-world characteristic of brain network in different degree for two groups. Relative to healthy normal controls, the properties of cortical networks in MCI patients tend to be a shift of randomization. Lower σ of MCI had suggested that patients had a further loss of small-world attribute both during active and resting states. Our results provide evidence for the functional disconnection of brain regions in MCI. Furthermore, we found the properties of cortical networks could reflect the processing of conflict information in the selective attention task. The human brain tends to be a more regular and efficient neural architecture in the late stage of information processing. In addition, the processing of conflict information needs stronger information integration and transfer between cortical areas. Copyright © 2015 Elsevier B.V. All rights reserved.

High-dose corticosterone after fear conditioning selectively suppresses fear renewal by reducing anxiety-like response.

PubMed

Wang, Hongbo; Xing, Xiaoli; Liang, Jing; Bai, Yunjing; Lui, Zhengkui; Zheng, Xigeng

2014-09-01

Exposure therapy is widely used to treat anxiety disorders, including posttraumatic stress disorder (PTSD). However, preventing the return of fear is still a major challenge after this behavioral treatment. An increasing number of studies suggest that high-dose glucocorticoid treatment immediately after trauma can alleviate the symptoms of PTSD in humans. Unknown is whether high-dose glucocorticoid treatment following fear conditioning suppresses the return of fear. In the present study, a typical fear renewal paradigm (AAB) was used, in which the fear response to an auditory cue can be restored in a novel context (context B) when both training and extinction occur in the same context (context A). We trained rats for auditory fear conditioning and administered corticosterone (CORT; 5 and 25mg/kg, i.p.) or vehicle with different delays (1 and 24h). Forty-eight hours after drug injection, extinction was conducted with no drug in the training context, followed by a test of tone-induced freezing behavior in the same (AAA) or a shifted (AAB) context. Both immediate and delayed administration of high-dose CORT after fear conditioning reduced fear renewal. To examine the anxiolytic effect of CORT, independent rats were trained for cued or contextual fear conditioning, followed by an injection of CORT (5 and 25mg/kg, i.p.) or vehicle at a 1 or 24h delay. One week later, anxiety-like behavior was assessed in the elevated plus maze (EPM) before and after fear expression. We found that high-dose CORT decreased anxiety-like behavior without changing tone- or context-induced freezing. These findings indicate that a single high-dose CORT administration given after fear conditioning may selectively suppress fear renewal by reducing anxiety-like behavior and not by altering the consolidation, retrieval, or extinction of fear memory. Copyright © 2014 Elsevier Inc. All rights reserved.

Social selection and peer influence in an online social network

PubMed Central

Lewis, Kevin; Gonzalez, Marco; Kaufman, Jason

2012-01-01

Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends—except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes. PMID:22184242

Social selection and peer influence in an online social network.

PubMed

Lewis, Kevin; Gonzalez, Marco; Kaufman, Jason

2012-01-03

Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends-except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes.

Complex networks with large numbers of labelable attractors

NASA Astrophysics Data System (ADS)

Mi, Yuanyuan; Zhang, Lisheng; Huang, Xiaodong; Qian, Yu; Hu, Gang; Liao, Xuhong

2011-09-01

Information storage in many functional subsystems of the brain is regarded by theoretical neuroscientists to be related to attractors of neural networks. The number of attractors is large and each attractor can be temporarily represented or suppressed easily by corresponding external stimulus. In this letter, we discover that complex networks consisting of excitable nodes have similar fascinating properties of coexistence of large numbers of oscillatory attractors, most of which can be labeled with a few nodes. According to a simple labeling rule, different attractors can be identified and the number of labelable attractors can be predicted from the analysis of network topology. With the cues of the labeling association, these attractors can be conveniently retrieved or suppressed on purpose.

Interleukin-10-induced gene expression and suppressive function are selectively modulated by the PI3K-Akt-GSK3 pathway

PubMed Central

Antoniv, Taras T; Ivashkiv, Lionel B

2011-01-01

Interleukin-10 (IL-10) is an immunosuppressive cytokine that inhibits inflammatory gene expression. Phosphatidylinositol 3-kinase (PI3K) -mediated signalling regulates inflammatory responses and can induce IL-10 production, but a role for PI3K signalling in cellular responses to IL-10 is not known. In this study we investigated the involvement of the PI3K-Akt-GSK3 signalling pathway in IL-10-induced gene expression and IL-10-mediated suppression of Toll-like receptor-induced gene expression in primary human macrophages. A combination of loss and gain of function approaches using kinase inhibitors, expression of constitutively active Akt, and RNA interference in primary human macrophages showed that expression of a subset of IL-10-inducible genes was dependent on PI3K-Akt signalling. The effects of PI3K-Akt signalling on IL-10 responses were mediated at least in part by glycogen synthase kinase 3 (GSK3). In accordance with a functional role for PI3K pathways in contributing to the suppressive actions of IL-10, PI3K signalling augmented IL-10-mediated inhibition of lipopolysaccharide-induced IL-1, IL-8 and cyclo-oxygenase-2 expression. The PI3K signalling selectively modulated IL-10 responses, as it was not required for inhibition of tumour necrosis factor expression or for induction of certain IL-10-inducible genes such as SOCS3. These findings identify a new mechanism by which PI3K-mediated signalling can suppress inflammation by regulating IL-10-mediated gene induction and anti-inflammatory function. PMID:21255011

The Modification of siRNA with 3′ Cholesterol to Increase Nuclease Protection and Suppression of Native mRNA by Select siRNA Polyplexes

PubMed Central

Ambardekar, Vishakha V.; Han, Huai-Yun; Varney, Michelle L.; Vinogradov, Serguei V.; Singh, Rakesh K.; Vetro, Joseph A.

2010-01-01

Polymer-siRNA complexes (siRNA polyplexes) are being actively developed to improve the therapeutic application of siRNA. A major limitation for many siRNA polyplexes, however, is insufficient mRNA suppression. Given that modifying the sense strand of siRNA with 3′ cholesterol (chol-siRNA) increases the activity of free nuclease-resistant siRNA in vitro and in vivo, we hypothesized that complexation of chol-siRNA can increase mRNA suppression by siRNA polyplexes. In this study, the characteristics and siRNA activity of self assembled polyplexes formed with chol-siRNA or unmodified siRNA were compared using three types of conventional, positively charged polymers: (i) biodegradable, cross-linked nanogels (BDNG) (ii) graft copolymers (PEI-PEG), and (iii) linear block copolymers (PLL10-PEG, and PLL50-PEG). Chol-siRNA did not alter complex formation or the resistance of polyplexes to siRNA displacement by heparin but increased nuclease protection by BDNG, PLL10-PEG, and PLL50-PEG polyplexes over polyplexes with unmodified siRNA. Chol-CYPB siRNA increased suppression of native CYPB mRNA in mammary microvascular endothelial cells (MVEC) by BDNG polyplexes (35%) and PLL10-PEG polyplexes (69%) over comparable CYPB siRNA polyplexes but had no effect on PEI-PEG or PLL50-PEG polyplexes. Overall, these results indicate that complexation of chol-siRNA increases nuclease protection and mRNA suppression by select siRNA polyplexes. These results also suggest that polycationic block length is an important factor in increasing mRNA suppression by PLL-PEG chol-siRNA polyplexes in mammary MVEC. PMID:21047680

Functional imaging correlates of impaired distractor suppression following sleep deprivation.

PubMed

Kong, Danyang; Soon, Chun Siong; Chee, Michael W L

2012-05-15

Sleep deprivation (SD) has been shown to affect selective attention but it is not known how two of its component processes: target enhancement and distractor suppression, are affected. To investigate, young volunteers either attended to houses or were obliged to ignore them (when attending to faces) while viewing superimposed face-house pictures. MR signal enhancement and suppression in the parahippocampal place area (PPA) were determined relative to a passive viewing control condition. Sleep deprivation was associated with lower PPA activation across conditions. Critically SD specifically impaired distractor suppression in selective attention, leaving target enhancement relatively preserved. These findings parallel some observations in cognitive aging. Additionally, following SD, attended houses were not significantly better recognized than ignored houses in a post-experiment test of recognition memory contrasting with the finding of superior recognition of attended houses in the well-rested state. These results provide evidence for co-encoding of distracting information with targets into memory when one is sleep deprived. Copyright © 2012 Elsevier Inc. All rights reserved.

Dynamics of convulsive seizure termination and postictal generalized EEG suppression

PubMed Central

Bauer, Prisca R.; Thijs, Roland D.; Lamberts, Robert J.; Velis, Demetrios N.; Visser, Gerhard H.; Tolner, Else A.; Sander, Josemir W.; Lopes da Silva, Fernando H.; Kalitzin, Stiliyan N.

2017-01-01

Abstract It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15–61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal

Selective Reduction of AMPA Currents onto Hippocampal Interneurons Impairs Network Oscillatory Activity

PubMed Central

Le Magueresse, Corentin; Monyer, Hannah

2012-01-01

Reduction of excitatory currents onto GABAergic interneurons in the forebrain results in impaired spatial working memory and altered oscillatory network patterns in the hippocampus. Whether this phenotype is caused by an alteration in hippocampal interneurons is not known because most studies employed genetic manipulations affecting several brain regions. Here we performed viral injections in genetically modified mice to ablate the GluA4 subunit of the AMPA receptor in the hippocampus (GluA4HC−/− mice), thereby selectively reducing AMPA receptor-mediated currents onto a subgroup of hippocampal interneurons expressing GluA4. This regionally selective manipulation led to a strong spatial working memory deficit while leaving reference memory unaffected. Ripples (125–250 Hz) in the CA1 region of GluA4HC−/− mice had larger amplitude, slower frequency and reduced rate of occurrence. These changes were associated with an increased firing rate of pyramidal cells during ripples. The spatial selectivity of hippocampal pyramidal cells was comparable to that of controls in many respects when assessed during open field exploration and zigzag maze running. However, GluA4 ablation caused altered modulation of firing rate by theta oscillations in both interneurons and pyramidal cells. Moreover, the correlation between the theta firing phase of pyramidal cells and position was weaker in GluA4HC−/− mice. These results establish the involvement of AMPA receptor-mediated currents onto hippocampal interneurons for ripples and theta oscillations, and highlight potential cellular and network alterations that could account for the altered working memory performance. PMID:22675480

A dendrite-suppressing composite ion conductor from aramid nanofibres.

PubMed

Tung, Siu-On; Ho, Szushen; Yang, Ming; Zhang, Ruilin; Kotov, Nicholas A

2015-01-27

Dendrite growth threatens the safety of batteries by piercing the ion-transporting separators between the cathode and anode. Finding a dendrite-suppressing material that combines high modulus and high ionic conductance has long been considered a major technological and materials science challenge. Here we demonstrate that these properties can be attained in a composite made from Kevlar-derived aramid nanofibres assembled in a layer-by-layer manner with poly(ethylene oxide). Importantly, the porosity of the membranes is smaller than the growth area of the dendrites so that aramid nanofibres eliminate 'weak links' where the dendrites pierce the membranes. The aramid nanofibre network suppresses poly(ethylene oxide) crystallization detrimental for ion transport, giving a composite that exhibits high modulus, ionic conductivity, flexibility, ion flux rates and thermal stability. Successful suppression of hard copper dendrites by the composite ion conductor at extreme discharge conditions is demonstrated, thereby providing a new approach for the materials engineering of solid ion conductors.

A dendrite-suppressing composite ion conductor from aramid nanofibres

NASA Astrophysics Data System (ADS)

Tung, Siu-On; Ho, Szushen; Yang, Ming; Zhang, Ruilin; Kotov, Nicholas A.

2015-01-01

Dendrite growth threatens the safety of batteries by piercing the ion-transporting separators between the cathode and anode. Finding a dendrite-suppressing material that combines high modulus and high ionic conductance has long been considered a major technological and materials science challenge. Here we demonstrate that these properties can be attained in a composite made from Kevlar-derived aramid nanofibres assembled in a layer-by-layer manner with poly(ethylene oxide). Importantly, the porosity of the membranes is smaller than the growth area of the dendrites so that aramid nanofibres eliminate ‘weak links’ where the dendrites pierce the membranes. The aramid nanofibre network suppresses poly(ethylene oxide) crystallization detrimental for ion transport, giving a composite that exhibits high modulus, ionic conductivity, flexibility, ion flux rates and thermal stability. Successful suppression of hard copper dendrites by the composite ion conductor at extreme discharge conditions is demonstrated, thereby providing a new approach for the materials engineering of solid ion conductors.

Suppressing epidemic spreading by risk-averse migration in dynamical networks

NASA Astrophysics Data System (ADS)

Yang, Han-Xin; Tang, Ming; Wang, Zhen

2018-01-01

In this paper, we study the interplay between individual behaviors and epidemic spreading in a dynamical network. We distribute agents on a square-shaped region with periodic boundary conditions. Every agent is regarded as a node of the network and a wireless link is established between two agents if their geographical distance is less than a certain radius. At each time, every agent assesses the epidemic situation and make decisions on whether it should stay in or leave its current place. An agent will leave its current place with a speed if the number of infected neighbors reaches or exceeds a critical value E. Owing to the movement of agents, the network's structure is dynamical. Interestingly, we find that there exists an optimal value of E leading to the maximum epidemic threshold. This means that epidemic spreading can be effectively controlled by risk-averse migration. Besides, we find that the epidemic threshold increases as the recovering rate increases, decreases as the contact radius increases, and is maximized by an optimal moving speed. Our findings offer a deeper understanding of epidemic spreading in dynamical networks.

Selective attention modulates high-frequency activity in the face-processing network.

PubMed

Müsch, Kathrin; Hamamé, Carlos M; Perrone-Bertolotti, Marcela; Minotti, Lorella; Kahane, Philippe; Engel, Andreas K; Lachaux, Jean-Philippe; Schneider, Till R

2014-11-01

Face processing depends on the orchestrated activity of a large-scale neuronal network. Its activity can be modulated by attention as a function of task demands. However, it remains largely unknown whether voluntary, endogenous attention and reflexive, exogenous attention to facial expressions equally affect all regions of the face-processing network, and whether such effects primarily modify the strength of the neuronal response, the latency, the duration, or the spectral characteristics. We exploited the good temporal and spatial resolution of intracranial electroencephalography (iEEG) and recorded from depth electrodes to uncover the fast dynamics of emotional face processing. We investigated frequency-specific responses and event-related potentials (ERP) in the ventral occipito-temporal cortex (VOTC), ventral temporal cortex (VTC), anterior insula, orbitofrontal cortex (OFC), and amygdala when facial expressions were task-relevant or task-irrelevant. All investigated regions of interest (ROI) were clearly modulated by task demands and exhibited stronger changes in stimulus-induced gamma band activity (50-150 Hz) when facial expressions were task-relevant. Observed latencies demonstrate that the activation is temporally coordinated across the network, rather than serially proceeding along a processing hierarchy. Early and sustained responses to task-relevant faces in VOTC and VTC corroborate their role for the core system of face processing, but they also occurred in the anterior insula. Strong attentional modulation in the OFC and amygdala (300 msec) suggests that the extended system of the face-processing network is only recruited if the task demands active face processing. Contrary to our expectation, we rarely observed differences between fearful and neutral faces. Our results demonstrate that activity in the face-processing network is susceptible to the deployment of selective attention. Moreover, we show that endogenous attention operates along the whole

Older Adults Can Suppress Unwanted Memories When Given an Appropriate Strategy

PubMed Central

2015-01-01

Memory suppression refers to the ability to exclude distracting memories from conscious awareness, and this ability can be assessed with the think/no-think paradigm. Recent research with older adults has provided evidence suggesting both intact and deficient memory suppression. The present studies seek to understand the conditions contributing to older adults’ ability to suppress memories voluntarily. We report 2 experiments indicating that the specificity of the think/no-think task instructions contributes to older adults’ suppression success: When older adults receive open-ended instructions that require them to develop a retrieval suppression strategy on their own, they show diminished memory suppression compared with younger adults. Conversely, when older adults receive focused instructions directing them to a strategy thought to better isolate inhibitory control, they show suppression-induced forgetting similar to that exhibited by younger adults. Younger adults demonstrate memory suppression regardless of the specificity of the instructions given, suggesting that the ability to select a successful suppression strategy spontaneously may be compromised in older adults. If so, this deficit may be associated with diminished control over unwanted memories in naturalistic settings if impeded strategy development reduces the successful deployment of inhibitory control. PMID:25602491

Novel, selective vitamin D analog suppresses parathyroid hormone in uremic animals and postmenopausal women.

PubMed

Zella, Julia B; Plum, Lori A; Plowchalk, David R; Potochoiba, Michael; Clagett-Dame, Margaret; DeLuca, Hector F

2014-01-01

The use of 1α-hydroxylated vitamin D therapy to control secondary hyperparathyroidism in renal failure patients has been a success story, culminating with the demonstration of increased life expectancy in patients treated with these compounds. However, hypercalcemic episodes have been a recurrent problem with these therapies and have resulted in the added use of calcium mimetics. Clearly there is good reason to search for improved vitamin D therapy. In our inventory of vitamin D compounds, 2-methylene-19-nor-(20S)-1α,25-dihydroxyvitamin D3 (2MD) surfaced as a potential candidate. This was based on its preferential localization in the parathyroid gland and a clear suppression of serum parathyroid hormone (PTH) levels without a change in serum calcium in a clinical trial in postmenopausal women. 2MD has now been tested in the rat 5/6-nephrectomy model of renal failure, and in postmenopausal women to determine if it can suppress serum PTH at doses that do not elevate serum calcium and serum phosphorus concentrations. Daily oral treatment of uremic rats on 2.5 ng/bw/day of 2MD dramatically suppressed PTH without a change in serum calcium or serum phosphorus. Further, PTH was suppressed in postmenopausal women after only 3 daily oral doses of 2MD that continued for 4 weeks with no change in serum calcium or serum phosphorus. These results coupled with a pharmacokinetic half-life of ~24 h suggest that 2MD given either daily or at the time of dialysis may be a superior therapy for secondary hyperparathyroidism in chronic renal failure patients.

Feature-selective attention in healthy old age: a selective decline in selective attention?

PubMed

Quigley, Cliodhna; Müller, Matthias M

2014-02-12

Deficient selection against irrelevant information has been proposed to underlie age-related cognitive decline. We recently reported evidence for maintained early sensory selection when older and younger adults used spatial selective attention to perform a challenging task. Here we explored age-related differences when spatial selection is not possible and feature-selective attention must be deployed. We additionally compared the integrity of feedforward processing by exploiting the well established phenomenon of suppression of visual cortical responses attributable to interstimulus competition. Electroencephalogram was measured while older and younger human adults responded to brief occurrences of coherent motion in an attended stimulus composed of randomly moving, orientation-defined, flickering bars. Attention was directed to horizontal or vertical bars by a pretrial cue, after which two orthogonally oriented, overlapping stimuli or a single stimulus were presented. Horizontal and vertical bars flickered at different frequencies and thereby elicited separable steady-state visual-evoked potentials, which were used to examine the effect of feature-based selection and the competitive influence of a second stimulus on ongoing visual processing. Age differences were found in feature-selective attentional modulation of visual responses: older adults did not show consistent modulation of magnitude or phase. In contrast, the suppressive effect of a second stimulus was robust and comparable in magnitude across age groups, suggesting that bottom-up processing of the current stimuli is essentially unchanged in healthy old age. Thus, it seems that visual processing per se is unchanged, but top-down attentional control is compromised in older adults when space cannot be used to guide selection.

Selective suppression of cytokine secretion in whole blood cell cultures of patients with colorectal cancer.

PubMed Central

Lahm, H.; Schindel, M.; Frikart, L.; Cerottini, J. P.; Yilmaz, A.; Givel, J. C.; Fischer, J. R.

