Temporal Delay Research Articles

Assessment of early anthracycline-induced cardiotoxicity using segmental strain of cardiac magnetic resonance compared with global strain and functional parameters: an animal study.

The identification of anthracycline-induced cardiotoxicity holds significant importance in guiding subsequent treatment strategies, and recent research has demonstrated the efficacy of cardiac magnetic resonance (CMR) global strain analysis for its diagnosis. On the other hand, it is noteworthy that abnormal global myocardial strain may exhibit a temporal delay due to different cardiac movement in each segment of the left ventricle. To address this concern, this study aims to assess the diagnostic utility of CMR segmental strain analysis as an early detection method for cardiotoxicity. A serials of CMR scans were performed in 18 adult males New Zealand rabbits at baseline time (n=15), followed by scans at week 2 (n=15), week 4 (n=9), week 6 (n=6), and week 8 (n=5) after each week's anthracycline injection. Additionally, following each CMR scan, two to three rabbits were euthanized for pathological comparison. Cardiac functional parameters, global peak strain parameters, segmental peak strain parameters of the left ventricle, and the presence of myocardial cells damage were obtained. A mixed linear model was employed to obtain the earliest CMR diagnostic time. Receiver operating characteristic (ROC) analysis was performed to get the parameter threshold indicative of cardiotoxicity. The left ventricular ejection fraction decreased at week 8 (P=0.002). There were no statistical differences in global strain throughout the experiment period (P>0.05). Regarding segmental strain analysis, the peak segmental radial strain of the apical lateral wall exhibited a decrease starting from week 2 and reached its lowest point at this week (P=0.011). Conversely, peak segmental circumferential strain of the apical anterior wall showed an increase at week 2 and reached its peak at week 6 (P=0.026). The cutoff strain value by ROC analysis for these two walls were 46.285 and -16.920, with the respective areas under the curve (AUC) 0.593 [specificity =0.267, sensitivity =1.000, 95% confidence interval (CI): 0.471-0.777] and 0.764 (specificity =0.733, sensitivity =0.784, 95% CI: 0.511-0.816). Peak segmental longitudinal strain of the apical anterior and apical lateral wall showed relatively delayed changes, occurring in the 4th week (P=0.030 and P=0.048), the cutoff values for these strains were -12.415 and -15.960, with corresponding AUCs of 0.645 (specificity =0.333, sensitivity =0.955, 95% CI: 0.495-0.795) and 0.717 (specificity =0.433, sensitivity =0.955, 95% CI: 0.566-0.902), respectively. Notably, the myocardial injury was also observed at the corresponding periods. Based on experimental evidence, the peak segmental strain of the apical lateral and anterior wall, as determined by CMR, demonstrated an earlier detection of anthracycline-induced cardiotoxicity compared to peak global strain and cardiac function.

Managing Delays for Realtime Error Correction and Compensation of an Industrial Robot in an Open Network

The calibration of articulated arms presents a substantial challenge within the manufacturing domain, necessitating sophisticated calibration systems often reliant on the integration of costly metrology equipment for ensuring high precision. However, the logistical complexities and financial burden associated with deploying these devices across diverse systems hinder their widespread adoption. In response, Industry 4.0 emerges as a transformative paradigm by enabling the integration of manufacturing devices into networked environments, thereby providing access through cloud-based infrastructure. Nonetheless, this transition introduces a significant concern in the form of network-induced delays, which can significantly impact realtime calibration procedures. To address this pivotal challenge, the present study introduces an innovative framework that adeptly manages and mitigates network-induced delays. This framework leverages two key components: controller and optimiser, specifically the MPC (Model Predictive Controller) in conjunction with the Extended Kalman Filter (EKF), and a Predictor, characterised as the Dead Reckoning Model (DRM). Collectively, these methodologies are strategically integrated to address and ameliorate the temporal delays experienced during the calibration process. Significantly expanding upon antecedent investigations, the study transcends prior boundaries by implementing an advanced realtime error correction system across networked environments, with particular emphasis on the intricate management of delays originating from network traffic dynamics. The fundamental aim of this research extension is twofold: firstly, it aims to enhance realtime system performance on open networks, while concurrently achieving an impressive level of error correction precision at 0.02 mm. The employment of the proposed methodologies is anticipated to effectively surmount the intricacies and challenges associated with network-induced delays. Subsequently, this endeavour serves to catalyse accurate and efficient calibration procedures in the context of realtime manufacturing scenarios. This research significantly advances the landscape of error correction systems and lays a robust groundwork for the optimised utilisation of networked manufacturing devices within the dynamic realm of Industry 4.0 applications.