1998-01-01

We have investigated the secretion of interferon alpha (IFN-alpha), IFN-gamma, interleukin-1alpha (IL-1alpha), IL-1beta, IL-2 and tumour necrosis factor alpha (TNF-alpha) in whole blood cell cultures (WBCCs) of colorectal cancer patients upon mitogen stimulation. Whereas the values for IL-1beta and TNF-alpha remained virtually unchanged in comparison with healthy control subjects, WBCCs of colorectal cancer patients secreted significantly lower amounts of IFN-alpha (P < 0.005), IFN-gamma (P < 0.0001), IL-1alpha (P < 0.0001) and IL-2 (P < 0.05). This reduction correlated with the progression of the disease. The total leucocyte and monocyte population were almost identical in both groups. In contrast, a dramatic depletion of lymphocytes was observed in colorectal cancer patients, which affected both lymphocyte counts (P < 0.0005) and their distribution (P < 0.0001). Our results suggest a selective suppression of cytokines in colorectal cancer patients that is related to tumour burden. Several mechanisms might account for this phenomenon, one of which might be lymphocyte depletion. PMID:9792144

Nimesulide, a cyclooxygenase-2 selective inhibitor, suppresses obesity-related non-alcoholic fatty liver disease and hepatic insulin resistance through the regulation of peroxisome proliferator-activated receptor γ

PubMed Central

Tsujimoto, Shunsuke; Kishina, Manabu; Koda, Masahiko; Yamamoto, Yasutaka; Tanaka, Kohei; Harada, Yusuke; Yoshida, Akio; Hisatome, Ichiro

2016-01-01

Cyclooxygenase (COX)-2 selective inhibitors suppress non-alcoholic fatty liver disease (NAFLD); however, the precise mechanism of action remains unknown. The aim of this study was to examine how the COX-2 selective inhibitor nimesulide suppresses NAFLD in a murine model of high-fat diet (HFD)-induced obesity. Mice were fed either a normal chow diet (NC), an HFD, or HFD plus nimesulide (HFD-nime) for 12 weeks. Body weight, hepatic COX-2 mRNA expression and triglyceride accumulation were significantly increased in the HFD group. Triglyceride accumulation was suppressed in the HFD-nime group. The mRNA expression of hepatic peroxisome proliferator-activated receptor γ (PPARγ) and the natural PPARγ agonist 15-deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2) were significantly increased in the HFD group and significantly suppressed in the HFD-nime group. Glucose metabolism was impaired in the HFD group compared with the NC group, and it was significantly improved in the HFD-nime group. In addition, the plasma insulin levels in the HFD group were increased compared with those in the NC group, and were decreased in the HFD-nime group. These results indicate that HFD-induced NAFLD is mediated by the increased hepatic expression of COX-2. We suggest that the production of 15d-PGJ2, which is mediated by COX-2, induces NAFLD and hepatic insulin resistance by activating PPARγ. Furthermore, the mRNA expression of tissue inhibitor of metalloproteinases-1 (TIMP-1), procollagen-1 and monocyte chemoattractant protein-1 (MCP-1), as well as the number of F4/80-positive hepatic (Kupffer) cells, were significantly increased in the HFD group compared with the NC group, and they were reduced by nimesulide. In conclusion, COX-2 may emerge as a molecular target for preventing the development of NAFLD and insulin resistance in diet-related obesity. PMID:27431935

On Proper Selection of Multihop Relays for Future Enhancement of AeroMACS Networks

NASA Technical Reports Server (NTRS)

Kamali, Behnam; Kerczewski, Robert J.; Apaza, Rafael D.

2015-01-01

As the Aeronautical Mobile Airport Communications System (AeroMACS) has evolved from a technology concept to a deployed communications network over major US airports, it is now time to contemplate whether the existing capacity of AeroMACS is sufficient to meet the demands set forth by all fixed and mobile applications over the airport surface given the AeroMACS constraints regarding bandwidth and transmit power. The underlying idea in this article is to present IEEE 802.16j-based WiMAX as a technology that can address future capacity enhancements and therefore is most feasible for AeroMACS applications. The principal argument in favor IEEE 802.16j technology is the flexible and cost effective extension of radio coverage that is afforded by relay fortified networks, with virtually no increase in the power requirements and virtually no rise in interference levels to co-allocated applications. The IEEE 802.16j-based multihop relay systems are briefly described. The focus is on key features of this technology, frame structure, and its architecture. Next, AeroMACS is described as a WiMAX-based wireless network. The two major relay modes supported by IEEE 802.16j amendment, i.e., transparent and non-transparent are described. The benefits of employing multihop relays are listed. Some key challenges related to incorporating relays into AeroMACS networks are discussed. The selection of relay type in a broadband wireless network affects a number of network parameters such as latency, signal overhead, PHY (Scalable Physical Layer) and MAC (Media Access Layer) layer protocols, consequently it can alter key network quantities of throughput and QoS (Quality of Service).

Selective impairment of hippocampus and posterior hub areas in Alzheimer's disease: an MEG-based multiplex network study.

PubMed

Yu, Meichen; Engels, Marjolein M A; Hillebrand, Arjan; van Straaten, Elisabeth C W; Gouw, Alida A; Teunissen, Charlotte; van der Flier, Wiesje M; Scheltens, Philip; Stam, Cornelis J

2017-05-01

Although frequency-specific network analyses have shown that functional brain networks are altered in patients with Alzheimer's disease, the relationships between these frequency-specific network alterations remain largely unknown. Multiplex network analysis is a novel network approach to study complex systems consisting of subsystems with different types of connectivity patterns. In this study, we used magnetoencephalography to integrate five frequency-band specific brain networks in a multiplex framework. Previous structural and functional brain network studies have consistently shown that hub brain areas are selectively disrupted in Alzheimer's disease. Accordingly, we hypothesized that hub regions in the multiplex brain networks are selectively targeted in patients with Alzheimer's disease in comparison to healthy control subjects. Eyes-closed resting-state magnetoencephalography recordings from 27 patients with Alzheimer's disease (60.6 ± 5.4 years, 12 females) and 26 controls (61.8 ± 5.5 years, 14 females) were projected onto atlas-based regions of interest using beamforming. Subsequently, source-space time series for both 78 cortical and 12 subcortical regions were reconstructed in five frequency bands (delta, theta, alpha 1, alpha 2 and beta band). Multiplex brain networks were constructed by integrating frequency-specific magnetoencephalography networks. Functional connections between all pairs of regions of interests were quantified using a phase-based coupling metric, the phase lag index. Several multiplex hub and heterogeneity metrics were computed to capture both overall importance of each brain area and heterogeneity of the connectivity patterns across frequency-specific layers. Different nodal centrality metrics showed consistently that several hub regions, particularly left hippocampus, posterior parts of the default mode network and occipital regions, were vulnerable in patients with Alzheimer's disease compared to control subjects. Of note

Prediction of the Seizure Suppression Effect by Electrical Stimulation via a Computational Modeling Approach.

PubMed

Ahn, Sora; Jo, Sumin; Jun, Sang Beom; Lee, Hyang Woon; Lee, Seungjun

2017-01-01

In this paper, we identified factors that can affect seizure suppression via electrical stimulation by an integrative study based on experimental and computational approach. Preferentially, we analyzed the characteristics of seizure-like events (SLEs) using our previous in vitro experimental data. The results were analyzed in two groups classified according to the size of the effective region, in which the SLE was able to be completely suppressed by local stimulation. However, no significant differences were found between these two groups in terms of signal features or propagation characteristics (i.e., propagation delays, frequency spectrum, and phase synchrony). Thus, we further investigated important factors using a computational model that was capable of evaluating specific influences on effective region size. In the proposed model, signal transmission between neurons was based on two different mechanisms: synaptic transmission and the electrical field effect. We were able to induce SLEs having similar characteristics with differentially weighted adjustments for the two transmission methods in various noise environments. Although the SLEs had similar characteristics, their suppression effects differed. First of all, the suppression effect occurred only locally where directly received the stimulation effect in the high noise environment, but it occurred in the entire network in the low noise environment. Interestingly, in the same noise environment, the suppression effect was different depending on SLE propagation mechanism; only a local suppression effect was observed when the influence of the electrical field transmission was very weak, whereas a global effect was observed with a stronger electrical field effect. These results indicate that neuronal activities synchronized by a strong electrical field effect respond more sensitively to partial changes in the entire network. In addition, the proposed model was able to predict that stimulation of a seizure focus

High-precision buffer circuit for suppression of regenerative oscillation

NASA Technical Reports Server (NTRS)

Tripp, John S.; Hare, David A.; Tcheng, Ping

1995-01-01

Precision analog signal conditioning electronics have been developed for wind tunnel model attitude inertial sensors. This application requires low-noise, stable, microvolt-level DC performance and a high-precision buffered output. Capacitive loading of the operational amplifier output stages due to the wind tunnel analog signal distribution facilities caused regenerative oscillation and consequent rectification bias errors. Oscillation suppression techniques commonly used in audio applications were inadequate to maintain the performance requirements for the measurement of attitude for wind tunnel models. Feedback control theory is applied to develop a suppression technique based on a known compensation (snubber) circuit, which provides superior oscillation suppression with high output isolation and preserves the low-noise low-offset performance of the signal conditioning electronics. A practical design technique is developed to select the parameters for the compensation circuit to suppress regenerative oscillation occurring when typical shielded cable loads are driven.

The Human Burst Suppression Electroencephalogram of Deep Hypothermia

PubMed Central

Kumaraswamy, Vishakhadatta M.; Akeju, Seun Oluwaseun; Pierce, Eric; Cash, Sydney S.; Kilbride, Ronan; Brown, Emery N.; Purdon, Patrick L.

2015-01-01

Objective Deep hypothermia induces ‘burst suppression’ (BS), an electroencephalogram pattern with low-voltage ‘suppressions’ alternating with high-voltage ‘bursts’. Current understanding of BS comes mainly from anesthesia studies, while hypothermia-induced BS has received little study. We set out to investigate the electroencephalogram changes induced by cooling the human brain through increasing depths of BS through isoelectricity. Methods We recorded scalp electroencephalograms from eleven patients undergoing deep hypothermia during cardiac surgery with complete circulatory arrest, and analyzed these using methods of spectral analysis. Results Within patients, the depth of BS systematically depends on the depth of hypothermia, though responses vary between patients except at temperature extremes. With decreasing temperature, burst lengths increase, and burst amplitudes and lengths decrease, while the spectral content of bursts remains constant. Conclusions These findings support an existing theoretical model in which the common mechanism of burst suppression across diverse etiologies is the cyclical diffuse depletion of metabolic resources, and suggest the new hypothesis of local micro-network dropout to explain decreasing burst amplitudes at lower temperatures. Significance These results pave the way for accurate noninvasive tracking of brain metabolic state during surgical procedures under deep hypothermia, and suggest new testable predictions about the network mechanisms underlying burst suppression. PMID:25649968

The Most Remote Point Method for the Site Selection of the Future VGOS Network

NASA Astrophysics Data System (ADS)

Hase, Hayo; Pedreros, Felipe

2014-12-01

The VLBI Global Observing System (VGOS) will be part of the Global Geodetic Observing System (GGOS) and will consist of globally well distributed geodetic observatories. The most remote point (MRP) method is used to identify gaps in the network geometry. In each iteration step the identified most remote points are assumed to become new observatory sites improving the homogeneity of the global network. New locations for VGOS observatories have been found in La Plata, Tahiti, O'Higgins, Galapagos, Colombo, and Syowa. This contribution is an excerpt of a work published in Journal of Geodesy (DOI: 10.1007/s00190-014-0731-y) covering the site selection for the GGOS.%

Brain mechanisms underlying the effects of aging on different aspects of selective attention.

PubMed

Geerligs, Linda; Saliasi, Emi; Maurits, Natasha M; Renken, Remco J; Lorist, Monicque M

2014-05-01

The ability to suppress irrelevant information declines with age, while the ability to enhance relevant information remains largely intact. We examined mechanisms behind this dissociation in an fMRI study, using a selective attention task in which relevant and irrelevant information appeared simultaneously. Slowing of response times due to distraction by irrelevant targets was larger in older than younger participants. Increased distraction was related to larger increases in activity and connectivity in areas of the dorsal attention network, indicating a more pronounced (re-)orientation of attention. The decreases in accuracy in target compared to nontarget trials were smaller in older compared to younger participants. In older adults we found increased recruitment of areas in the fronto-parietal control network (FPCN) during target detection. Moreover, older adults showed increased connectivity between the FPCN, supporting cognitive control, and somatomotor areas implicated in response selection and execution. This connectivity increase was related to improved target detection, suggesting that older adults engage additional cognitive control, which might enable the observed intact performance in detecting and responding to target stimuli. Copyright © 2014 Elsevier Inc. All rights reserved.

On the globality of motor suppression: unexpected events and their influence on behavior and cognition

PubMed Central

Wessel, Jan R.; Aron, Adam R.

2016-01-01

SUMMARY Unexpected events are part of everyday experience. They come in several varieties – action errors, unexpected action outcomes, and unexpected perceptual events – and they lead to motor slowing and cognitive distraction. While different varieties of unexpected events have been studied largely independently, and many different mechanisms are thought to explain their effects on action and cognition, we suggest a unifying theory. We propose that unexpected events recruit a fronto-basal-ganglia network for stopping. This network includes specific prefrontal cortical nodes and is posited to project to the subthalamic nucleus, with a putative global suppressive effect on basal-ganglia output. We argue that unexpected events interrupt action and impact cognition, partly at least, by recruiting this global suppressive network. This provides a common mechanistic basis for different types of unexpected events, links the literatures on motor inhibition, performance-monitoring, attention, and working memory, and is relevant for understanding clinical symptoms of distractibility and mental inflexibility. PMID:28103476

On the Globality of Motor Suppression: Unexpected Events and Their Influence on Behavior and Cognition.

PubMed

Wessel, Jan R; Aron, Adam R

2017-01-18

Unexpected events are part of everyday experience. They come in several varieties-action errors, unexpected action outcomes, and unexpected perceptual events-and they lead to motor slowing and cognitive distraction. While different varieties of unexpected events have been studied largely independently, and many different mechanisms are thought to explain their effects on action and cognition, we suggest a unifying theory. We propose that unexpected events recruit a fronto-basal-ganglia network for stopping. This network includes specific prefrontal cortical nodes and is posited to project to the subthalamic nucleus, with a putative global suppressive effect on basal-ganglia output. We argue that unexpected events interrupt action and impact cognition, partly at least, by recruiting this global suppressive network. This provides a common mechanistic basis for different types of unexpected events; links the literatures on motor inhibition, performance monitoring, attention, and working memory; and is relevant for understanding clinical symptoms of distractibility and mental inflexibility. Copyright © 2017 Elsevier Inc. All rights reserved.

Peer Network Drinking Predicts Increased Alcohol Use From Adolescence to Early Adulthood After Controlling for Genetic and Shared Environmental Selection

PubMed Central

Cruz, Jennifer E.; Emery, Robert E.; Turkheimer, Eric

2013-01-01

Research consistently links adolescents' and young adults' drinking with their peers' alcohol intake. In interpreting this correlation, 2 essential questions are often overlooked. First, which peers are more important, best friends or broader social networks? Second, do peers cause increased drinking, or do young people select friends whose drinking habits match their own? The present study combines social network analyses with family (twin and sibling) designs to answer these questions via data from the National Longitudinal Study of Adolescent Health. Analysis of peer nomination data from 134 schools (n = 82,629) and 1,846 twin and sibling pairs shows that peer network substance use predicts changes in drinking from adolescence into young adult life even after controlling for genetic and shared environmental selection, as well as best friend substance use. This effect was particularly strong for high-intensity friendships. Although the peer-adolescent drinking correlation is partially explained by selection, the present finding offers powerful evidence that peers also cause increased drinking. PMID:22390657

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

Enabling Interoperable and Selective Data Sharing among Social Networking Sites

NASA Astrophysics Data System (ADS)

Shin, Dongwan; Lopes, Rodrigo

With the widespread use of social networking (SN) sites and even introduction of a social component in non-social oriented services, there is a growing concern over user privacy in general, how to handle and share user profiles across SN sites in particular. Although there have been several proprietary or open source-based approaches to unifying the creation of third party applications, the availability and retrieval of user profile information are still limited to the site where the third party application is run, mostly devoid of the support for data interoperability. In this paper we propose an approach to enabling interopearable and selective data sharing among SN sites. To support selective data sharing, we discuss an authenticated dictionary (ADT)-based credential which enables a user to share only a subset of her information certified by external SN sites with applications running on an SN site. For interoperable data sharing, we propose an extension to the OpenSocial API so that it can provide an open source-based framework for allowing the ADT-based credential to be used seamlessly among different SN sites.

Measuring colour rivalry suppression in amblyopia.

PubMed

Hofeldt, T S; Hofeldt, A J

1999-11-01

To determine if the colour rivalry suppression is an index of the visual impairment in amblyopia and if the stereopsis and fusion evaluator (SAFE) instrument is a reliable indicator of the difference in visual input from the two eyes. To test the accuracy of the SAFE instrument for measuring the visual input from the two eyes, colour rivalry suppression was measured in six normal subjects. A test neutral density filter (NDF) was placed before one eye to induce a temporary relative afferent defect and the subject selected the NDF before the fellow eye to neutralise the test NDF. In a non-paediatric private practice, 24 consecutive patients diagnosed with unilateral amblyopia were tested with the SAFE. Of the 24 amblyopes, 14 qualified for the study because they were able to fuse images and had no comorbid disease. The relation between depth of colour rivalry suppression, stereoacuity, and interocular difference in logMAR acuity was analysed. In normal subjects, the SAFE instrument reversed temporary defects of 0.3 to 1. 8 log units to within 0.6 log units. In amblyopes, the NDF to reverse colour rivalry suppression was positively related to interocular difference in logMAR acuity (beta=1.21, p<0.0001), and negatively related to stereoacuity (beta=-0.16, p=0.019). The interocular difference in logMAR acuity was negatively related to stereoacuity (beta=-0.13, p=0.009). Colour rivalry suppression as measured with the SAFE was found to agree closely with the degree of visual acuity impairment in non-paediatric patients with amblyopia.

Predicting selective drug targets in cancer through metabolic networks

PubMed Central

Folger, Ori; Jerby, Livnat; Frezza, Christian; Gottlieb, Eyal; Ruppin, Eytan; Shlomi, Tomer

2011-01-01

The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled. PMID:21694718

Space-time adaptive decision feedback neural receivers with data selection for high-data-rate users in DS-CDMA systems.

PubMed

de Lamare, Rodrigo C; Sampaio-Neto, Raimundo

2008-11-01

A space-time adaptive decision feedback (DF) receiver using recurrent neural networks (RNNs) is proposed for joint equalization and interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems equipped with antenna arrays. The proposed receiver structure employs dynamically driven RNNs in the feedforward section for equalization and multiaccess interference (MAI) suppression and a finite impulse response (FIR) linear filter in the feedback section for performing interference cancellation. A data selective gradient algorithm, based upon the set-membership (SM) design framework, is proposed for the estimation of the coefficients of RNN structures and is applied to the estimation of the parameters of the proposed neural receiver structure. Simulation results show that the proposed techniques achieve significant performance gains over existing schemes.

Next generation fire suppressants

NASA Technical Reports Server (NTRS)

Brown, Jerry A.

1995-01-01

Spectrex, Inc., located in Cedar Grove, NJ is a manufacturer of fire detection and suppression equipment. Spectrex is one of the original pioneers in high speed fire detection and suppression systems for combat vehicles. Spectrex has installed fire suppressions systems in thousands of combat vehicles and ships throughout the world. Additionally, they manufacture flame explosion detectors, ship damage control systems, and optical gas and vapor detectors. The culmination of several years of research and development has recently produced an innovative electro-optical continuous monitoring systems called SharpEye 20/20I IR(sup 3) and SAFEYE that provide fast and reliable gas, vapor, aerosol, flame, and explosion detection. SharpEye 20/20I IR(sup 3) is a self-contained triple spectrum flame detector which scans for oscillating IR radiation (1 to 10 Hz) in the spectral bands ranging from 4.0 to 5.0 microns and uses programmed algorithms to check the ratio and correlation of data received by the three sensors to make the system highly immune to false alarms. It is extremely sensitive as it can detect a 1 x 1 square foot gasoline pan fire at 200 feet in less than 3 seconds. The sensitivity is user programmable, offering 4 ranges of detection. SAFEYE is comprised of a selected number of multispectral ban microprocessors controlled detectors which are in communication with one or more radiation sources that is projected along a 600 feet optical path. The signals from the selected narrow bands are processed and analyzed by highly sophisticated algorithms. It is ideal for high risk, remote, large areas such as petroleum and chemical manufacturing sites, waste dumps, aircraft cargo bays, and ship compartments. The SAFEYE will perform direct readings of the presence or rate of rise of concentrations of gases, vapors, or aerosols at the range of parts per million and provide alarms at various set points at different levels of concentrations.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

PubMed

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

Causal Networks with Selectively Influenced Components

DTIC Science & Technology

2012-02-29

influences a different vertex. If so, the form of a processing tree accounting for the data can determined. Prior to the work on the grant, processing...their order. Processing trees were found to account well for data in the literature on immediate ordered recall and on effects of sleep and...ordered in the network) or concurrent (unordered). Ordinarily for a given data set, if one directed acyclic network can account for the data

Dim Networks: The Utility of Social Network Analysis for Illuminating Partner Security Force Networks

DTIC Science & Technology

2015-12-01

use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations and selectively target key elements...data to improve SC. 14. SUBJECT TERMS social network analysis, dark networks, light networks, dim networks, security cooperation, Southeast Asia...task may already exist. Recently, the use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations

MRI correlates of interaction between gender and expressive suppression among the Chinese population.

PubMed

Wang, Kangcheng; Huang, Hui; Chen, Li; Hou, Xin; Zhang, Yong; Yang, Junyi; Hao, Xin; Qiu, Jiang

2017-04-07

Expressive suppression is a kind of emotion regulation strategies by suppressing behaviors related to emotional responding. Despite the amount of behavioral research on expressive suppression, the structural and functional mechanisms underlying the interaction between gender and expressive suppression in Chinese healthy subjects have remained unknown. In the current study, we assessed the levels of expressive suppression and acquired the structural and functional imaging data from 273 Chinese individuals. A nearly automatic cortical processing technique was used to calculate cortical thickness for each subject. The results from cortical thickness analyses revealed a significant interaction between gender and expressive suppression in the superior frontal gyrus. Then, we conducted the whole-brain functional connectivity analysis with the seed of the superior frontal gyrus to explore the functionally related regions of brain. Subsequent analysis of the interaction between gender and expressive suppression indicated a significant functional connectivity between the superior frontal gyrus and default mode network (DMN) core regions, including the medial prefrontal cortex, precuneus and parahippocampal gyrus. Our results provided the robust empirical evidence illustrating the role of the superior frontal gyrus and DMN in gender difference of expressive suppression among the Chinese population. These findings might have implications for understanding gender difference in emotion processing and regulation. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Pyridinedicarboxylates, the first mechanism-derived inhibitors for prolyl 4-hydroxylase, selectively suppress cellular hydroxyprolyl biosynthesis. Decrease in interstitial collagen and Clq secretion in cell culture.

PubMed Central

Tschank, G; Raghunath, M; Günzler, V; Hanauske-Abel, H M

1987-01-01

Two pyridinedicarboxylates, predicted [Hanauske-Abel (1983) M.D.-Ph.D. Thesis, Philipps Universität Marburg] and later found to be potent reversible inhibitors of purified prolyl 4-hydroxylase [Majaama, Hanauske-Abel, Günzler & Kivirikko (1984) Eur. J. Biochem. 138, 239-245] were investigated with respect to their effect on hydroxyprolyl biosynthesis in the fibroblast/collagen and the macrophage/Clq systems, and the effect was compared with that of the iron chelator 2,2'-dipyridyl, the compound usually employed to inhibit cellular hydroxyprolyl formation. Only the enzyme-mechanism-derived pyridinedicarboxylates were highly selective inhibitors, and only they lacked overt cytotoxicity. Morphologically, their effect was restricted to the site of cellular hydroxyprolyl biosynthesis, i.e. the cisternae of the rough-surfaced endoplasmic reticulum. They were equally effective in the different cell types studied, and human and guinea-pig fibroblasts showed the same sensitivity. The minimal lipophilicity of the pyridinedicarboxylates necessitated high concentrations to achieve suppression of cellular hydroxyprolyl formation, but lipophilic bio-activatable pro-inhibitors may overcome this disadvantage. For the first time, experimental evidence is presented suggesting that, in cell culture, the biosynthesis of interstitial collagens and Clq can be suppressed selectively, identifying the pyridinedicarboxylates as promising pilot compounds for experiments in vivo. Images Fig. 3. Fig. 4. PMID:2829835

A novel inhibitor of STAT3 homodimerization selectively suppresses STAT3 activity and malignant transformation.

PubMed

Zhang, Xiaolei; Sun, Ying; Pireddu, Roberta; Yang, Hua; Urlam, Murali K; Lawrence, Harshani R; Guida, Wayne C; Lawrence, Nicholas J; Sebti, Saïd M

2013-03-15

STAT3-STAT3 dimerization, which involves reciprocal binding of the STAT3-SH2 domain to phosphorylated tyrosine-705 (Y-705), is required for STAT3 nuclear translocation, DNA binding, and transcriptional regulation of downstream target genes. Here, we describe a small molecule S3I-1757 capable of disrupting STAT3-STAT3 dimerization, activation, and malignant transforming activity. Fluorescence polarization assay and molecular modeling suggest that S3I-1757 interacts with the phospho-Y-705-binding site in the SH2 domain and displaces fluorescein-labeled GpYLPQTV phosphotyrosine peptide from binding to STAT3. We generated hemagglutinin (HA)-tagged STAT3 and FLAG-tagged STAT3 and showed using coimmunoprecipitation and colocalization studies that S3I-1757 inhibits STAT3 dimerization and STAT3-EGF receptor (EGFR) binding in intact cells. Treatment of human cancer cells with S3I-1757 (but not a closely related analog, S3I-1756, which does not inhibit STAT3 dimerization), inhibits selectively the phosphorylation of STAT3 over AKT1 and ERK1/2 (MAPK3/1), nuclear accumulation of P-Y705-STAT3, STAT3-DNA binding, and transcriptional activation and suppresses the expression levels of STAT3 target genes, such as Bcl-xL (BCL2L1), survivin (BIRC5), cyclin D1 (CCND1), and matrix metalloproteinase (MMP)-9. Furthermore, S3I-1757, but not S3I-1756, inhibits anchorage-dependent and -independent growth, migration, and invasion of human cancer cells, which depend on STAT3. Finally, STAT3-C, a genetically engineered mutant of STAT3 that forms a constitutively dimerized STAT3, rescues cells from the effects of S3I-1757 inhibition. Thus, we have developed S3I-1757 as a STAT3-STAT3 dimerization inhibitor capable of blocking hyperactivated STAT3 and suppressing malignant transformation in human cancer cells that depend on STAT3.

A novel inhibitor of STAT3 homodimerization selectively suppresses STAT3 activity and malignant transformation

PubMed Central

Zhang, Xiaolei; Sun, Ying; Pireddu, Roberta; Yang, Hua; Urlam, Murali K.; Lawrence, Harshani R.; Guida, Wayne C.; Lawrence, Nicholas J.; Sebti, Saïd M.

2014-01-01

STAT3-STAT3 dimerization, which involves reciprocal binding of the STAT3-SH2 domain to phosphorylated tyrosine-705 (Y-705), is required for STAT3 nuclear translocation, DNA binding and transcriptional regulation of downstream target genes. Here we describe a small molecule S3I-1757 capable of disrupting STAT3-STAT3 dimerization, activation and malignant transforming activity. Fluorescence polarization assays and molecular modeling suggest that S3I-1757 interacts with the Y-705 binding site in the SH2 domain and displaces fluorescein-labelled GpYLPQTV phosphotyrosine peptide from binding to STAT3. We generated HA-tagged STAT3 and FLAG-tagged STAT3 and showed using co-immunoprecipitation and co-localization studies that S3I-1757 inhibits STAT3 dimerization and STAT3-EGF receptor binding in intact cells. Treatment of human cancer cells with S3I-1757 (but not a closely related analogue, S3I-1756, that does not inhibit STAT3 dimerization), inhibits selectively the phosphorylation of STAT3 over AKT1 and ERK1/2 (MAPK3/1), nuclear accumulation of P-Y705-STAT3, STAT3-DNA binding and transcriptional activation and suppresses the expression levels of STAT3 target genes such as Bcl-xL (BCL2L1), survivin (BIRC5), cyclin D1 (CCND1) and MMP9. Furthermore, S3I-1757 but not S3I-1756 inhibits anchorage-dependent and -independent growth, migration and invasion of human cancer cells which depend on STAT3. Finally, STAT3-C, a genetically engineered mutant of STAT3 that forms a constitutively dimerized STAT3, rescues cells from the effects of S3I-1757 inhibition. Thus, we have developed S3I-1757 as a STAT3-STAT3 dimerization inhibitor capable of blocking hyper activated STAT3 and suppressing malignant transformation in human cancer cells that depend on STAT3. PMID:23322008

Feature selection in feature network models: finding predictive subsets of features with the Positive Lasso.

PubMed

Frank, Laurence E; Heiser, Willem J

2008-05-01

A set of features is the basis for the network representation of proximity data achieved by feature network models (FNMs). Features are binary variables that characterize the objects in an experiment, with some measure of proximity as response variable. Sometimes features are provided by theory and play an important role in the construction of the experimental conditions. In some research settings, the features are not known a priori. This paper shows how to generate features in this situation and how to select an adequate subset of features that takes into account a good compromise between model fit and model complexity, using a new version of least angle regression that restricts coefficients to be non-negative, called the Positive Lasso. It will be shown that features can be generated efficiently with Gray codes that are naturally linked to the FNMs. The model selection strategy makes use of the fact that FNM can be considered as univariate multiple regression model. A simulation study shows that the proposed strategy leads to satisfactory results if the number of objects is less than or equal to 22. If the number of objects is larger than 22, the number of features selected by our method exceeds the true number of features in some conditions.

Social Networks and the Diffusion of Adolescent Problem Behavior: Reliable Estimates of Selection and Influence from Sixth Through Ninth Grades.

PubMed

Osgood, D Wayne; Feinberg, Mark E; Ragan, Daniel T

2015-08-01

Seeking to reduce problematic peer influence is a prominent theme of programs to prevent adolescent problem behavior. To support the refinement of this aspect of prevention programming, we examined peer influence and selection processes for three problem behaviors (delinquency, alcohol use, and smoking). We assessed not only the overall strengths of these peer processes, but also their consistency versus variability across settings. We used dynamic stochastic actor-based models to analyze five waves of friendship network data across sixth through ninth grades for a large sample of U.S. adolescents. Our sample included two successive grade cohorts of youth in 26 school districts participating in the PROSPER study, yielding 51 longitudinal social networks based on respondents' friendship nominations. For all three self-reported antisocial behaviors, we found evidence of both peer influence and selection processes tied to antisocial behavior. There was little reliable variance in these processes across the networks, suggesting that the statistical imprecision of the peer influence and selection estimates in previous studies likely accounts for inconsistencies in results. Adolescent friendship networks play a strong role in shaping problem behavior, but problem behaviors also inform friendship choices. In addition to preferring friends with similar levels of problem behavior, adolescents tend to choose friends who engage in problem behaviors, thus creating broader diffusion.

Suppressing turbulence of self-propelling rods by strongly coupled passive particles.

PubMed

Su, Yen-Shuo; Wang, Hao-Chen; I, Lin

2015-03-01

The strong turbulence suppression, mainly for large-scale modes, of two-dimensional self-propelling rods, by increasing the long-range coupling strength Γ of low-concentration passive particles, is numerically demonstrated. It is found that large-scale collective rod motion in forms of swirls or jets is mainly contributed from well-aligned dense patches, which can push small poorly aligned rod patches and uncoupled passive particles. The more efficient momentum transfer and dissipation through increasing passive particle coupling leads to the formation of a more ordered and slowed down network of passive particles, which competes with coherent dense active rod clusters. The frustration of active rod alignment ordering and coherent motion by the passive particle network, which interrupt the inverse cascading of forming large-scale swirls, is the key for suppressing collective rod motion with scales beyond the interpassive distance, even in the liquid phase of passive particles. The loosely packed active rods are weakly affected by increasing passive particle coupling due to the weak rod-particle interaction. They mainly contribute to the small-scale modes and high-speed motion.

Adjuvant Exemestane with Ovarian Suppression in Premenopausal Breast Cancer

PubMed Central

Pagani, Olivia; Regan, Meredith M.; Walley, Barbara A.; Fleming, Gini F.; Colleoni, Marco; Láng, István; Gomez, Henry L.; Tondini, Carlo; Burstein, Harold J.; Perez, Edith A.; Ciruelos, Eva; Stearns, Vered; Bonnefoi, Hervé R.; Martino, Silvana; Geyer, Charles E.; Pinotti, Graziella; Puglisi, Fabio; Crivellari, Diana; Ruhstaller, Thomas; Winer, Eric P.; Rabaglio-Poretti, Manuela; Maibach, Rudolf; Ruepp, Barbara; Giobbie-Hurder, Anita; Price, Karen N.; Bernhard, Jürg; Luo, Weixiu; Ribi, Karin; Viale, Giuseppe; Coates, Alan S.; Gelber, Richard D.; Goldhirsch, Aron; Francis, Prudence A.

2014-01-01

BACKGROUND Adjuvant therapy with an aromatase inhibitor improves outcomes, as compared with tamoxifen, in postmenopausal women with hormone-receptor–positive breast cancer. METHODS In two phase 3 trials, we randomly assigned premenopausal women with hormone-receptor–positive early breast cancer to the aromatase inhibitor exemestane plus ovarian suppression or tamoxifen plus ovarian suppression for a period of 5 years. Suppression of ovarian estrogen production was achieved with the use of the gonadotropin-releasing-hormone agonist triptorelin, oophorectomy, or ovarian irradiation. The primary analysis combined data from 4690 patients in the two trials. RESULTS After a median follow-up of 68 months, disease-free survival at 5 years was 91.1% in the exemestane–ovarian suppression group and 87.3% in the tamoxifen–ovarian suppression group (hazard ratio for disease recurrence, second invasive cancer, or death, 0.72; 95% confidence interval [CI], 0.60 to 0.85; P<0.001). The rate of freedom from breast cancer at 5 years was 92.8% in the exemestane–ovarian suppression group, as compared with 88.8% in the tamoxifen–ovarian suppression group (hazard ratio for recurrence, 0.66; 95% CI, 0.55 to 0.80; P<0.001). With 194 deaths (4.1% of the patients), overall survival did not differ significantly between the two groups (hazard ratio for death in the exemestane–ovarian suppression group, 1.14; 95% CI, 0.86 to 1.51; P = 0.37). Selected adverse events of grade 3 or 4 were reported for 30.6% of the patients in the exemestane–ovarian suppression group and 29.4% of those in the tamoxifen–ovarian suppression group, with profiles similar to those for postmenopausal women. CONCLUSIONS In premenopausal women with hormone-receptor–positive early breast cancer, adjuvant treatment with exemestane plus ovarian suppression, as compared with tamoxifen plus ovarian suppression, significantly reduced recurrence. (Funded by Pfizer and others; TEXT and SOFT Clinical

Adjuvant exemestane with ovarian suppression in premenopausal breast cancer.

PubMed

Pagani, Olivia; Regan, Meredith M; Walley, Barbara A; Fleming, Gini F; Colleoni, Marco; Láng, István; Gomez, Henry L; Tondini, Carlo; Burstein, Harold J; Perez, Edith A; Ciruelos, Eva; Stearns, Vered; Bonnefoi, Hervé R; Martino, Silvana; Geyer, Charles E; Pinotti, Graziella; Puglisi, Fabio; Crivellari, Diana; Ruhstaller, Thomas; Winer, Eric P; Rabaglio-Poretti, Manuela; Maibach, Rudolf; Ruepp, Barbara; Giobbie-Hurder, Anita; Price, Karen N; Bernhard, Jürg; Luo, Weixiu; Ribi, Karin; Viale, Giuseppe; Coates, Alan S; Gelber, Richard D; Goldhirsch, Aron; Francis, Prudence A

2014-07-10

Adjuvant therapy with an aromatase inhibitor improves outcomes, as compared with tamoxifen, in postmenopausal women with hormone-receptor-positive breast cancer. In two phase 3 trials, we randomly assigned premenopausal women with hormone-receptor-positive early breast cancer to the aromatase inhibitor exemestane plus ovarian suppression or tamoxifen plus ovarian suppression for a period of 5 years. Suppression of ovarian estrogen production was achieved with the use of the gonadotropin-releasing-hormone agonist triptorelin, oophorectomy, or ovarian irradiation. The primary analysis combined data from 4690 patients in the two trials. After a median follow-up of 68 months, disease-free survival at 5 years was 91.1% in the exemestane-ovarian suppression group and 87.3% in the tamoxifen-ovarian suppression group (hazard ratio for disease recurrence, second invasive cancer, or death, 0.72; 95% confidence interval [CI], 0.60 to 0.85; P<0.001). The rate of freedom from breast cancer at 5 years was 92.8% in the exemestane-ovarian suppression group, as compared with 88.8% in the tamoxifen-ovarian suppression group (hazard ratio for recurrence, 0.66; 95% CI, 0.55 to 0.80; P<0.001). With 194 deaths (4.1% of the patients), overall survival did not differ significantly between the two groups (hazard ratio for death in the exemestane-ovarian suppression group, 1.14; 95% CI, 0.86 to 1.51; P=0.37). Selected adverse events of grade 3 or 4 were reported for 30.6% of the patients in the exemestane-ovarian suppression group and 29.4% of those in the tamoxifen-ovarian suppression group, with profiles similar to those for postmenopausal women. In premenopausal women with hormone-receptor-positive early breast cancer, adjuvant treatment with exemestane plus ovarian suppression, as compared with tamoxifen plus ovarian suppression, significantly reduced recurrence. (Funded by Pfizer and others; TEXT and SOFT ClinicalTrials.gov numbers, NCT00066703 and NCT00066690, respectively.).

Reversible Assembly of Graphitic Carbon Nitride 3D Network for Highly Selective Dyes Absorption and Regeneration.

PubMed

Zhang, Yuye; Zhou, Zhixin; Shen, Yanfei; Zhou, Qing; Wang, Jianhai; Liu, Anran; Liu, Songqin; Zhang, Yuanjian

2016-09-27

Responsive assembly of 2D materials is of great interest for a range of applications. In this work, interfacial functionalized carbon nitride (CN) nanofibers were synthesized by hydrolyzing bulk CN in sodium hydroxide solution. The reversible assemble and disassemble behavior of the as-prepared CN nanofibers was investigated by using CO2 as a trigger to form a hydrogel network at first. Compared to the most widespread absorbent materials such as active carbon, graphene and previously reported supramolecular gel, the proposed CN hydrogel not only exhibited a competitive absorbing capacity (maximum absorbing capacity of methylene blue up to 402 mg/g) but also overcame the typical deficiencies such as poor selectivity and high energy-consuming regeneration. This work would provide a strategy to construct a 3D CN network and open an avenue for developing smart assembly for potential applications ranging from environment to selective extraction.

Evolutionary Agroecology: the potential for cooperative, high density, weed-suppressing cereals.

PubMed

Weiner, Jacob; Andersen, Sven B; Wille, Wibke K-M; Griepentrog, Hans W; Olsen, Jannie M

2010-09-01

Evolutionary theory can be applied to improve agricultural yields and/or sustainability, an approach we call Evolutionary Agroecology. The basic idea is that plant breeding is unlikely to improve attributes already favored by millions of years of natural selection, whereas there may be unutilized potential in selecting for attributes that increase total crop yield but reduce plants' individual fitness. In other words, plant breeding should be based on group selection. We explore this approach in relation to crop-weed competition, and argue that it should be possible to develop high density cereals that can utilize their initial size advantage over weeds to suppress them much better than under current practices, thus reducing or eliminating the need for chemical or mechanical weed control. We emphasize the role of density in applying group selection to crops: it is competition among individuals that generates the 'Tragedy of the Commons', providing opportunities to improve plant production by selecting for attributes that natural selection would not favor. When there is competition for light, natural selection of individuals favors a defensive strategy of 'shade avoidance', but a collective, offensive 'shading' strategy could increase weed suppression and yield in the high density, high uniformity cropping systems we envision.