Ballistic dynamics of emergent soliton from Airy pulse in a medium with linear optical potential

We numerically investigate the propagation dynamics of Airy pulse in dispersive and nonlinear medium with time-dependent external optical potential. These time-dependent optical potentials are created by the co-propagating strong pump wave. In the presence of linear optical potential, soliton shedding from signal Airy pulse is observed, which demonstrates ballistic motion. However, emergent soliton can either be advanced or delayed depending upon the sign of the potential and the extent of temporal advancement or delay is directly proportional to the magnitude of the potential strength. In addition, the temporal shift of the emergent soliton is found to be dependent on the input pulse power. Moreover, we show ballistic motion of the emergent soliton by incorporating an initial linear phase as well as linear chirp (quadratic phase) parameters in the input Airy pulse. Furthermore, the effect of truncation factor on the propagation dynamics is explored. These results provide new insights on the manipulation of the signal Airy pulse dynamics in dispersive and nonlinear media.

Photoacoustic real-time monitoring of UV laser ablation of aged varnish coatings on heritage objects

A novel, simple and non-invasive diagnostic methodology is presented herein, as an effective approach to monitor in real-time the UV laser-assisted thinning of aged varnished coatings from heritage objects, using the acoustic signals generated upon light interaction with matter. Detection of the photoacoustic (PA) signals is realized by means of a non-contact air-coupled ultrasonic transducer with a frequency response in the MHz regime. This proposed statistical approach utilizes the information the PA signals provide during the laser ablation process, embedded in their temporal delay and amplitude reduction during varnish removal. Based on the cross-correlation of the PA signals, this monitoring technique determines the critical laser pulse, responsible for complete varnish removal. The efficiency of our methodology has been examined on a series of aged varnish mock-ups on different substrates. The laser treated surfaces were further assessed using various techniques, in order to confirm the results of our PA monitoring strategy. Application of this technique is aimed at validating its potential and suitability in addressing different varnish cleaning challenges. Based on previous encouraging results on encrusted stonework, primary objective of this study is to establish the PA monitoring methodology as an essential, real-time monitoring tool for controlled laser ablation of aged varnish coatings from heritage surfaces (paintings, metallic objects, wall paintings etc.), ensuring their efficient removal while preserving the integrity of the objects. Implementation of the PA technique may pave the way for numerous applications as regards the reliable monitoring of removing unwanted layers from various surfaces of interest.

Electromagnetic characteristics of NI-REBCO coils according to contact surface conditions controlled by the oxidation state and roughness of the REBCO conductor

Although no-insulation (NI) rare-earth barium copper oxide (REBCO) coils offer technical advantages, such as high-energy density, mechanical strength, and self-stabilizing performance, sometimes their applications are limited owing to current leaks through turn-to-turns inside the coils, which are caused by their very low turn-to-turn contact resistance. This results in temporal magnetic field delays and limits their applicability in fields requiring fast response performance in magnetic field control. These shortcomings can be addressed by increasing the turn-to-turn contact resistance of the NI coils. A NI winding method with REBCO conductor variations of surface-oxidation and roughness was proposed in this study; this method improved the magnetic field response by reducing the temporal delays of the magnetic field via the suppression of the turn-to-turn bypass current. This was achieved by increasing the turn-to-turn contact resistance within the NI coils through adjustments to the oxidation and roughness of the surface of a copper stabilizer layer, which was coated on the outermost part of the REBCO conductor by electroplating to ensure electrical and mechanical protection. In this study, the steady- and transient-state characteristics of NI coils were experimentally analyzed according to changes in the oxidation and roughness levels of the surface of the REBCO conductor. To verify the effectiveness of the proposed winding approach, basic tests were conducted in a liquid nitrogen cooling environment by constructing different types of sample coils using REBCO conductors, which were thermally oxidized at different temperatures in a convection oven and scratched using sandpaper. Further, the decay time constant and the time delay of the center magnetic field in the sample coils were measured in sudden current discharging and current charging/discharging tests, respectively. In addition, overcurrent tests using currents exceeding the critical current were conducted to analyze the thermal stability of the sample coils. In conclusion, it was experimentally verified that the time delays of the NI coils were reduced as the surface oxidation and roughness of the REBCO conductor increased. Furthermore, when the oxidizing and scratching approaches were employed, the contact resistance values of the NI coils (3.48 µΩ·cm2), which were not subjected to any surface treatment, increased to 155.01 and 4.43 µΩ·cm2, which were oxidized at 230 °C and sanded using P400-grit sandpaper, respectively. For oxidizing approach, heat treat temperatures at 200 °C – 230 °C will be suitable for increasing the contact resistance of NI coils without inserting any resistive material, thus resulting in a enhancing the magnetic response performance of NI coils.