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

NASA Astrophysics Data System (ADS)

Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

2016-06-01

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

Evaluation of CO2, N2 and He as Fire Suppression Agents in Microgravity

NASA Technical Reports Server (NTRS)

Ruff, Gary A.; Hicks, Michael; Pettegrew, Richard

2004-01-01

The U.S. modules of the International Space Station use gaseous CO2 as the fire extinguishing agent. This was selected as a result of extensive experience with CO2 as a fire suppressant in terrestrial applications, trade studies on various suppressants, and experiments. The selection of fire suppressants and suppression strategies for NASA s Lunar and Martian exploration missions will be based on the same studies and normal-gravity data unless reduced gravity fire suppression data is obtained. In this study, the suppressant agent concentrations required to extinguish a flame in low velocity convective flows within the 20-sec of low gravity on the KC-135 aircraft were investigated. Suppressant gas mixtures of CO2, N2, and He with the balance being oxygen/nitrogen mixtures with either 21% or 25% O2 were used to suppress flames on a 19-mm diameter PMMA cylinder in reduced gravity. For each of the suppressant mixtures, limiting concentrations were established that would extinguish the flame at any velocity. Similarly, concentrations were established that would not extinguish the flame. The limiting concentrations were generally consistent with previous studies but did suggest that geometry had an effect on the limiting conditions. Between the extinction and non-extinction limits, the suppression characteristics depended on the extinguishing agent, flow velocity, and O2 concentration. The limiting velocity data from the CO2, He, and N2 suppressants were well correlated using an effective mixture enthalpy per mole of O2, indicating that all act via O2 displacement and cooling mechanisms. In reduced gravity, the agent concentration required to suppress the flames increased as the velocity increased, up to approximately 10 cm/s (the maximum velocity evaluated in this experiment). The effective enthalpy required to extinguish flames at velocities of 10 cm/s is approximately the same as the concentrations in normal gravity. A computational study is underway to further

A genetic network that suppresses genome rearrangements in Saccharomyces cerevisiae and contains defects in cancers

PubMed Central

Putnam, Christopher D.; Srivatsan, Anjana; Nene, Rahul V.; Martinez, Sandra L.; Clotfelter, Sarah P.; Bell, Sara N.; Somach, Steven B.; E.S. de Souza, Jorge; Fonseca, André F.; de Souza, Sandro J.; Kolodner, Richard D.

2016-01-01

Gross chromosomal rearrangements (GCRs) play an important role in human diseases, including cancer. The identity of all Genome Instability Suppressing (GIS) genes is not currently known. Here multiple Saccharomyces cerevisiae GCR assays and query mutations were crossed into arrays of mutants to identify progeny with increased GCR rates. One hundred eighty two GIS genes were identified that suppressed GCR formation. Another 438 cooperatively acting GIS genes were identified that were not GIS genes, but suppressed the increased genome instability caused by individual query mutations. Analysis of TCGA data using the human genes predicted to act in GIS pathways revealed that a minimum of 93% of ovarian and 66% of colorectal cancer cases had defects affecting one or more predicted GIS gene. These defects included loss-of-function mutations, copy-number changes associated with reduced expression, and silencing. In contrast, acute myeloid leukaemia cases did not appear to have defects affecting the predicted GIS genes. PMID:27071721

Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

NASA Astrophysics Data System (ADS)

Gouissem, A.; Hamila, R.; Al-Dhahir, N.; Foufou, S.

2016-12-01

In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte Carlo simulations.

Neural adaptive control for vibration suppression in composite fin-tip of aircraft.

PubMed

Suresh, S; Kannan, N; Sundararajan, N; Saratchandran, P

2008-06-01

In this paper, we present a neural adaptive control scheme for active vibration suppression of a composite aircraft fin tip. The mathematical model of a composite aircraft fin tip is derived using the finite element approach. The finite element model is updated experimentally to reflect the natural frequencies and mode shapes very accurately. Piezo-electric actuators and sensors are placed at optimal locations such that the vibration suppression is a maximum. Model-reference direct adaptive neural network control scheme is proposed to force the vibration level within the minimum acceptable limit. In this scheme, Gaussian neural network with linear filters is used to approximate the inverse dynamics of the system and the parameters of the neural controller are estimated using Lyapunov based update law. In order to reduce the computational burden, which is critical for real-time applications, the number of hidden neurons is also estimated in the proposed scheme. The global asymptotic stability of the overall system is ensured using the principles of Lyapunov approach. Simulation studies are carried-out using sinusoidal force functions of varying frequency. Experimental results show that the proposed neural adaptive control scheme is capable of providing significant vibration suppression in the multiple bending modes of interest. The performance of the proposed scheme is better than the H(infinity) control scheme.

Effectors from Wheat Rust Fungi Suppress Multiple Plant Defense Responses.

PubMed

Ramachandran, Sowmya R; Yin, Chuntao; Kud, Joanna; Tanaka, Kiwamu; Mahoney, Aaron K; Xiao, Fangming; Hulbert, Scot H

2017-01-01

Fungi that cause cereal rust diseases (genus Puccinia) are important pathogens of wheat globally. Upon infection, the fungus secretes a number of effector proteins. Although a large repository of putative effectors has been predicted using bioinformatic pipelines, the lack of available high-throughput effector screening systems has limited functional studies on these proteins. In this study, we mined the available transcriptomes of Puccinia graminis and P. striiformis to look for potential effectors that suppress host hypersensitive response (HR). Twenty small (<300 amino acids), secreted proteins, with no predicted functions were selected for the HR suppression assay using Nicotiana benthamiana, in which each of the proteins were transiently expressed and evaluated for their ability to suppress HR caused by four cytotoxic effector-R gene combinations (Cp/Rx, ATR13/RPP13, Rpt2/RPS-2, and GPA/RBP-1) and one mutated R gene-Pto(Y207D). Nine out of twenty proteins, designated Shr1 to Shr9 (suppressors of hypersensitive response), were found to suppress HR in N. benthamiana. These effectors varied in the effector-R gene defenses they suppressed, indicating these pathogens can interfere with a variety of host defense pathways. In addition to HR suppression, effector Shr7 also suppressed PAMP-triggered immune response triggered by flg22. Finally, delivery of Shr7 through Pseudomonas fluorescens EtHAn suppressed nonspecific HR induced by Pseudomonas syringae DC3000 in wheat, confirming its activity in a homologous system. Overall, this study provides the first evidence for the presence of effectors in Puccinia species suppressing multiple plant defense responses.

Selective Memories: Infants' Encoding Is Enhanced in Selection via Suppression

ERIC Educational Resources Information Center

Markant, Julie; Amso, Dima

2013-01-01

The present study examined the hypothesis that inhibitory visual selection mechanisms play a vital role in memory by limiting distractor interference during item encoding. In Experiment 1a we used a modified spatial cueing task in which 9-month-old infants encoded multiple category exemplars in the contexts of an attention orienting mechanism…

The multiple facets of Peto's paradox: a life-history model for the evolution of cancer suppression

PubMed Central

Brown, Joel S.; Cunningham, Jessica J.; Gatenby, Robert A.

2015-01-01

Large animals should have higher lifetime probabilities of cancer than small animals because each cell division carries an attendant risk of mutating towards a tumour lineage. However, this is not observed—a (Peto's) paradox that suggests large and/or long-lived species have evolved effective cancer suppression mechanisms. Using the Euler–Lotka population model, we demonstrate the evolutionary value of cancer suppression as determined by the ‘cost’ (decreased fecundity) of suppression verses the ‘cost’ of cancer (reduced survivorship). Body size per se will not select for sufficient cancer suppression to explain the paradox. Rather, cancer suppression should be most extreme when the probability of non-cancer death decreases with age (e.g. alligators), maturation is delayed, fecundity rates are low and fecundity increases with age. Thus, the value of cancer suppression is predicted to be lowest in the vole (short lifespan, high fecundity) and highest in the naked mole rat (long lived with late female sexual maturity). The life history of pre-industrial humans likely selected for quite low levels of cancer suppression. In modern humans that live much longer, this level results in unusually high lifetime cancer risks. The model predicts a lifetime risk of 49% compared with the current empirical value of 43%. PMID:26056365

Phosphorodiamidate morpholino oligomers suppress mutant huntingtin expression and attenuate neurotoxicity

PubMed Central

Sun, Xin; Marque, Leonard O.; Cordner, Zachary; Pruitt, Jennifer L.; Bhat, Manik; Li, Pan P.; Kannan, Geetha; Ladenheim, Ellen E.; Moran, Timothy H.; Margolis, Russell L.; Rudnicki, Dobrila D.

2014-01-01

Huntington's disease (HD) is a neurodegenerative disorder caused by a CAG trinucleotide repeat expansion in the huntingtin (HTT) gene. Disease pathogenesis derives, at least in part, from the long polyglutamine tract encoded by mutant HTT. Therefore, considerable effort has been dedicated to the development of therapeutic strategies that significantly reduce the expression of the mutant HTT protein. Antisense oligonucleotides (ASOs) targeted to the CAG repeat region of HTT transcripts have been of particular interest due to their potential capacity to discriminate between normal and mutant HTT transcripts. Here, we focus on phosphorodiamidate morpholino oligomers (PMOs), ASOs that are especially stable, highly soluble and non-toxic. We designed three PMOs to selectively target expanded CAG repeat tracts (CTG22, CTG25 and CTG28), and two PMOs to selectively target sequences flanking the HTT CAG repeat (HTTex1a and HTTex1b). In HD patient–derived fibroblasts with expanded alleles containing 44, 77 or 109 CAG repeats, HTTex1a and HTTex1b were effective in suppressing the expression of mutant and non-mutant transcripts. CTGn PMOs also suppressed HTT expression, with the extent of suppression and the specificity for mutant transcripts dependent on the length of the targeted CAG repeat and on the CTG repeat length and concentration of the PMO. PMO CTG25 reduced HTT-induced cytotoxicity in vitro and suppressed mutant HTT expression in vivo in the N171-82Q transgenic mouse model. Finally, CTG28 reduced mutant HTT expression and improved the phenotype of HdhQ7/Q150 knock-in HD mice. These data demonstrate the potential of PMOs as an approach to suppressing the expression of mutant HTT. PMID:25035419

The interplay of friendship networks and social networking sites: longitudinal analysis of selection and influence effects on adolescent smoking and alcohol use.

PubMed

Huang, Grace C; Soto, Daniel; Fujimoto, Kayo; Valente, Thomas W

2014-08-01

We examined the coevolution of adolescent friendships and peer influences with respect to their risk behaviors and social networking site use. Investigators of the Social Network Study collected longitudinal data during fall 2010 and spring 2011 from 10th-grade students in 5 Southern California high schools (n = 1434). We used meta-analyses of stochastic actor-based models to estimate changes in friendship ties and risk behaviors and the effects of Facebook and MySpace use. Significant shifts in adolescent smoking and drinking occurred despite little change in overall prevalence rates. Students with higher levels of alcohol use were more likely to send and receive friendship nominations and become friends with other drinkers. They were also more likely to increase alcohol use if their friends drank more. Adolescents selected friends with similar Facebook and MySpace use habits. Exposure to friends' risky online pictures increased smoking behaviors but had no significant effects on alcohol use. Our findings support a greater focus on friendship selection mechanisms in school-based alcohol use interventions. Social media platforms may help identify at-risk adolescent groups and foster positive norms about risk behaviors.

The Interplay of Friendship Networks and Social Networking Sites: Longitudinal Analysis of Selection and Influence Effects on Adolescent Smoking and Alcohol Use

PubMed Central

Soto, Daniel; Fujimoto, Kayo; Valente, Thomas W.

2014-01-01

Objectives. We examined the coevolution of adolescent friendships and peer influences with respect to their risk behaviors and social networking site use. Methods. Investigators of the Social Network Study collected longitudinal data during fall 2010 and spring 2011 from 10th-grade students in 5 Southern California high schools (n = 1434). We used meta-analyses of stochastic actor-based models to estimate changes in friendship ties and risk behaviors and the effects of Facebook and MySpace use. Results. Significant shifts in adolescent smoking and drinking occurred despite little change in overall prevalence rates. Students with higher levels of alcohol use were more likely to send and receive friendship nominations and become friends with other drinkers. They were also more likely to increase alcohol use if their friends drank more. Adolescents selected friends with similar Facebook and MySpace use habits. Exposure to friends’ risky online pictures increased smoking behaviors but had no significant effects on alcohol use. Conclusions. Our findings support a greater focus on friendship selection mechanisms in school-based alcohol use interventions. Social media platforms may help identify at-risk adolescent groups and foster positive norms about risk behaviors. PMID:24922126

Prevention and suppression of metal packing fires.

PubMed

Roberts, Mark; Rogers, William J; Sam Mannan, M; Ostrowski, Scott W

2003-11-14

Structured packing has been widely used because of large surface area that makes possible columns with high capacity and efficiency. The large surface area also contributes to fire hazards because of hydrocarbon deposits that can easily combust and promote combustion of the thin metal packing materials. Materials of high surface area that can fuel fires include reactive metals, such as titanium, and materials that are not considered combustible, such as stainless steel. Column design and material selection for packing construction is discussed together with employee training and practices for safe column maintenance and operations. Presented also are methods and agents for suppression of metal fires. Guidance for prevention and suppression of metal fires is related to incidents involving packing fires in columns.

Spatiotemporal alterations of cortical network activity by selective loss of NOS-expressing interneurons.

PubMed

Shlosberg, Dan; Buskila, Yossi; Abu-Ghanem, Yasmin; Amitai, Yael

2012-01-01

Deciphering the role of GABAergic neurons in large neuronal networks such as the neocortex forms a particularly complex task as they comprise a highly diverse population. The neuronal isoform of the enzyme nitric oxide synthase (nNOS) is expressed in the neocortex by specific subsets of GABAergic neurons. These neurons can be identified in live brain slices by the nitric oxide (NO) fluorescent indicator diaminofluorescein-2 diacetate (DAF-2DA). However, this indicator was found to be highly toxic to the stained neurons. We used this feature to induce acute phototoxic damage to NO-producing neurons in cortical slices, and measured subsequent alterations in parameters of cellular and network activity. Neocortical slices were briefly incubated in DAF-2DA and then illuminated through the 4× objective. Histochemistry for NADPH-diaphorase (NADPH-d), a marker for nNOS activity, revealed elimination of staining in the illuminated areas following treatment. Whole cell recordings from several neuronal types before, during, and after illumination confirmed the selective damage to non-fast-spiking (FS) interneurons. Treated slices displayed mild disinhibition. The reversal potential of compound synaptic events on pyramidal neurons became more positive, and their decay time constant was elongated, substantiating the removal of an inhibitory conductance. The horizontal decay of local field potentials (LFPs) was significantly reduced at distances of 300-400 μm from the stimulation, but not when inhibition was non-selectively weakened with the GABA(A) blocker picrotoxin. Finally, whereas the depression of LFPs along short trains of 40 Hz stimuli was linearly reduced with distance or initial amplitude in control slices, this ordered relationship was disrupted in DAF-treated slices. These results reveal that NO-producing interneurons in the neocortex convey lateral inhibition to neighboring columns, and shape the spatiotemporal dynamics of the network's activity.

Local cortical dynamics of burst suppression in the anaesthetized brain.

PubMed

Lewis, Laura D; Ching, Shinung; Weiner, Veronica S; Peterfreund, Robert A; Eskandar, Emad N; Cash, Sydney S; Brown, Emery N; Purdon, Patrick L

2013-09-01

Burst suppression is an electroencephalogram pattern that consists of a quasi-periodic alternation between isoelectric 'suppressions' lasting seconds or minutes, and high-voltage 'bursts'. It is characteristic of a profoundly inactivated brain, occurring in conditions including hypothermia, deep general anaesthesia, infant encephalopathy and coma. It is also used in neurology as an electrophysiological endpoint in pharmacologically induced coma for brain protection after traumatic injury and during status epilepticus. Classically, burst suppression has been regarded as a 'global' state with synchronous activity throughout cortex. This assumption has influenced the clinical use of burst suppression as a way to broadly reduce neural activity. However, the extent of spatial homogeneity has not been fully explored due to the challenges in recording from multiple cortical sites simultaneously. The neurophysiological dynamics of large-scale cortical circuits during burst suppression are therefore not well understood. To address this question, we recorded intracranial electrocorticograms from patients who entered burst suppression while receiving propofol general anaesthesia. The electrodes were broadly distributed across cortex, enabling us to examine both the dynamics of burst suppression within local cortical regions and larger-scale network interactions. We found that in contrast to previous characterizations, bursts could be substantially asynchronous across the cortex. Furthermore, the state of burst suppression itself could occur in a limited cortical region while other areas exhibited ongoing continuous activity. In addition, we found a complex temporal structure within bursts, which recapitulated the spectral dynamics of the state preceding burst suppression, and evolved throughout the course of a single burst. Our observations imply that local cortical dynamics are not homogeneous, even during significant brain inactivation. Instead, cortical and, implicitly

An Examination of Native and Immigrant Students' Social Networking Using the College Search and Selection Process

ERIC Educational Resources Information Center

Neimeyer, Bruce Carlton

2009-01-01

This dissertation explores the use of formal and informal networks through cyber- and traditional communication methods in the college search and selection process by native and immigrant students to examine various postulates and propositions of social capital theory. In addition, the analysis of cybernetworks used by disadvantaged, college bound…

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

PubMed

Harper, Nicol S; Schoppe, Oliver; Willmore, Ben D B; Cui, Zhanfeng; Schnupp, Jan W H; King, Andrew J

2016-11-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons

PubMed Central

Willmore, Ben D. B.; Cui, Zhanfeng; Schnupp, Jan W. H.; King, Andrew J.

2016-01-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1–7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context. PMID:27835647

Classification of burst and suppression in the neonatal electroencephalogram

NASA Astrophysics Data System (ADS)

Löfhede, J.; Löfgren, N.; Thordstein, M.; Flisberg, A.; Kjellmer, I.; Lindecrantz, K.

2008-12-01

Fisher's linear discriminant (FLD), a feed-forward artificial neural network (ANN) and a support vector machine (SVM) were compared with respect to their ability to distinguish bursts from suppressions in electroencephalograms (EEG) displaying a burst-suppression pattern. Five features extracted from the EEG were used as inputs. The study was based on EEG signals from six full-term infants who had suffered from perinatal asphyxia, and the methods have been trained with reference data classified by an experienced electroencephalographer. The results are summarized as the area under the curve (AUC), derived from receiver operating characteristic (ROC) curves for the three methods. Based on this, the SVM performs slightly better than the others. Testing the three methods with combinations of increasing numbers of the five features shows that the SVM handles the increasing amount of information better than the other methods.

A comparison of novel, selective fatty acid amide hydrolase (FAAH), monoacyglycerol lipase (MAGL) or dual FAAH/MAGL inhibitors to suppress acute and anticipatory nausea in rat models.

PubMed

Parker, Linda A; Limebeer, Cheryl L; Rock, Erin M; Sticht, Martin A; Ward, Jordan; Turvey, Greig; Benchama, Othman; Rajarshi, Girija; Wood, JodiAnne T; Alapafuja, Shakiru O; Makriyannis, Alexandros

2016-06-01

Drugs that block fatty acid amide hydrolase (FAAH, which elevates anandamide [AEA]) and drugs which block monoacylglycerol (MAGL, which elevates 2-arachidonyl glycerol [2-AG]) have promise in treating both acute and anticipatory nausea in human patients. This study aims to evaluate the relative effectiveness of dual MAGL/FAAH inhibition with either alone to reduce acute and anticipatory nausea in rat models. AM4302, a new dual MAGL/FAAH inhibitor, was compared with a new selective MAGL inhibitor, AM4301, and new selective FAAH inhibitor, AM4303, for their potential to reduce acute nausea (gaping in taste reactivity) and anticipatory nausea (contextually elicited conditioned gaping) in two rat models. Our in vitro studies indicate that AM4302 blocks human and rat FAAH: IC50 60 and 31 nM, respectively, with comparable potencies against human MAGL (IC50 41 nM) and rat MAGL (IC50 200 nM). AM4301 selectively blocks human and rat MAGL (IC50 8.9 and 36 nM, respectively), while AM4303 selectively inhibits human and rat FAAH (IC50 2 and 1.9 nM), respectively. Our in vivo studies show that the MAGL inhibitor, AM4301, suppressed acute nausea in a CB1-mediated manner, when delivered systemically or into the interoceptive insular cortex. Although the dual FAAH/MAGL inhibitor, AM4302, was equally effective as the FAAH inhibitor or MAGL inhibitor in reducing acute nausea, it was more effective than both in suppressing anticipatory nausea. Dual FAAH and MAGL inhibition with AM4302 may be an especially effective treatment for the very difficult to treat symptom of anticipatory nausea.