Stability of steady-state visual evoked potential contrast response functions.

Repetitive sensory stimulation has been shown to induce neuroplasticity in sensory cortical circuits, at least under certain conditions. We measured the plasticity-inducing effect of repetitive contrast-reversal-sweep steady-state visual-evoked potential (ssVEP) stimuli, hoping to employ the ssVEP's high signal-to-noise electrophysiological readout in the study of human visual cortical neuroplasticity. Steady-state VEP contrast-sweep responses were measured daily for 4 days (four 20-trial blocks per day, 20 participants). No significant neuroplastic changes in response amplitude were observed either across blocks or across days. Furthermore, response amplitudes were stable within-participant, with measured across-block and across-day coefficients of variation (CV = SD/mean) of 15-20 ± 2% and 22-25 ± 2%, respectively. Steady-state VEP response phase was also highly stable, suggesting that temporal processing delays in the visual system vary by at most 2-3 ms across blocks and days. While we fail to replicate visual stimulation-dependent cortical plasticity, we show that contrast-sweep steady-state VEPs provide a stable human neurophysiological measure well suited for repeated-measures longitudinal studies.

Spatial disparities and variation sources decomposition of energy poverty in China

Addressing energy poverty and promoting energy equity are crucial for China to eradicate poverty comprehensively and achieve shared prosperity. Through a combined dynamic evaluation approach to accurately measure the extent of energy poverty, this paper analyzes the staged time series, spatial distribution characteristics of energy poverty applies the Dagum Gini coefficient and variance decomposition to observe the imbalance characteristics of energy poverty and identify the sources of variation. The objective of this paper is to mitigate the influence of spatial disparities on coordinating efforts to eradicate energy poverty across different regions. Consequently, provides valuable insights for decision-making to effectively eradicate energy poverty and expedite the achievement of energy equity. The results indicate: The reduction process of energy poverty in China exhibit phased characteristics from 2000 to 2020, with significant variations in reduction levels among provinces. Different sources of energy poverty exhibits imbalanced spatial distribution and evolution. The overall disparity in energy poverty widens as the phases progress, with characteristic nodes experiencing a temporal delay of 2–3 years compared to the policy nodes. Inter-regional disparities are the primary spatial source of energy poverty differences, while energy use capacity is the main factor contributing to variation.

Edge detection using fast pixel based matching and contours mapping algorithms.

Current methods of edge identification were constrained by issues like lighting changes, position disparity, colour changes, and gesture variability, among others. The aforementioned modifications have a significant impact, especially on scaled factors like temporal delay, gradient data, effectiveness in noise, translation, and qualifying edge outlines. It is obvious that an image's borders hold the majority of the shape data. Reducing the amount of time it takes for image identification, increase gradient knowledge of the image, improving efficiency in high noise environments, and pinpointing the precise location of an image are some potential obstacles in recognizing edges. the boundaries of an image stronger and more apparent locate those borders in the image initially, sharpening it by removing any extraneous detail with the use of the proper filters, followed by enhancing the edge-containing areas. The processes involved in recognizing edges are filtering, boosting, recognizing, and localizing. Numerous approaches have been suggested for the previously outlined identification of edges procedures. Edge detection using Fast pixel-based matching and contours mappingmethods are used to overcome the aforementioned restrictions for better picture recognition. In this article, we are introducing the Fast Pixel based matching and contours mapping algorithms to compare the edges in reference and targeted frames using mask-propagation and non-local techniques. Our system resists significant item visual fluctuation as well as copes with obstructions because we incorporate input from both the first and prior frames Improvement in performance in proposed system is discussed in result section, evidences are tabulated and sketched. Mainly detection probabilities and detection time is remarkably reinforced Effective identification of such things were widely useful in fingerprint comparison, medical diagnostics, Smart Cities, production, Cyber Physical Systems, incorporating Artificial Intelligence, and license plate recognition are conceivable applications of this suggested work.