A comparison of novel, selective fatty acid amide hydrolase (FAAH), monoacyglycerol lipase (MAGL) or dual FAAH/MAGL inhibitors to suppress acute and anticipatory nausea in rat models

PubMed Central

Limebeer, Cheryl L.; Rock, Erin M.; Sticht, Martin A.; Ward, Jordan; Turvey, Greig; Benchama, Othman; Rajarshi, Girija; Wood, JodiAnne T.; Alapafuja, Shakiru O.; Makriyannis, Alexandros

2017-01-01

Rationale Drugs that block fatty acid amide hydrolase (FAAH, which elevates anandamide [AEA]) and drugs which block monoacylglycerol (MAGL, which elevates 2-arachidonyl glycerol [2-AG]) have promise in treating both acute and anticipatory nausea in human patients. Objective This study aims to evaluate the relative effectiveness of dual MAGL/FAAH inhibition with either alone to reduce acute and anticipatory nausea in rat models. Materials and methods AM4302, a new dual MAGL/FAAH inhibitor, was compared with a new selective MAGL inhibitor, AM4301, and new selective FAAH inhibitor, AM4303, for their potential to reduce acute nausea (gaping in taste reactivity) and anticipatory nausea (contextually elicited conditioned gaping) in two rat models. Results Our in vitro studies indicate that AM4302 blocks human and rat FAAH: IC50 60 and 31 nM, respectively, with comparable potencies against human MAGL (IC50 41 nM) and rat MAGL (IC50 200 nM). AM4301 selectively blocks human and rat MAGL (IC50 8.9 and 36 nM, respectively), while AM4303 selectively inhibits human and rat FAAH (IC50 2 and 1.9 nM), respectively. Our in vivo studies show that the MAGL inhibitor, AM4301, suppressed acute nausea in a CB1-mediated manner, when delivered systemically or into the interoceptive insular cortex. Although the dual FAAH/MAGL inhibitor, AM4302, was equally effective as the FAAH inhibitor or MAGL inhibitor in reducing acute nausea, it was more effective than both in suppressing anticipatory nausea. Conclusions Dual FAAH and MAGL inhibition with AM4302 may be an especially effective treatment for the very difficult to treat symptom of anticipatory nausea. PMID:27048155

Reversible Smad-dependent signaling between tumor suppression and oncogenesis.

PubMed

Sekimoto, Go; Matsuzaki, Koichi; Yoshida, Katsunori; Mori, Shigeo; Murata, Miki; Seki, Toshihito; Matsui, Hirofumi; Fujisawa, Jun-ichi; Okazaki, Kazuichi

2007-06-01

Cancer cells often gain advantage by reducing the tumor-suppressive activity of transforming growth factor-beta (TGF-beta) together with stimulation of its oncogenic activity as in Ras-transformed cells; however, molecular mechanisms remain largely unknown. TGF-beta activates both its type I receptor (TbetaRI) and c-Jun NH2-terminal kinase (JNK), which phosphorylate Smad2 and Smad3 at the COOH-terminal (pSmad2/3C) and linker regions (pSmad2/3L). Here, we report that Ras transformation suppresses TbetaRI-mediated pSmad3C signaling, which involves growth inhibition by down-regulating c-Myc. Instead, hyperactive Ras constitutively stimulates JNK-mediated pSmad2/3L signaling, which fosters tumor invasion by up-regulating plasminogen activator inhibitor-1 and matrix metalloproteinase-1 (MMP-1), MMP-2, and MMP-9. Conversely, selective blockade of linker phosphorylation by a mutant Smad3 lacking JNK-dependent phosphorylation sites results in preserved tumor-suppressive function via pSmad3C in Ras-transformed cells while eliminating pSmad2/3L-mediated invasive capacity. Thus, specific inhibition of the JNK/pSmad2/3L pathway should suppress cancer progression by shifting Smad-dependent signaling from oncogenesis to tumor suppression.

Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things.

PubMed

Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

2015-09-18

With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified.

Multi-channels coupling-induced pattern transition in a tri-layer neuronal network

NASA Astrophysics Data System (ADS)

Wu, Fuqiang; Wang, Ya; Ma, Jun; Jin, Wuyin; Hobiny, Aatef

2018-03-01

Neurons in nerve system show complex electrical behaviors due to complex connection types and diversity in excitability. A tri-layer network is constructed to investigate the signal propagation and pattern formation by selecting different coupling channels between layers. Each layer is set as different states, and the local kinetics is described by Hindmarsh-Rose neuron model. By changing the number of coupling channels between layers and the state of the first layer, the collective behaviors of each layer and synchronization pattern of network are investigated. A statistical factor of synchronization on each layer is calculated. It is found that quiescent state in the second layer can be excited and disordered state in the third layer is suppressed when the first layer is controlled by a pacemaker, and the developed state is dependent on the number of coupling channels. Furthermore, the collapse in the first layer can cause breakdown of other layers in the network, and the mechanism is that disordered state in the third layer is enhanced when sampled signals from the collapsed layer can impose continuous disturbance on the next layer.

Resource constrained flux balance analysis predicts selective pressure on the global structure of metabolic networks.

PubMed

Abedpour, Nima; Kollmann, Markus

2015-11-23

A universal feature of metabolic networks is their hourglass or bow-tie structure on cellular level. This architecture reflects the conversion of multiple input nutrients into multiple biomass components via a small set of precursor metabolites. However, it is yet unclear to what extent this structural feature is the result of natural selection. We extend flux balance analysis to account for limited cellular resources. Using this model, optimal structure of metabolic networks can be calculated for different environmental conditions. We observe a significant structural reshaping of metabolic networks for a toy-network and E. coli core metabolism if we increase the share of invested resources for switching between different nutrient conditions. Here, hub nodes emerge and the optimal network structure becomes bow-tie-like as a consequence of limited cellular resource constraint. We confirm this theoretical finding by comparing the reconstructed metabolic networks of bacterial species with respect to their lifestyle. We show that bow-tie structure can give a system-level fitness advantage to organisms that live in highly competitive and fluctuating environments. Here, limitation of cellular resources can lead to an efficiency-flexibility tradeoff where it pays off for the organism to shorten catabolic pathways if they are frequently activated and deactivated. As a consequence, generalists that shuttle between diverse environmental conditions should have a more predominant bow-tie structure than specialists that visit just a few isomorphic habitats during their life cycle.

An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting.

PubMed

Hippert, Henrique S; Taylor, James W

2010-04-01

Artificial neural networks have frequently been proposed for electricity load forecasting because of their capabilities for the nonlinear modelling of large multivariate data sets. Modelling with neural networks is not an easy task though; two of the main challenges are defining the appropriate level of model complexity, and choosing the input variables. This paper evaluates techniques for automatic neural network modelling within a Bayesian framework, as applied to six samples containing daily load and weather data for four different countries. We analyse input selection as carried out by the Bayesian 'automatic relevance determination', and the usefulness of the Bayesian 'evidence' for the selection of the best structure (in terms of number of neurones), as compared to methods based on cross-validation. Copyright 2009 Elsevier Ltd. All rights reserved.

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors

PubMed Central

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-01-01

Motivation Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. Results We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. Availability A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm. PMID:21234299

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors.

PubMed

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-12-12

Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm.

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.

PubMed

Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

2015-01-01

This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks

PubMed Central

Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

2015-01-01

This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571

Key node selection in minimum-cost control of complex networks

NASA Astrophysics Data System (ADS)

Ding, Jie; Wen, Changyun; Li, Guoqi

2017-11-01

Finding the key node set that is connected with a given number of external control sources for driving complex networks from initial state to any predefined state with minimum cost, known as minimum-cost control problem, is critically important but remains largely open. By defining an importance index for each node, we propose revisited projected gradient method extension (R-PGME) in Monte-Carlo scenario to determine key node set. It is found that the importance index of a node is strongly correlated to occurrence rate of that node to be selected as a key node in Monte-Carlo realizations for three elementary topologies, Erdős-Rényi and scale-free networks. We also discover the distribution patterns of key nodes when the control cost reaches its minimum. Specifically, the importance indices of all nodes in an elementary stem show a quasi-periodic distribution with high peak values in the beginning and end of a quasi-period while they approach to a uniform distribution in an elementary cycle. We further point out that an elementary dilation can be regarded as two elementary stems whose lengths are the closest, and the importance indices in each stem present similar distribution as in an elementary stem. Our results provide a better understanding and deep insight of locating the key nodes in different topologies with minimum control cost.

The multiple facets of Peto's paradox: a life-history model for the evolution of cancer suppression.

PubMed

Brown, Joel S; Cunningham, Jessica J; Gatenby, Robert A

2015-07-19

Large animals should have higher lifetime probabilities of cancer than small animals because each cell division carries an attendant risk of mutating towards a tumour lineage. However, this is not observed--a (Peto's) paradox that suggests large and/or long-lived species have evolved effective cancer suppression mechanisms. Using the Euler-Lotka population model, we demonstrate the evolutionary value of cancer suppression as determined by the 'cost' (decreased fecundity) of suppression verses the 'cost' of cancer (reduced survivorship). Body size per se will not select for sufficient cancer suppression to explain the paradox. Rather, cancer suppression should be most extreme when the probability of non-cancer death decreases with age (e.g. alligators), maturation is delayed, fecundity rates are low and fecundity increases with age. Thus, the value of cancer suppression is predicted to be lowest in the vole (short lifespan, high fecundity) and highest in the naked mole rat (long lived with late female sexual maturity). The life history of pre-industrial humans likely selected for quite low levels of cancer suppression. In modern humans that live much longer, this level results in unusually high lifetime cancer risks. The model predicts a lifetime risk of 49% compared with the current empirical value of 43%. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Burst suppression probability algorithms: state-space methods for tracking EEG burst suppression

NASA Astrophysics Data System (ADS)

Chemali, Jessica; Ching, ShiNung; Purdon, Patrick L.; Solt, Ken; Brown, Emery N.

2013-10-01

Objective. Burst suppression is an electroencephalogram pattern in which bursts of electrical activity alternate with an isoelectric state. This pattern is commonly seen in states of severely reduced brain activity such as profound general anesthesia, anoxic brain injuries, hypothermia and certain developmental disorders. Devising accurate, reliable ways to quantify burst suppression is an important clinical and research problem. Although thresholding and segmentation algorithms readily identify burst suppression periods, analysis algorithms require long intervals of data to characterize burst suppression at a given time and provide no framework for statistical inference. Approach. We introduce the concept of the burst suppression probability (BSP) to define the brain's instantaneous propensity of being in the suppressed state. To conduct dynamic analyses of burst suppression we propose a state-space model in which the observation process is a binomial model and the state equation is a Gaussian random walk. We estimate the model using an approximate expectation maximization algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia and a patient during induction of controlled hypothermia. Main result. The BSP algorithms track burst suppression on a second-to-second time scale, and make possible formal statistical comparisons of burst suppression at different times. Significance. The state-space approach suggests a principled and informative way to analyze burst suppression that can be used to monitor, and eventually to control, the brain states of patients in the operating room and in the intensive care unit.

EGU2013 SM1.4/GI1.6 session: "Improving seismic networks performances: from site selection to data integration"

NASA Astrophysics Data System (ADS)

Pesaresi, D.; Busby, R.

2013-08-01

The number and quality of seismic stations and networks in Europe continually improves, nevertheless there is always scope to optimize their performance. In this session we welcomed contributions from all aspects of seismic network installation, operation and management. This includes site selection; equipment testing and installation; planning and implementing communication paths; policies for redundancy in data acquisition, processing and archiving; and integration of different datasets including GPS and OBS.

Robust support vector regression networks for function approximation with outliers.

PubMed

Chuang, Chen-Chia; Su, Shun-Feng; Jeng, Jin-Tsong; Hsiao, Chih-Ching

2002-01-01

Support vector regression (SVR) employs the support vector machine (SVM) to tackle problems of function approximation and regression estimation. SVR has been shown to have good robust properties against noise. When the parameters used in SVR are improperly selected, overfitting phenomena may still occur. However, the selection of various parameters is not straightforward. Besides, in SVR, outliers may also possibly be taken as support vectors. Such an inclusion of outliers in support vectors may lead to seriously overfitting phenomena. In this paper, a novel regression approach, termed as the robust support vector regression (RSVR) network, is proposed to enhance the robust capability of SVR. In the approach, traditional robust learning approaches are employed to improve the learning performance for any selected parameters. From the simulation results, our RSVR can always improve the performance of the learned systems for all cases. Besides, it can be found that even the training lasted for a long period, the testing errors would not go up. In other words, the overfitting phenomenon is indeed suppressed.

Zone routing in a torus network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Heidelberger, Philip; Kumar, Sameer

A system for routing data in a network comprising a network logic device at a sending node for determining a path between the sending node and a receiving node, wherein the network logic device sets one or more selection bits and one or more hint bits within the data packet, a control register for storing one or more masks, wherein the network logic device uses the one or more selection bits to select a mask from the control register and the network logic device applies the selected mask to the hint bits to restrict routing of the data packet tomore » one or more routing directions for the data packet within the network and selects one of the restricted routing directions from the one or more routing directions and sends the data packet along a link in the selected routing direction toward the receiving node.« less

Localization of Epileptogenic Zone With the Correction of Pathological Networks.

PubMed

Yang, Chuanzuo; Luan, Guoming; Wang, Qian; Liu, Zhao; Zhai, Feng; Wang, Qingyun

2018-01-01

Patients with focal drug-resistant epilepsy are potential candidates for surgery. Stereo-electroencephalograph (SEEG) is often considered as the "gold standard" to identify the epileptogenic zone (EZ) that accounts for the onset and propagation of epileptiform discharges. However, visual analysis of SEEG still prevails in clinical practice. In addition, epilepsy is increasingly understood to be the result of network disorder, but the specific organization of the epileptic network is still unclear. Therefore, it is necessary to quantitatively localize the EZ and investigate the nature of epileptogenic networks. In this study, intracranial recordings from 10 patients were analyzed through adaptive directed transfer function, and the out-degree of effective network was selected as the principal indicator to localize the epileptogenic area. Furthermore, a coupled neuronal population model was used to qualitatively simulate electrical activity in the brain. By removing individual populations, virtual surgery adjusting the network organization could be performed. Results suggested that the accuracy and detection rate of the EZ localization were 82.86 and 85.29%, respectively. In addition, the same stage shared a relatively stable connectivity pattern, while the patterns changed with transition to different processes. Meanwhile, eight cases of simulations indicated that networks in the ictal stage were more likely to generate rhythmic spikes. This indicated the existence of epileptogenic networks, which could enhance local excitability and facilitate synchronization. The removal of the EZ could correct these pathological networks and reduce the amount of spikes by at least 75%. This might be one reason why accurate resection could reduce or even suppress seizures. This study provides novel insights into epilepsy and surgical treatments from the network perspective.

Glucocorticoid suppression of osteocyte perilacunar remodeling is associated with subchondral bone degeneration in osteonecrosis

DOE PAGES

Fowler, Tristan W.; Acevedo, Claire; Mazur, Courtney M.; ...

2017-03-22

Through a process called perilacunar remodeling, bone-embedded osteocytes dynamically resorb and replace the surrounding perilacunar bone matrix to maintain mineral homeostasis. The vital canalicular networks required for osteocyte nourishment and communication, as well as the exquisitely organized bone extracellular matrix, also depend upon perilacunar remodeling. Nonetheless, many questions remain about the regulation of perilacunar remodeling and its role in skeletal disease. We find that suppression of osteocyte-driven perilacunar remodeling, a fundamental cellular mechanism, plays a critical role in the glucocorticoid-induced osteonecrosis. In glucocorticoid-treated mice, we find that glucocorticoids coordinately suppress expression of several proteases required for perilacunar remodeling while causingmore » degeneration of the osteocyte lacunocanalicular network, collagen disorganization, and matrix hypermineralization; all of which are apparent in human osteonecrotic lesions. Therefore, osteocyte-mediated perilacunar remodeling maintains bone homeostasis, is dysregulated in skeletal disease, and may represent an attractive therapeutic target for the treatment of osteonecrosis.« less

Glucocorticoid suppression of osteocyte perilacunar remodeling is associated with subchondral bone degeneration in osteonecrosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, Tristan W.; Acevedo, Claire; Mazur, Courtney M.

Through a process called perilacunar remodeling, bone-embedded osteocytes dynamically resorb and replace the surrounding perilacunar bone matrix to maintain mineral homeostasis. The vital canalicular networks required for osteocyte nourishment and communication, as well as the exquisitely organized bone extracellular matrix, also depend upon perilacunar remodeling. Nonetheless, many questions remain about the regulation of perilacunar remodeling and its role in skeletal disease. We find that suppression of osteocyte-driven perilacunar remodeling, a fundamental cellular mechanism, plays a critical role in the glucocorticoid-induced osteonecrosis. In glucocorticoid-treated mice, we find that glucocorticoids coordinately suppress expression of several proteases required for perilacunar remodeling while causingmore » degeneration of the osteocyte lacunocanalicular network, collagen disorganization, and matrix hypermineralization; all of which are apparent in human osteonecrotic lesions. Therefore, osteocyte-mediated perilacunar remodeling maintains bone homeostasis, is dysregulated in skeletal disease, and may represent an attractive therapeutic target for the treatment of osteonecrosis.« less

Fog-Based Two-Phase Event Monitoring and Data Gathering in Vehicular Sensor Networks

PubMed Central

Yang, Fan; Su, Jinsong; Zhou, Qifeng; Wang, Tian; Zhang, Lu; Xu, Yifan

2017-01-01

Vehicular nodes are equipped with more and more sensing units, and a large amount of sensing data is generated. Recently, more and more research considers cooperative urban sensing as the heart of intelligent and green city traffic management. The key components of the platform will be a combination of a pervasive vehicular sensing system, as well as a central control and analysis system, where data-gathering is a fundamental component. However, the data-gathering and monitoring are also challenging issues in vehicular sensor networks because of the large amount of data and the dynamic nature of the network. In this paper, we propose an efficient continuous event-monitoring and data-gathering framework based on fog nodes in vehicular sensor networks. A fog-based two-level threshold strategy is adopted to suppress unnecessary data upload and transmissions. In the monitoring phase, nodes sense the environment in low cost sensing mode and generate sensed data. When the probability of the event is high and exceeds some threshold, nodes transfer to the event-checking phase, and some nodes would be selected to transfer to the deep sensing mode to generate more accurate data of the environment. Furthermore, it adaptively adjusts the threshold to upload a suitable amount of data for decision making, while at the same time suppressing unnecessary message transmissions. Simulation results showed that the proposed scheme could reduce more than 84 percent of the data transmissions compared with other existing algorithms, while it detects the events and gathers the event data. PMID:29286320

Classification of complex networks based on similarity of topological network features

NASA Astrophysics Data System (ADS)

Attar, Niousha; Aliakbary, Sadegh

2017-09-01

Over the past few decades, networks have been widely used to model real-world phenomena. Real-world networks exhibit nontrivial topological characteristics and therefore, many network models are proposed in the literature for generating graphs that are similar to real networks. Network models reproduce nontrivial properties such as long-tail degree distributions or high clustering coefficients. In this context, we encounter the problem of selecting the network model that best fits a given real-world network. The need for a model selection method reveals the network classification problem, in which a target-network is classified into one of the candidate network models. In this paper, we propose a novel network classification method which is independent of the network size and employs an alignment-free metric of network comparison. The proposed method is based on supervised machine learning algorithms and utilizes the topological similarities of networks for the classification task. The experiments show that the proposed method outperforms state-of-the-art methods with respect to classification accuracy, time efficiency, and robustness to noise.

Feature selection for neural network based defect classification of ceramic components using high frequency ultrasound.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh

2015-09-01

The motivation for this research stems from a need for providing a non-destructive testing method capable of detecting and locating any defects and microstructural variations within armour ceramic components before issuing them to the soldiers who rely on them for their survival. The development of an automated ultrasonic inspection based classification system would make possible the checking of each ceramic component and immediately alert the operator about the presence of defects. Generally, in many classification problems a choice of features or dimensionality reduction is significant and simultaneously very difficult, as a substantial computational effort is required to evaluate possible feature subsets. In this research, a combination of artificial neural networks and genetic algorithms are used to optimize the feature subset used in classification of various defects in reaction-sintered silicon carbide ceramic components. Initially wavelet based feature extraction is implemented from the region of interest. An Artificial Neural Network classifier is employed to evaluate the performance of these features. Genetic Algorithm based feature selection is performed. Principal Component Analysis is a popular technique used for feature selection and is compared with the genetic algorithm based technique in terms of classification accuracy and selection of optimal number of features. The experimental results confirm that features identified by Principal Component Analysis lead to improved performance in terms of classification percentage with 96% than Genetic algorithm with 94%. Copyright © 2015 Elsevier B.V. All rights reserved.

Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things

PubMed Central

Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

2015-01-01

With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified. PMID:26393617

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

1991-01-01

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

A spiking neural network based on the basal ganglia functional anatomy.

PubMed

Baladron, Javier; Hamker, Fred H

2015-07-01

We introduce a spiking neural network of the basal ganglia capable of learning stimulus-action associations. We model learning in the three major basal ganglia pathways, direct, indirect and hyperdirect, by spike time dependent learning and considering the amount of dopamine available (reward). Moreover, we allow to learn a cortico-thalamic pathway that bypasses the basal ganglia. As a result the system develops new functionalities for the different basal ganglia pathways: The direct pathway selects actions by disinhibiting the thalamus, the hyperdirect one suppresses alternatives and the indirect pathway learns to inhibit common mistakes. Numerical experiments show that the system is capable of learning sets of either deterministic or stochastic rules. Copyright © 2015 Elsevier Ltd. All rights reserved.

Possible mechanisms of dose-dependent cough suppressive effect of Althaea officinalis rhamnogalacturonan in guinea pigs test system.

PubMed

Sutovská, M; Nosálová, G; Sutovský, J; Franová, S; Prisenznáková, L; Capek, P

2009-07-01

The rhamnogalacturonan, isolated from the roots of medicinal plant Althaea officinalis L., showed various biological effects on the citric acid-induced cough reflex and reactivity of airways smooth muscle in vitro and in vivo conditions. It possessed dose-dependent cough suppression effect comparable with opioid agonist codeine. However, reactivity of the airways smooth muscle, measured in vitro as well as in vivo conditions was not significantly affected by rhamnogalacturonan and thus bronchodilatory activity did not participate in the cough suppression effect of polysaccharide tested. Moreover, the cough suppression effect of the polymer was not significantly modified by pretreatment of K(+)(ATP) ion channels with selective antagonist and therefore activation of this type of ion channels is not involved in the mechanism of rhamnogalacturonan cough suppressive ability. On the contrary, pretreatment of animals with selective 5-HT(2) receptors antagonist significantly decreased rhamnogalacturonan antitussive efficacy. From this point of view it seems that the cough suppression effect of the polymer is associated with the serotonergic 5-HT(2) receptor's function.

Oxotremorine suppresses thalamocortical oscillations via thalamic muscarinic acetylcholine receptors.

PubMed

Puoliväli, J; Jäkälä, P; Koivisto, E; Riekkinen, P

1998-12-01

We investigated whether the local intrathalamic infusion of a muscarinic acetylcholine receptor agonist (oxotremorine) at either the reticular nucleus of thalamus (NRT) or the ventroposteromedial nucleus of thalamus (VPM) suppresses thalamocortically generated neocortical high-voltage spindles (HVSs). In addition, we studied whether the intracerebroventricular (ICV) infusion of a selective muscarinic M2 acetylcholine receptor antagonist (methoctramine) could block the suppression of HVSs induced by either systemic (IP) administration of an anticholinesterase drug [tetrahydroaminoacridine (THA)] or ICV infusion of oxotremorine in rats. Intrathalamic administration of oxotremorine at 3 and 15 microg in the NRT, and at 15 microg in the VPM suppressed HVSs. ICV oxotremorine at 30 and 100 microg and IP THA at 3 mg/kg decreased HVSs. ICV methoctramine at 100 microg increased HVSs and completely blocked the decrease in HVSs produced by oxotremorine 100 microg and THA 3 mg/kg. The results suggest that activation of muscarinic M2 acetylcholine receptors in thalamic nuclei (NRT and VPM) can suppress thalamocortical oscillations and that ICV or systemically administered drugs that activate either directly (oxotremorine and methoctramine) or indirectly (THA) the muscarinic M2 acetylcholine receptors may modulate neocortical HVSs via the thalamus.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficacy of microorganisms selected from compost to control soil-borne pathogens.

PubMed

Pugliese, M; Gullino, M L; Garibaldi, A

2010-01-01

Suppression of soil-borne plant pathogens with compost has been widely studied. Compost has been found to be suppressive against several soil-borne pathogens in various cropping systems. However, an increase of some diseases due to compost usage has also been observed, since compost is a product that varies considerably in chemical, physical and biotic composition, and, consequently, also in ability to suppress soil borne diseases. New opportunities in disease management can be obtained by the selection of antagonists from suppressive composts. The objective of the present work was to isolate microorganisms from a suppressive compost and to test them for their activity against soil-borne pathogens. A compost from green wastes, organic domestic wastes and urban sludge's that showed a good suppressive activity in previous trials was used as source of microorganisms. Serial diluted suspensions of compost samples were plated on five different media: selective for Fusarium sp., selective for Trichoderma sp., selective for oomycetes, potato dextrose agar (PDA) for isolation of fungi, lysogeny broth (LB) for isolation of bacteria. In total, 101 colonies were isolated from plates and tested under laboratory conditions on tomato seedlings growing on perlite medium in Petri plates infected with Fusarium oxysporum f.sp. radicis-lycopersici and compared to a commercial antagonist (Streptomyces griserovidis, Mycostop, Bioplanet). Among them, 28 showed a significant disease reduction and were assessed under greenhouse condition on three pathosystems: Fusarium oxysporum f.sp. basilica/basil, Phytophthora nicotianae/tomato and Rhizoctonia solani/bean. Fusarium spp. selected from compost generally showed a good disease control against Fusarium wilts, while only bacteria significantly controlled P. nicotianae on tomato under greenhouse conditions. None of the microorganisms was able to control the three soil-borne pathogens together, in particular Rhizoctonia solani. Results

Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content

PubMed Central

Kling, Teresia; Johansson, Patrik; Sanchez, José; Marinescu, Voichita D.; Jörnsten, Rebecka; Nelander, Sven

2015-01-01

Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets. PMID:25953855

Efficacy of MBA: On the Role of Network Effects in Influencing the Selection of Elective Courses

ERIC Educational Resources Information Center

Roy, Vivek; Parsad, Chandan

2018-01-01

Purpose: The purpose of this paper is to outline the importance of social network effects in influencing the elective (courses) selection among masters of business administration (MBA) students and its role in influencing the efficacy of MBA. As such, given the enormous time and investment required for students to pursue an MBA and the role of…

Communication Policies in Knowledge Networks

NASA Astrophysics Data System (ADS)

Ioannidis, Evangelos; Varsakelis, Nikos; Antoniou, Ioannis

2018-02-01

Faster knowledge attainment within organizations leads to improved innovation, and therefore competitive advantage. Interventions on the organizational network may be risky or costly or time-demanding. We investigate several communication policies in knowledge networks, which reduce the knowledge attainment time without interventions. We examine the resulting knowledge dynamics for real organizational networks, as well as for artificial networks. More specifically, we investigate the dependence of knowledge dynamics on: (1) the Selection Rule of agents for knowledge acquisition, and (2) the Order of implementation of "Selection" and "Filtering". Significant decrease of the knowledge attainment time (up to -74%) can be achieved by: (1) selecting agents of both high knowledge level and high knowledge transfer efficiency, and (2) implementing "Selection" after "Filtering" in contrast to the converse, implicitly assumed, conventional prioritization. The Non-Commutativity of "Selection" and "Filtering", reveals a Non-Boolean Logic of the Network Operations. The results demonstrate that significant improvement of knowledge dynamics can be achieved by implementing "fruitful" communication policies, by raising the awareness of agents, without any intervention on the network structure.

Nimesulide, a cyclooxygenase-2 selective inhibitor, suppresses obesity-related non-alcoholic fatty liver disease and hepatic insulin resistance through the regulation of peroxisome proliferator-activated receptor γ.

PubMed

Tsujimoto, Shunsuke; Kishina, Manabu; Koda, Masahiko; Yamamoto, Yasutaka; Tanaka, Kohei; Harada, Yusuke; Yoshida, Akio; Hisatome, Ichiro

2016-09-01

Cyclooxygenase (COX)-2 selective inhibitors suppress non-alcoholic fatty liver disease (NAFLD); however, the precise mechanism of action remains unknown. The aim of this study was to examine how the COX-2 selective inhibitor nimesulide suppresses NAFLD in a murine model of high-fat diet (HFD)‑induced obesity. Mice were fed either a normal chow diet (NC), an HFD, or HFD plus nimesulide (HFD-nime) for 12 weeks. Body weight, hepatic COX-2 mRNA expression and triglyceride accumulation were significantly increased in the HFD group. Triglyceride accumulation was suppressed in the HFD-nime group. The mRNA expression of hepatic peroxisome proliferator-activated receptor γ (PPARγ) and the natural PPARγ agonist 15-deoxy-Δ12,14-prostaglandin J2 (15d‑PGJ2) were significantly increased in the HFD group and significantly suppressed in the HFD-nime group. Glucose metabolism was impaired in the HFD group compared with the NC group, and it was significantly improved in the HFD-nime group. In addition, the plasma insulin levels in the HFD group were increased compared with those in the NC group, and were decreased in the HFD-nime group. These results indicate that HFD-induced NAFLD is mediated by the increased hepatic expression of COX-2. We suggest that the production of 15d-PGJ2, which is mediated by COX-2, induces NAFLD and hepatic insulin resistance by activating PPARγ. Furthermore, the mRNA expression of tissue inhibitor of metalloproteinases-1 (TIMP‑1), procollagen-1 and monocyte chemoattractant protein-1 (MCP-1), as well as the number of F4/80-positive hepatic (Kupffer) cells, were significantly increased in the HFD group compared with the NC group, and they were reduced by nimesulide. In conclusion, COX-2 may emerge as a molecular target for preventing the development of NAFLD and insulin resistance in diet-related obesity.

Deterministic delivery of remote entanglement on a quantum network.

PubMed

Humphreys, Peter C; Kalb, Norbert; Morits, Jaco P J; Schouten, Raymond N; Vermeulen, Raymond F L; Twitchen, Daniel J; Markham, Matthew; Hanson, Ronald

2018-06-01

Large-scale quantum networks promise to enable secure communication, distributed quantum computing, enhanced sensing and fundamental tests of quantum mechanics through the distribution of entanglement across nodes 1-7 . Moving beyond current two-node networks 8-13 requires the rate of entanglement generation between nodes to exceed the decoherence (loss) rate of the entanglement. If this criterion is met, intrinsically probabilistic entangling protocols can be used to provide deterministic remote entanglement at pre-specified times. Here we demonstrate this using diamond spin qubit nodes separated by two metres. We realize a fully heralded single-photon entanglement protocol that achieves entangling rates of up to 39 hertz, three orders of magnitude higher than previously demonstrated two-photon protocols on this platform 14 . At the same time, we suppress the decoherence rate of remote-entangled states to five hertz through dynamical decoupling. By combining these results with efficient charge-state control and mitigation of spectral diffusion, we deterministically deliver a fresh remote state with an average entanglement fidelity of more than 0.5 at every clock cycle of about 100 milliseconds without any pre- or post-selection. These results demonstrate a key building block for extended quantum networks and open the door to entanglement distribution across multiple remote nodes.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses.

PubMed

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-08-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses

PubMed Central

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-01-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure. PMID:26291697

Social Mimicry Enhances Mu-Suppression During Action Observation.

PubMed

Hogeveen, Jeremy; Chartrand, Tanya L; Obhi, Sukhvinder S

2015-08-01

During social interactions, there is a tendency for people to mimic the gestures and mannerisms of others, which increases liking and rapport. Psychologists have extensively studied the antecedents and consequences of mimicry at the social level, but the neural basis of this behavior remains unclear. Many researchers have speculated that mimicry is related to activity in the human mirror system (HMS), a network of parietofrontal regions that are involved in both action execution and observation. However, activity of the HMS during reciprocal social interactions involving mimicry has not been demonstrated. Here, we took an electroencephalographic (EEG) index of mirror activity-mu-suppression during action observation-in a pretest/post-test design with 1 of 3 intervening treatments: 1) social interaction in which the participant was mimicked, 2) social interaction without mimicry, or 3) an innocuous computer task, not involving another human agent. The change in mu-suppression from pre- to post-test varied as a function of the intervening treatment, with participants who had been mimicked showing an increase in mu-suppression during the post-treatment action observation session. We propose that this specific modulation of HMS activity as a function of mimicry constitutes the first direct evidence for mirror system involvement in real social mimicry. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Jet noise suppression

NASA Astrophysics Data System (ADS)

Gliebe, P. R.; Brausch, J. F.; Majjigi, R. K.; Lee, R.

1991-08-01

The objectives of this chapter are to review and summarize the jet noise suppression technology, to provide a physical and theoretical model to explain the measured jet noise suppression characteristics of different concepts, and to provide a set of guidelines for evolving jet noise suppression designs. The underlying principle for all jet noise suppression devices is to enhance rapid mixing (i.e., diffusion) of the jet plume by geometric and aerothermodynamic means. In the case of supersonic jets, the shock-cell broadband noise reduction is effectively accomplished by the elimination or mitigation of the shock-cell structure. So far, the diffusion concepts have predominantly concentrated on jet momentum and energy (kinetic and thermal) diffusion, in that order, and have yielded better noise reduction than the simple conical nozzles. A critical technology issue that needs resolution is the effect of flight on the noise suppression potential of mechanical suppressor nozzles. A more thorough investigation of this mechanism is necessary for the successful development and design of an acceptable noise suppression device for future high-speed civil transports.

Bayesian model selection applied to artificial neural networks used for water resources modeling

NASA Astrophysics Data System (ADS)

Kingston, Greer B.; Maier, Holger R.; Lambert, Martin F.

2008-04-01

Artificial neural networks (ANNs) have proven to be extremely valuable tools in the field of water resources engineering. However, one of the most difficult tasks in developing an ANN is determining the optimum level of complexity required to model a given problem, as there is no formal systematic model selection method. This paper presents a Bayesian model selection (BMS) method for ANNs that provides an objective approach for comparing models of varying complexity in order to select the most appropriate ANN structure. The approach uses Markov Chain Monte Carlo posterior simulations to estimate the evidence in favor of competing models and, in this study, three known methods for doing this are compared in terms of their suitability for being incorporated into the proposed BMS framework for ANNs. However, it is acknowledged that it can be particularly difficult to accurately estimate the evidence of ANN models. Therefore, the proposed BMS approach for ANNs incorporates a further check of the evidence results by inspecting the marginal posterior distributions of the hidden-to-output layer weights, which unambiguously indicate any redundancies in the hidden layer nodes. The fact that this check is available is one of the greatest advantages of the proposed approach over conventional model selection methods, which do not provide such a test and instead rely on the modeler's subjective choice of selection criterion. The advantages of a total Bayesian approach to ANN development, including training and model selection, are demonstrated on two synthetic and one real world water resources case study.

Efficiency of prompt quarantine measures on a susceptible-infected-removed model in networks.

PubMed

Hasegawa, Takehisa; Nemoto, Koji

2017-08-01

This study focuses on investigating the manner in which a prompt quarantine measure suppresses epidemics in networks. A simple and ideal quarantine measure is considered in which an individual is detected with a probability immediately after it becomes infected and the detected one and its neighbors are promptly isolated. The efficiency of this quarantine in suppressing a susceptible-infected-removed (SIR) model is tested in random graphs and uncorrelated scale-free networks. Monte Carlo simulations are used to show that the prompt quarantine measure outperforms random and acquaintance preventive vaccination schemes in terms of reducing the number of infected individuals. The epidemic threshold for the SIR model is analytically derived under the quarantine measure, and the theoretical findings indicate that prompt executions of quarantines are highly effective in containing epidemics. Even if infected individuals are detected with a very low probability, the SIR model under a prompt quarantine measure has finite epidemic thresholds in fat-tailed scale-free networks in which an infected individual can always cause an outbreak of a finite relative size without any measure. The numerical simulations also demonstrate that the present quarantine measure is effective in suppressing epidemics in real networks.

Efficiency of prompt quarantine measures on a susceptible-infected-removed model in networks

NASA Astrophysics Data System (ADS)

Hasegawa, Takehisa; Nemoto, Koji

2017-08-01

This study focuses on investigating the manner in which a prompt quarantine measure suppresses epidemics in networks. A simple and ideal quarantine measure is considered in which an individual is detected with a probability immediately after it becomes infected and the detected one and its neighbors are promptly isolated. The efficiency of this quarantine in suppressing a susceptible-infected-removed (SIR) model is tested in random graphs and uncorrelated scale-free networks. Monte Carlo simulations are used to show that the prompt quarantine measure outperforms random and acquaintance preventive vaccination schemes in terms of reducing the number of infected individuals. The epidemic threshold for the SIR model is analytically derived under the quarantine measure, and the theoretical findings indicate that prompt executions of quarantines are highly effective in containing epidemics. Even if infected individuals are detected with a very low probability, the SIR model under a prompt quarantine measure has finite epidemic thresholds in fat-tailed scale-free networks in which an infected individual can always cause an outbreak of a finite relative size without any measure. The numerical simulations also demonstrate that the present quarantine measure is effective in suppressing epidemics in real networks.

Selective Activation of Sphingosine 1-Phosphate Receptors 1 and 3 Promotes Local Microvascular Network Growth

PubMed Central

Sefcik, Lauren S.; Petrie Aronin, Caren E.; Awojoodu, Anthony O.; Shin, Soo J.; Mac Gabhann, Feilim; MacDonald, Timothy L.; Wamhoff, Brian R.; Lynch, Kevin R.; Peirce, Shayn M.

2011-01-01

Proper spatial and temporal regulation of microvascular remodeling is critical to the formation of functional vascular networks, spanning the various arterial, venous, capillary, and collateral vessel systems. Recently, our group has demonstrated that sustained release of sphingosine 1-phosphate (S1P) from biodegradable polymers promotes microvascular network growth and arteriolar expansion. In this study, we employed S1P receptor-specific compounds to activate and antagonize different combinations of S1P receptors to elucidate those receptors most critical for promotion of pharmacologically induced microvascular network growth. We show that S1P1 and S1P3 receptors act synergistically to enhance functional network formation via increased functional length density, arteriolar diameter expansion, and increased vascular branching in the dorsal skinfold window chamber model. FTY720, a potent activator of S1P1 and S1P3, promoted a 107% and 153% increase in length density 3 and 7 days after implantation, respectively. It also increased arteriolar diameters by 60% and 85% 3 and 7 days after implantation. FTY720-stimulated branching in venules significantly more than unloaded poly(D, L-lactic-co-glycolic acid). When implanted on the mouse spinotrapezius muscle, FTY720 stimulated an arteriogenic response characterized by increased tortuosity and collateralization of branching microvascular networks. Our results demonstrate the effectiveness of S1P1 and S1P3 receptor-selective agonists (such as FTY720) in promoting microvascular growth for tissue engineering applications. PMID:20874260

Learned suppression for multiple distractors in visual search.

PubMed

Won, Bo-Yeong; Geng, Joy J

2018-05-07

Visual search for a target object occurs rapidly if there were no distractors to compete for attention, but this rarely happens in real-world environments. Distractors are almost always present and must be suppressed for target selection to succeed. Previous research suggests that one way this occurs is through the creation of a stimulus-specific distractor template. However, it remains unknown how information within such templates scale up with multiple distractors. Here we investigated the informational content of distractor templates created from repeated exposures to multiple distractors. We investigated this question using a visual search task in which participants searched for a gray square among colored squares. During "training," participants always saw the same set of colored distractors. During "testing," new distractor sets were interleaved with the trained distractors. The critical manipulation in each study was the distance (in color space) of the new test distractors from the trained distractors. We hypothesized that the pattern of distractor interference during testing would reveal the tuning of the suppression template: RTs should be commensurate with the degree to which distractor colors are encoded within the suppression template. Results from four experiments converged on the notion that the distractor template includes information about specific color values, but has broad "tuning," allowing suppression to generalize to new distractors. These results suggest that distractor templates, unlike target templates, encode multiple features and have broad representations, which have the advantage of generalizing suppression more easily to other potential distractors. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Selective attention modulates neural substrates of repetition priming and "implicit" visual memory: suppressions and enhancements revealed by FMRI.

PubMed

Vuilleumier, Patrik; Schwartz, Sophie; Duhoux, Stéphanie; Dolan, Raymond J; Driver, Jon

2005-08-01

Attention can enhance processing for relevant information and suppress this for ignored stimuli. However, some residual processing may still arise without attention. Here we presented overlapping outline objects at study, with subjects attending to those in one color but not the other. Attended objects were subsequently recognized on a surprise memory test, whereas there was complete amnesia for ignored items on such direct explicit testing; yet reliable behavioral priming effects were found on indirect testing. Event-related fMRI examined neural responses to previously attended or ignored objects, now shown alone in the same or mirror-reversed orientation as before, intermixed with new items. Repetition-related decreases in fMRI responses for objects previously attended and repeated in the same orientation were found in the right posterior fusiform, lateral occipital, and left inferior frontal cortex. More anterior fusiform regions also showed some repetition decreases for ignored objects, irrespective of orientation. View-specific repetition decreases were found in the striate cortex, particularly for previously attended items. In addition, previously ignored objects produced some fMRI response increases in the bilateral lingual gyri, relative to new objects. Selective attention at exposure can thus produce several distinct long-term effects on processing of stimuli repeated later, with neural response suppression stronger for previously attended objects, and some response enhancement for previously ignored objects, with these effects arising in different brain areas. Although repetition decreases may relate to positive priming phenomena, the repetition increases for ignored objects shown here for the first time might relate to processes that can produce "negative priming" in some behavioral studies. These results reveal quantitative and qualitative differences between neural substrates of long-term repetition effects for attended versus unattended objects.

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Outage Analysis of Dual-hop Cognitive Networks with Relay Selection over Nakagami-m Fading Environment

NASA Astrophysics Data System (ADS)

Zhang, Zongsheng; Pi, Xurong

2014-09-01

In this paper, we investigate the outage performance of decode-and-forward cognitive relay networks for Nakagami-m fading channels, with considering both best relay selection and interference constraints. Focusing on the relay selection and making use of the underlay cognitive approach, an exact closed-form outage probability expression is derived in an independent, non-identical distributed Nakagami-m environment. The closed-form outage probability provides an efficient means to evaluate the effects of the maximum allowable interference power, number of cognitive relays, and channel conditions between the primary user and cognitive users. Finally, we present numerical results to validate the theory analysis. Moreover, from the simulation results, we obtain that the system can obtain the full diversity.

Joint Transmit Antenna Selection and Power Allocation for ISDF Relaying Mobile-to-Mobile Sensor Networks

PubMed Central

Xu, Lingwei; Zhang, Hao; Gulliver, T. Aaron

2016-01-01

The outage probability (OP) performance of multiple-relay incremental-selective decode-and-forward (ISDF) relaying mobile-to-mobile (M2M) sensor networks with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated. Exact closed-form OP expressions for both optimal and suboptimal TAS schemes are derived. The power allocation problem is formulated to determine the optimal division of transmit power between the broadcast and relay phases. The OP performance under different conditions is evaluated via numerical simulation to verify the analysis. These results show that the optimal TAS scheme has better OP performance than the suboptimal scheme. Further, the power allocation parameter has a significant influence on the OP performance. PMID:26907282

Norepinephrine ignites local hotspots of neuronal excitation: How arousal amplifies selectivity in perception and memory.

PubMed

Mather, Mara; Clewett, David; Sakaki, Michiko; Harley, Carolyn W

2016-01-01

Emotional arousal enhances perception and memory of high-priority information but impairs processing of other information. Here, we propose that, under arousal, local glutamate levels signal the current strength of a representation and interact with norepinephrine (NE) to enhance high priority representations and out-compete or suppress lower priority representations. In our "glutamate amplifies noradrenergic effects" (GANE) model, high glutamate at the site of prioritized representations increases local NE release from the locus coeruleus (LC) to generate "NE hotspots." At these NE hotspots, local glutamate and NE release are mutually enhancing and amplify activation of prioritized representations. In contrast, arousal-induced LC activity inhibits less active representations via two mechanisms: 1) Where there are hotspots, lateral inhibition is amplified; 2) Where no hotspots emerge, NE levels are only high enough to activate low-threshold inhibitory adrenoreceptors. Thus, LC activation promotes a few hotspots of excitation in the context of widespread suppression, enhancing high priority representations while suppressing the rest. Hotspots also help synchronize oscillations across neural ensembles transmitting high-priority information. Furthermore, brain structures that detect stimulus priority interact with phasic NE release to preferentially route such information through large-scale functional brain networks. A surge of NE before, during, or after encoding enhances synaptic plasticity at NE hotspots, triggering local protein synthesis processes that enhance selective memory consolidation. Together, these noradrenergic mechanisms promote selective attention and memory under arousal. GANE not only reconciles apparently contradictory findings in the emotion-cognition literature but also extends previous influential theories of LC neuromodulation by proposing specific mechanisms for how LC-NE activity increases neural gain.

A Comparison of Techniques for Camera Selection and Hand-Off in a Video Network

NASA Astrophysics Data System (ADS)

Li, Yiming; Bhanu, Bir

Video networks are becoming increasingly important for solving many real-world problems. Multiple video sensors require collaboration when performing various tasks. One of the most basic tasks is the tracking of objects, which requires mechanisms to select a camera for a certain object and hand-off this object from one camera to another so as to accomplish seamless tracking. In this chapter, we provide a comprehensive comparison of current and emerging camera selection and hand-off techniques. We consider geometry-, statistics-, and game theory-based approaches and provide both theoretical and experimental comparison using centralized and distributed computational models. We provide simulation and experimental results using real data for various scenarios of a large number of cameras and objects for in-depth understanding of strengths and weaknesses of these techniques.

Acoustic stimulation can induce a selective neural network response mediated by piezoelectric nanoparticles.

PubMed

Rojas, Camilo; Tedesco, Mariateresa; Massobrio, Paolo; Marino, Attilio; Ciofani, Gianni; Martinoia, Sergio; Raiteri, Roberto

2018-06-01

We aim to develop a novel non-invasive or minimally invasive method for neural stimulation to be applied in the study and treatment of brain (dys)functions and neurological disorders. We investigate the electrophysiological response of in vitro neuronal networks when subjected to low-intensity pulsed acoustic stimulation, mediated by piezoelectric nanoparticles adsorbed on the neuronal membrane. We show that the presence of piezoelectric barium titanate nanoparticles induces, in a reproducible way, an increase in network activity when excited by stationary ultrasound waves in the MHz regime. Such a response can be fully recovered when switching the ultrasound pulse off, depending on the generated pressure field amplitude, whilst it is insensitive to the duration of the ultrasound pulse in the range 0.5 s-1.5 s. We demonstrate that the presence of piezoelectric nanoparticles is necessary, and when applying the same acoustic stimulation to neuronal cultures without nanoparticles or with non-piezoelectric nanoparticles with the same size distribution, no network response is observed. We believe that our results open up an extremely interesting approach when coupled with suitable functionalization strategies of the nanoparticles in order to address specific neurons and/or brain areas and applied in vivo, thus enabling remote, non-invasive, and highly selective modulation of the activity of neuronal subpopulations of the central nervous system of mammalians.

Acoustic stimulation can induce a selective neural network response mediated by piezoelectric nanoparticles

NASA Astrophysics Data System (ADS)

Rojas, Camilo; Tedesco, Mariateresa; Massobrio, Paolo; Marino, Attilio; Ciofani, Gianni; Martinoia, Sergio; Raiteri, Roberto

2018-06-01

Objective. We aim to develop a novel non-invasive or minimally invasive method for neural stimulation to be applied in the study and treatment of brain (dys)functions and neurological disorders. Approach. We investigate the electrophysiological response of in vitro neuronal networks when subjected to low-intensity pulsed acoustic stimulation, mediated by piezoelectric nanoparticles adsorbed on the neuronal membrane. Main results. We show that the presence of piezoelectric barium titanate nanoparticles induces, in a reproducible way, an increase in network activity when excited by stationary ultrasound waves in the MHz regime. Such a response can be fully recovered when switching the ultrasound pulse off, depending on the generated pressure field amplitude, whilst it is insensitive to the duration of the ultrasound pulse in the range 0.5 s–1.5 s. We demonstrate that the presence of piezoelectric nanoparticles is necessary, and when applying the same acoustic stimulation to neuronal cultures without nanoparticles or with non-piezoelectric nanoparticles with the same size distribution, no network response is observed. Significance. We believe that our results open up an extremely interesting approach when coupled with suitable functionalization strategies of the nanoparticles in order to address specific neurons and/or brain areas and applied in vivo, thus enabling remote, non-invasive, and highly selective modulation of the activity of neuronal subpopulations of the central nervous system of mammalians.

Bio-Inspired Networking — Self-Organizing Networked Embedded Systems

NASA Astrophysics Data System (ADS)

Dressler, Falko

The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many research domains. In this article, we study the applicability of biological mechanisms and techniques in the domain of communications. In particular, we study the behavior and the challenges in networked embedded systems that are meant to self-organize in large groups of nodes. Application examples include wireless sensor networks and sensor/actuator networks. Based on a review of the needs and requirements in such networks, we study selected bio-inspired networking approaches that claim to outperform other methods in specific domains. We study mechanisms in swarm intelligence, the artificial immune system, and approaches based on investigations on the cellular signaling pathways. As a major conclusion, we derive that bio-inspired networking techniques do have advantages compared to engineering methods. Nevertheless, selection and employment must be done carefully to achieve the desired performance gains.

Evolutionarily conserved coupling of adaptive and excitable networks mediates eukaryotic chemotaxis

NASA Astrophysics Data System (ADS)

Tang, Ming; Wang, Mingjie; Shi, Changji; Iglesias, Pablo A.; Devreotes, Peter N.; Huang, Chuan-Hsiang

2014-10-01

Numerous models explain how cells sense and migrate towards shallow chemoattractant gradients. Studies show that an excitable signal transduction network acts as a pacemaker that controls the cytoskeleton to drive motility. Here we show that this network is required to link stimuli to actin polymerization and chemotactic motility and we distinguish the various models of chemotaxis. First, signalling activity is suppressed towards the low side in a gradient or following removal of uniform chemoattractant. Second, signalling activities display a rapid shut off and a slower adaptation during which responsiveness to subsequent test stimuli decline. Simulations of various models indicate that these properties require coupled adaptive and excitable networks. Adaptation involves a G-protein-independent inhibitor, as stimulation of cells lacking G-protein function suppresses basal activities. The salient features of the coupled networks were observed for different chemoattractants in Dictyostelium and in human neutrophils, suggesting an evolutionarily conserved mechanism for eukaryotic chemotaxis.

Inference of cancer-specific gene regulatory networks using soft computing rules.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Congruence analysis of geodetic networks - hypothesis tests versus model selection by information criteria

NASA Astrophysics Data System (ADS)

Lehmann, Rüdiger; Lösler, Michael

2017-12-01

Geodetic deformation analysis can be interpreted as a model selection problem. The null model indicates that no deformation has occurred. It is opposed to a number of alternative models, which stipulate different deformation patterns. A common way to select the right model is the usage of a statistical hypothesis test. However, since we have to test a series of deformation patterns, this must be a multiple test. As an alternative solution for the test problem, we propose the p-value approach. Another approach arises from information theory. Here, the Akaike information criterion (AIC) or some alternative is used to select an appropriate model for a given set of observations. Both approaches are discussed and applied to two test scenarios: A synthetic levelling network and the Delft test data set. It is demonstrated that they work but behave differently, sometimes even producing different results. Hypothesis tests are well-established in geodesy, but may suffer from an unfavourable choice of the decision error rates. The multiple test also suffers from statistical dependencies between the test statistics, which are neglected. Both problems are overcome by applying information criterions like AIC.

Social Networks and the Diffusion of Adolescent Problem Behavior: Reliable Estimates of Selection and Influence from 6th through 9th Grade

PubMed Central

Osgood, D. Wayne; Feinberg, Mark E.; Ragan, Daniel T.

2015-01-01

Seeking to reduce problematic peer influence is a prominent theme of programs to prevent adolescent problem behavior. To support the refinement of this aspect of prevention programming, we examined peer influence and selection processes for three problem behaviors (delinquency, alcohol use, and smoking). We assessed not only the overall strengths of these peer processes, but also their consistency versus variability across settings. We used dynamic stochastic actor-based models to analyze five waves of friendship network data across sixth through ninth grades for a large sample of U.S. adolescents. Our sample included two successive grade cohorts of youth in 26 school districts participating in the PROSPER study, yielding 51 longitudinal social networks based on respondents’ friendship nominations. For all three self-reported antisocial behaviors, we found evidence of both peer influence and selection processes tied to antisocial behavior. There was little reliable variance in these processes across the networks, suggesting that the statistical imprecision of the peer influence and selection estimates in previous studies likely accounts for inconsistencies in results. Adolescent friendship networks play a strong role in shaping problem behavior, but problem behaviors also inform friendship choices. In addition to preferring friends with similar levels of problem behavior, adolescents tend to choose friends who engage in problem behaviors, thus creating broader diffusion. PMID:25943034

Lung nodule detection from CT scans using 3D convolutional neural networks without candidate selection

NASA Astrophysics Data System (ADS)

Jenuwine, Natalia M.; Mahesh, Sunny N.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Early detection of lung nodules from CT scans is key to improving lung cancer treatment, but poses a significant challenge for radiologists due to the high throughput required of them. Computer-Aided Detection (CADe) systems aim to automatically detect these nodules with computer algorithms, thus improving diagnosis. These systems typically use a candidate selection step, which identifies all objects that resemble nodules, followed by a machine learning classifier which separates true nodules from false positives. We create a CADe system that uses a 3D convolutional neural network (CNN) to detect nodules in CT scans without a candidate selection step. Using data from the LIDC database, we train a 3D CNN to analyze subvolumes from anywhere within a CT scan and output the probability that each subvolume contains a nodule. Once trained, we apply our CNN to detect nodules from entire scans, by systematically dividing the scan into overlapping subvolumes which we input into the CNN to obtain the corresponding probabilities. By enabling our network to process an entire scan, we expect to streamline the detection process while maintaining its effectiveness. Our results imply that with continued training using an iterative training scheme, the one-step approach has the potential to be highly effective.

An Efficient Next Hop Selection Algorithm for Multi-Hop Body Area Networks

PubMed Central

Ayatollahitafti, Vahid; Ngadi, Md Asri; Mohamad Sharif, Johan bin; Abdullahi, Mohammed

2016-01-01

Body Area Networks (BANs) consist of various sensors which gather patient’s vital signs and deliver them to doctors. One of the most significant challenges faced, is the design of an energy-efficient next hop selection algorithm to satisfy Quality of Service (QoS) requirements for different healthcare applications. In this paper, a novel efficient next hop selection algorithm is proposed in multi-hop BANs. This algorithm uses the minimum hop count and a link cost function jointly in each node to choose the best next hop node. The link cost function includes the residual energy, free buffer size, and the link reliability of the neighboring nodes, which is used to balance the energy consumption and to satisfy QoS requirements in terms of end to end delay and reliability. Extensive simulation experiments were performed to evaluate the efficiency of the proposed algorithm using the NS-2 simulator. Simulation results show that our proposed algorithm provides significant improvement in terms of energy consumption, number of packets forwarded, end to end delay and packet delivery ratio compared to the existing routing protocol. PMID:26771586

ICA model order selection of task co-activation networks.

PubMed

Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

ICA model order selection of task co-activation networks

PubMed Central

Ray, Kimberly L.; McKay, D. Reese; Fox, Peter M.; Riedel, Michael C.; Uecker, Angela M.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.; Laird, Angela R.

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders. PMID:24339802

TGF-β Tumor Suppression Through A Lethal EMT

PubMed Central

David, Charles J.; Huang, Yun-Han; Chen, Mo; Su, Jie; Zou, Yilong; Bardeesy, Nabeel; Iacobuzio-Donahue, Christine A.; Massagué, Joan

2016-01-01

TGF-β signaling can be pro-tumorigenic or tumor suppressive. We investigated this duality in pancreatic ductal adenocarcinoma (PDA), which, with other gastrointestinal cancers, exhibits frequent inactivation of the TGF-β mediator Smad4. We show that TGF-β induces an epithelial-mesenchymal transition (EMT), generally considered a pro-tumorigenic event. However, in TGF-β sensitive PDA cells, EMT becomes lethal by converting TGF-β-induced Sox4 from an enforcer of tumorigenesis into a promoter of apoptosis. This is the result of an EMT-linked remodeling of the cellular transcription factor landscape, including the repression of the gastrointestinal lineage-master regulator Klf5. Klf5 cooperates with Sox4 in oncogenesis and prevents Sox4-induced apoptosis. Smad4 is required for EMT but dispensable for Sox4 induction by TGF-β. TGF-β-induced Sox4 is thus geared to bolster progenitor identity, while simultaneous Smad4-dependent EMT strips Sox4 of an essential partner in oncogenesis. Our work demonstrates that TGF-β tumor suppression functions through an EMT-mediated disruption of a lineage-specific transcriptional network. PMID:26898331

Suppression of Bacterial Wilt and Fusarium Wilt by a Burkholderia nodosa Strain Isolated from Kalimantan Soils, Indonesia.

PubMed

Nion, Yanetri Asi; Toyota, Koki

2008-01-01

A trial was conducted to suppress bacterial wilt of tomato (BWT) caused by Ralstonia solanacearum using biocontrol agents (BCAs) isolated from soils in Kalimantan, Indonesia. Five isolates were selected from 270 isolates as better performing BCAs through screening four times using a pumice medium. The isolates selected were identified as Burkholderia nodosa, Burkholderia sacchari, Burkholderia pyrrocinia and Burkholderia terricola according to 16S rDNA sequences, fatty acid composition and carbon source utilization patterns. Among them, B. nodosa G5.2.rif1 had significant suppressive effects on Fusarium wilt of tomato (FWT) and spinach (FWS) as well as BWT. When B. nodosa G5.2rif1 was inoculated into a pumice medium in combination with sucrose, it showed even more stable disease suppression for BWT, but not for FWS. This suppression was considered to mainly occur through competition for nutrients. In two times greenhouse experiments for BWT using pots comparable in size to those used commercially, B. nodosa G5.2rif1 significantly suppressed the disease index by 33-79%, with no inhibitory effects on the growth, yield and quality of tomatoes.

Analysis of shot noise suppression for electron beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ratner, Daniel; Huang, Zhirong; Stupakov, Gennady

2011-06-24

Shot noise can affect the performance of free-electron lasers (FELs) by driving instabilities (e.g., the microbunching instability) or by competing with seeded density modulations. Recent papers have proposed suppressing shot noise to enhance FEL performance. In this paper we use a onedimensional (1D) model to calculate the noise amplification from an energy modulation (e.g., electron interactions from space charge or undulator radiation) followed by a dispersive section. We show that, for a broad class of interactions, selecting the correct dispersive strength suppresses shot noise across a wide range of frequencies. The final noise level depends on the beam’s energy spreadmore » and the properties of the interaction potential. As a result, we confirm and illustrate our analytical results with 1D simulations.« less

Analysis of Shot Noise Suppression for Electron Beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ratner, Daniel; /Stanford U., Appl. Phys. Dept.; Huang, Zhirong

2012-05-07

Shot noise can affect the performance of free-electron lasers (FELs) by driving instabilities (e.g., the microbunching instability) or by competing with seeded density modulations. Recent papers have proposed suppressing shot noise to enhance FEL performance. In this paper we use a one-dimensional (1D) model to calculate the noise amplification from an energy modulation (e.g., electron interactions from space charge or undulator radiation) followed by a dispersive section. We show that, for a broad class of interactions, selecting the correct dispersive strength suppresses shot noise across a wide range of frequencies. The final noise level depends on the beam's energy spreadmore » and the properties of the interaction potential. We confirm and illustrate our analytical results with 1D simulations.« less

Off-resonance suppression for multispectral MR imaging near metallic implants.

PubMed

den Harder, J Chiel; van Yperen, Gert H; Blume, Ulrike A; Bos, Clemens

2015-01-01

Metal artifact reduction in MRI within clinically feasible scan-times without through-plane aliasing. Existing metal artifact reduction techniques include view angle tilting (VAT), which resolves in-plane distortions, and multispectral imaging (MSI) techniques, such as slice encoding for metal artifact correction (SEMAC) and multi-acquisition with variable resonances image combination (MAVRIC), that further reduce image distortions, but significantly increase scan-time. Scan-time depends on anatomy size and anticipated total spectral content of the signal. Signals outside the anticipated spatial region may cause through-plane back-folding. Off-resonance suppression (ORS), using different gradient amplitudes for excitation and refocusing, is proposed to provide well-defined spatial-spectral selectivity in MSI to allow scan-time reduction and flexibility of scan-orientation. Comparisons of MSI techniques with and without ORS were made in phantom and volunteer experiments. Off-resonance suppressed SEMAC (ORS-SEMAC) and outer-region suppressed MAVRIC (ORS-MAVRIC) required limited through-plane phase encoding steps compared with original MSI. Whereas SEMAC (scan time: 5'46") and MAVRIC (4'12") suffered from through-plane aliasing, ORS-SEMAC and ORS-MAVRIC allowed alias-free imaging in the same scan-times. ORS can be used in MSI to limit the selected spatial-spectral region and contribute to metal artifact reduction in clinically feasible scan-times while avoiding slice aliasing. © 2014 Wiley Periodicals, Inc.

Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia.

PubMed

Whitfield-Gabrieli, Susan; Thermenos, Heidi W; Milanovic, Snezana; Tsuang, Ming T; Faraone, Stephen V; McCarley, Robert W; Shenton, Martha E; Green, Alan I; Nieto-Castanon, Alfonso; LaViolette, Peter; Wojcik, Joanne; Gabrieli, John D E; Seidman, Larry J

2009-01-27

We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness.

Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia

PubMed Central

Whitfield-Gabrieli, Susan; Thermenos, Heidi W.; Milanovic, Snezana; Tsuang, Ming T.; Faraone, Stephen V.; McCarley, Robert W.; Shenton, Martha E.; Green, Alan I.; Nieto-Castanon, Alfonso; LaViolette, Peter; Wojcik, Joanne; Gabrieli, John D. E.; Seidman, Larry J.

2009-01-01

We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness. PMID:19164577

Characterization of biocontrol bacterial strains isolated from a suppressiveness-induced soil after amendment with composted almond shells.

PubMed

Vida, Carmen; Cazorla, Francisco M; de Vicente, Antonio

The improvement in soil quality of avocado crops through organic amendments with composted almond shells has a positive effect on crop yield and plant health, and enhances soil suppressiveness against the phytopathogenic fungus Rosellinia necatrix. In previous studies, induced soil suppressiveness against this pathogen was related to stimulation of Gammaproteobacteria, especially some members of Pseudomonas spp. with biocontrol-related activities. In this work, we isolated bacteria from this suppressiveness-induced amended soil using a selective medium for Pseudomonas-like microorganisms. We characterized the obtained bacterial collection to aid in identification, including metabolic profiles, antagonistic responses, hybridization to biosynthetic genes of antifungal compounds, production of lytic exoenzymatic activities and plant growth-promotion-related traits, and sequenced and compared amplified 16S rDNA genes from representative bacteria. The final selection of representative strains mainly belonged to the genus Pseudomonas, but also included the genera Serratia and Stenotrophomonas. Their biocontrol-related activities were assayed using the experimental avocado model, and results showed that all selected strains protected the avocado roots against R. necatrix. This work confirmed the biocontrol activity of these Gammaproteobacteria-related members against R. necatrix following specific stimulation in a suppressiveness-induced soil after a composted almond shell application. Copyright © 2017 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model.

PubMed

Jung, Won-Mo; Park, In-Soo; Lee, Ye-Seul; Kim, Chang-Eop; Lee, Hyangsook; Hahm, Dae-Hyun; Park, Hi-Joon; Jang, Bo-Hyoung; Chae, Younbyoung

2018-04-12

Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acupuncture treatment in a clinical setting was explored. A total of 232 clinical records were collected using a Charting Language program. The relationship between symptom information and selected acupoints was trained using an artificial neural network (ANN). A total of 11 hidden nodes with the highest average precision score were selected through a tenfold cross-validation. Our ANN model could predict the selected acupoints based on symptom and disease information with an average precision score of 0.865 (precision, 0.911; recall, 0.811). This model is a useful tool for diagnostic classification or pattern recognition and for the prediction and modeling of acupuncture treatment based on clinical data obtained in a real-world setting. The relationship between symptoms and selected acupoints could be systematically characterized through knowledge discovery processes, such as pattern identification.

Selective Suppression of Endothelial Cell Apoptosis by the High Molecular Weight Form of Adiponectin

PubMed Central

Kobayashi, Hideki; Ouchi, Noriyuki; Kihara, Shinji; Walsh, Kenneth; Kumada, Masahiro; Abe, Yuki; Funahashi, Tohru; Matsuzawa, Yuji

2015-01-01

Adiponectin is an adipocyte-derived, antiatherogenic protein that is present in serum as three isoforms. Total adiponectin levels are decreased in obese or diabetic humans or animal models. This study was designed to elucidate the relative isoform distribution of adiponectin in human disease states and identify the active form of adiponectin toward vascular endothelial cells. The percentage of high molecular weight form (HMW) per total adiponectin was significantly lower in patients with coronary artery disease than control subjects, whereas the hexamer form was similar and the trimer form was significantly higher. During weight reduction in obese subjects, the HMW form increased and the trimer and hexamer forms decreased. Recombinant adiponectin dose-dependently suppressed apoptosis and caspase-3 activity in human umbilical vein endothelial cells (HUVECs). Transduction with dominant-negative AMP-activated protein kinase (AMPK) abolished the suppressive effect of adiponectin on HUVECs. Gel filtration chromatography was used to separate the adiponectin isoforms, and the antiapoptotic effect toward HUVECs was only observed with the HMW form. These data suggest that HMW adiponectin specifically confers the vascular-protective activities of this adipocytokine. PMID:14752031

Age-related patterns in social networks among European Americans and African Americans: implications for socioemotional selectivity across the life span.

PubMed

Fung, H H; Carstensen, L L; Lang, F R

2001-01-01

Socioemotional selectivity theory contends that as people become increasingly aware of limitations on future time, they are increasingly motivated to be more selective in their choice of social partners, favoring emotionally meaningful relationships over peripheral ones. The theory hypothesizes that because age is negatively associated with time left in life, the social networks of older people contain fewer peripheral social partners than those of their younger counterparts. This study tested the hypothesis among African Americans and European Americans, two ethnic groups whose social structural resources differ. Findings confirm the hypothesis. Across a wide age range (18 to 94 years old) and among both ethnic groups, older people report as many emotionally close social partners but fewer peripheral social partners in their networks as compared to their younger counterparts. Moreover, a greater percentage of very close social partners in social networks is related to lower levels of happiness among the young age group, but not among the older age groups. Implications of findings for adaptive social functioning across the life span are discussed.

Interactions between neural networks: a mechanism for tuning chaos and oscillations

PubMed Central

2007-01-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability. PMID:19003511

Interactions between neural networks: a mechanism for tuning chaos and oscillations.

PubMed

Wang, Lipo

2007-06-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila

PubMed Central

Seeds, Andrew M; Ravbar, Primoz; Chung, Phuong; Hampel, Stefanie; Midgley, Frank M; Mensh, Brett D; Simpson, Julie H

2014-01-01

Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown. We determined the organizational principles governing how dirty fruit flies groom their bodies with sequential movements. Using genetically targeted activation of neural subsets, we drove distinct motor programs that clean individual body parts. This enabled competition experiments revealing that the motor programs are organized into a suppression hierarchy; motor programs that occur first suppress those that occur later. Cleaning one body part reduces the sensory drive to its motor program, which relieves suppression of the next movement, allowing the grooming sequence to progress down the hierarchy. A model featuring independently evoked cleaning movements activated in parallel, but selected serially through hierarchical suppression, was successful in reproducing the grooming sequence. This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences. DOI: http://dx.doi.org/10.7554/eLife.02951.001 PMID:25139955

Cross-orientation suppression in human visual cortex

PubMed Central

Heeger, David J.

2011-01-01

Cross-orientation suppression was measured in human primary visual cortex (V1) to test the normalization model. Subjects viewed vertical target gratings (of varying contrasts) with or without a superimposed horizontal mask grating (fixed contrast). We used functional magnetic resonance imaging (fMRI) to measure the activity in each of several hypothetical channels (corresponding to subpopulations of neurons) with different orientation tunings and fit these orientation-selective responses with the normalization model. For the V1 channel maximally tuned to the target orientation, responses increased with target contrast but were suppressed when the horizontal mask was added, evident as a shift in the contrast gain of this channel's responses. For the channel maximally tuned to the mask orientation, a constant baseline response was evoked for all target contrasts when the mask was absent; responses decreased with increasing target contrast when the mask was present. The normalization model provided a good fit to the contrast-response functions with and without the mask. In a control experiment, the target and mask presentations were temporally interleaved, and we found no shift in contrast gain, i.e., no evidence for suppression. We conclude that the normalization model can explain cross-orientation suppression in human visual cortex. The approach adopted here can be applied broadly to infer, simultaneously, the responses of several subpopulations of neurons in the human brain that span particular stimulus or feature spaces, and characterize their interactions. In addition, it allows us to investigate how stimuli are represented by the inferred activity of entire neural populations. PMID:21775720

Phospholipase C mediated Suppression of Dark Noise Enables Single Photon Detection in Drosophila Photoreceptors

PubMed Central

Katz, Ben; Minke, Baruch

2012-01-01

Drosophila photoreceptor cells use the ubiquitous G-protein-mediated phospholipase C (PLC) cascade to achieve ultimate single photon sensitivity. This is manifested in the single photon responses (quantum bumps). In photoreceptor cells, dark activation of Gqα molecules occurs spontaneously and produces unitary dark events (dark bumps). A high rate of spontaneous Gqα activation and dark bump production potentially hampers single photon detection. We found that in wild type flies the in vivo rate of spontaneous Gqα activation is very high. Nevertheless, this high rate is not manifested in a substantially high rate of dark bumps. Therefore, it is unclear how phototransduction suppresses dark bump production, arising from spontaneous Gqα activation, while still maintaining high-fidelity representation of single photons. In this study we show that reduced PLC catalytic activity selectively suppressed production of dark bumps but not light-induced bumps. Manipulations of PLC activity using PLC mutant flies and Ca2+ modulations revealed that a critical level of PLC activity is required to induce bump production. The required minimal level of PLC activity, selectively suppressed random production of single Gqα-activated dark bumps despite a high rate of spontaneous Gqα activation. This minimal PLC activity level is reliably obtained by photon induced synchronized activation of several neighboring Gqα molecules activating several PLC molecules, but not by random activation of single Gqα molecules. We thus demonstrate how a G-protein-mediated transduction system, with PLC as its target, selectively suppresses its intrinsic noise while preserving reliable signaling. PMID:22357856

Nanoparticles Containing Curcumin Useful for Suppressing Macrophages In Vivo in Mice

PubMed Central

Amano, Chie; Minematsu, Hideki; Fujita, Kazuyo; Iwashita, Shinki; Adachi, Masaki; Igarashi, Koichi; Hinuma, Shuji

2015-01-01

To explore a novel method using liposomes to suppress macrophages, we screened food constituents through cell culture assays. Curcumin was one of the strongest compounds exhibiting suppressive effects on macrophages. We subsequently tried various methods to prepare liposomal curcumin, and eventually succeeded in preparing liposomes with sufficient amounts of curcumin to suppress macrophages by incorporating a complex of curcumin and bovine serum albumin. The diameter of the resultant nanoparticles, the liposomes containing curcumin, ranged from 60 to 100 nm. Flow cytometric analyses revealed that after intraperitoneal administration of the liposomes containing curcumin into mice, these were incorporated mainly by macrophages positive for F4/80, CD36, and CD11b antigens. Peritoneal cells prepared from mice injected in vivo with the liposomes containing curcumin apparently decreased interleukin-6-producing activities. Major changes in body weight and survival rates in the mice were not observed after administrating the liposomes containing curcumin. These results indicate that the liposomes containing curcumin are safe and useful for the selective suppression of macrophages in vivo in mice. PMID:26361331

BRAF inhibitors suppress apoptosis through off-target inhibition of JNK signaling

PubMed Central

Vin, Harina; Ojeda, Sandra S; Ching, Grace; Leung, Marco L; Chitsazzadeh, Vida; Dwyer, David W; Adelmann, Charles H; Restrepo, Monica; Richards, Kristen N; Stewart, Larissa R; Du, Lili; Ferguson, Scarlett B; Chakravarti, Deepavali; Ehrenreiter, Karin; Baccarini, Manuela; Ruggieri, Rosamaria; Curry, Jonathan L; Kim, Kevin B; Ciurea, Ana M; Duvic, Madeleine; Prieto, Victor G; Ullrich, Stephen E; Dalby, Kevin N; Flores, Elsa R; Tsai, Kenneth Y

2013-01-01

Vemurafenib and dabrafenib selectively inhibit the v-Raf murine sarcoma viral oncogene homolog B1 (BRAF) kinase, resulting in high response rates and increased survival in melanoma. Approximately 22% of individuals treated with vemurafenib develop cutaneous squamous cell carcinoma (cSCC) during therapy. The prevailing explanation for this is drug-induced paradoxical ERK activation, resulting in hyperproliferation. Here we show an unexpected and novel effect of vemurafenib/PLX4720 in suppressing apoptosis through the inhibition of multiple off-target kinases upstream of c-Jun N-terminal kinase (JNK), principally ZAK. JNK signaling is suppressed in multiple contexts, including in cSCC of vemurafenib-treated patients, as well as in mice. Expression of a mutant ZAK that cannot be inhibited reverses the suppression of JNK activation and apoptosis. Our results implicate suppression of JNK-dependent apoptosis as a significant, independent mechanism that cooperates with paradoxical ERK activation to induce cSCC, suggesting broad implications for understanding toxicities associated with BRAF inhibitors and for their use in combination therapies. DOI: http://dx.doi.org/10.7554/eLife.00969.001 PMID:24192036

Controlling extreme events on complex networks

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng

2014-08-01

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

Suppression of Hepatocellular Carcinoma by Inhibition of Overexpressed Ornithine Aminotransferase.

PubMed

Zigmond, Ehud; Ben Ya'acov, Ami; Lee, Hyunbeom; Lichtenstein, Yoav; Shalev, Zvi; Smith, Yoav; Zolotarov, Lidya; Ziv, Ehud; Kalman, Rony; Le, Hoang V; Lu, Hejun; Silverman, Richard B; Ilan, Yaron

2015-08-13

Hepatocellular carcinoma is the second leading cause of cancer death worldwide. DNA microarray analysis identified the ornithine aminotransferase (OAT) gene as a prominent gene overexpressed in hepatocellular carcinoma (HCC) from Psammomys obesus. In vitro studies demonstrated inactivation of OAT by gabaculine (1), a neurotoxic natural product, which suppressed in vitro proliferation of two HCC cell lines. Alpha-fetoprotein (AFP) secretion, a biomarker for HCC, was suppressed by gabaculine in both cell lines, but not significantly. Because of the active site similarity between GABA aminotransferase (GABA-AT) and OAT, a library of 24 GABA-AT inhibitors was screened to identify a more selective inhibitor of OAT. (1S,3S)-3-Amino-4-(hexafluoropropan-2-ylidene)cyclopentane-1-carboxylic acid (2) was found to be an inactivator of OAT that only weakly inhibits GABA-AT, l-aspartate aminotransferase, and l-alanine aminotransferase. In vitro administration of 2 significantly suppressed AFP secretion in both Hep3B and HepG2 HCC cells; in vivo, 2 significantly suppressed AFP serum levels and tumor growth in HCC-harboring mice, even at 0.1 mg/kg. Overexpression of the OAT gene in HCC and the ability to block the growth of HCC by OAT inhibitors support the role of OAT as a potential therapeutic target to inhibit HCC growth. This is the first demonstration of suppression of HCC by an OAT inactivator.

Interaction with Smad4 is indispensable for suppression of BMP signaling by c-Ski.

PubMed

Takeda, Masafumi; Mizuide, Masafumi; Oka, Masako; Watabe, Tetsuro; Inoue, Hirofumi; Suzuki, Hiroyuki; Fujita, Toshiro; Imamura, Takeshi; Miyazono, Kohei; Miyazawa, Keiji

2004-03-01

c-Ski is a transcriptional corepressor that interacts strongly with Smad2, Smad3, and Smad4 but only weakly with Smad1 and Smad5. Through binding to Smad proteins, c-Ski suppresses signaling of transforming growth factor-beta (TGF-beta) as well as bone morphogenetic proteins (BMPs). In the present study, we found that a mutant of c-Ski, termed c-Ski (ARPG) inhibited TGF-beta/activin signaling but not BMP signaling. Selectivity was confirmed in luciferase reporter assays and by determination of cellular responses in mammalian cells (BMP-induced osteoblastic differentiation of C2C12 cells and TGF-beta-induced epithelial-to-mesenchymal transdifferentiation of NMuMG cells) and Xenopus embryos. The ARPG mutant recruited histone deacetylases 1 (HDAC1) to the Smad3-Smad4 complex but not to the Smad1/5-Smad4 complex. c-Ski (ARPG) was unable to interact with Smad4, and the selective loss of suppression of BMP signaling by c-Ski (ARPG) was attributed to the lack of Smad4 binding. We also found that c-Ski interacted with Smad3 or Smad4 without disrupting Smad3-Smad4 heteromer formation. c-Ski (ARPG) would be useful for selectively suppressing TGF-beta/activin signaling.

Interaction with Smad4 Is Indispensable for Suppression of BMP Signaling by c-Ski

PubMed Central

Takeda, Masafumi; Mizuide, Masafumi; Oka, Masako; Watabe, Tetsuro; Inoue, Hirofumi; Suzuki, Hiroyuki; Fujita, Toshiro; Imamura, Takeshi; Miyazono, Kohei; Miyazawa, Keiji

2004-01-01

c-Ski is a transcriptional corepressor that interacts strongly with Smad2, Smad3, and Smad4 but only weakly with Smad1 and Smad5. Through binding to Smad proteins, c-Ski suppresses signaling of transforming growth factor-β (TGF-β) as well as bone morphogenetic proteins (BMPs). In the present study, we found that a mutant of c-Ski, termed c-Ski (ARPG) inhibited TGF-β/activin signaling but not BMP signaling. Selectivity was confirmed in luciferase reporter assays and by determination of cellular responses in mammalian cells (BMP-induced osteoblastic differentiation of C2C12 cells and TGF-β–induced epithelial-to-mesenchymal transdifferentiation of NMuMG cells) and Xenopus embryos. The ARPG mutant recruited histone deacetylases 1 (HDAC1) to the Smad3-Smad4 complex but not to the Smad1/5-Smad4 complex. c-Ski (ARPG) was unable to interact with Smad4, and the selective loss of suppression of BMP signaling by c-Ski (ARPG) was attributed to the lack of Smad4 binding. We also found that c-Ski interacted with Smad3 or Smad4 without disrupting Smad3-Smad4 heteromer formation. c-Ski (ARPG) would be useful for selectively suppressing TGF-β/activin signaling. PMID:14699069