Time separating spatial memories does not influence their integration in humans.

Humans can navigate through similar environments-like grocery stores-by integrating across their memories to extract commonalities or by differentiating between each to find idiosyncratic locations. Here, we investigate one factor that might impact whether two related spatial memories are integrated or differentiated: Namely, the temporal delay between experiences. Rodents have been shown to integrate memories more often when they are formed within 6 hours of each other. To test if this effect influences how humans spontaneously integrate spatial memories, we had 131 participants search for rewards in two similar virtual environments. We separated these learning experiences by either 30 minutes, 3 hours, or 27 hours. Memory integration was assessed three days later. Participants were able to integrate and simultaneously differentiate related memories across experiences. However, neither memory integration nor differentiation was modulated by temporal delay, in contrast to previous work. We further showed that both the levels of initial memory reactivation during the second experience and memory generalization to novel environments were comparable across conditions. Moreover, perseveration toward the initial reward locations during the second experience was related positively to integration and negatively to differentiation-but again, these associations did not vary by delay. Our findings identify important boundary conditions on the translation of rodent memory mechanisms to humans, motivating more research to characterize how even fundamental memory mechanisms are conserved and diverge across species.

Input-to-state stability of stochastic Markovian jump genetic regulatory networks

The development of gene circuits in logic modules that start enormous output distributions with low signal-to-noise ratios is a difficult problem in engineering. As a result, the gene model depicts the transcription and translation of a single gene produced in the modification of noise in isolated logic modules. Our goal is to construct such networks with all types of connectivity. Further, the impacts of noise on further complex genetic networks have been investigated using stochastic gene models. Using this information as a foundation, our research investigates the input-to-state stability investigation for stochastic Markovian jump genetic regulatory networks with time-varying delay components. The goal of this article is to develop genetic networks with temporal delays, which are crucial for genetic regulation because slow biochemical processes like gene transcription and translation need time to occur. Additionally, the Markovian chain is essential for demonstrating how a system shifts from one mode to another with known transition probabilities. In the stochastic case, some complex systems with random disturbance will occur. Due to this significance the genetic regulatory network with stochastic case is applied to identify the complex behaviour among genes and proteins of the micro perspective. By establishing the Lyapunov functional with Ito’s and Dynkin’s formula, new stability conditions are derived and which is effectively solved by MATLAB toolbox. The efficiency of the suggested technique is demonstrated using a numerical example.

Fluctuations in alpha and beta power provide neural states favourable for contextually relevant anticipatory processes.

Cued sensory input occasionally fails to immediately ensue its respective trigger. Given that our environments are rich in sensory cues, we often end up processing other contextually relevant information in the meantime. The experimental design of the present study allowed us to investigate how such temporal delays and visual interferences may impact anticipatory processes. Thirty-four participants were trained to remember an individualised set of eight paired-up faces. These paired-up faces were presented pseudorandomly in sequences of unpaired face images. To keep participants engaged throughout the electroencephalography study, they were instructed to classify each face image, according to its sex, as fast as possible without compromising accuracy. We observed dissimilar modulations in alpha and beta power between the 6-s timeframe encompassing the onsets of predictive and expected images (temporal delay block) and the 6-s timeframe encompassing the predictive, interference and expected images (visual interference block). Furthermore, an expectation-facilitated reduction of the face-sensitive N170 component was only observed if an anticipated face image directly followed its corresponding predictive counterpart. This effect was no longer evident when the expected face was preceded by a distracting face image. Regardless of the block type, behavioural measures confirmed that anticipated faces were classified significantly faster and with fewer erroneous responses than faces not foretold by a predictive face. Collectively, these results demonstrate that whilst the brain continuously adjusts internal hierarchical generative models to account for temporal delays in stimulus onset and visual interferences, the higher levels, and subsequent predictions, fundamental for expectation-facilitated behaviours remain intact.

MediBERT: A Medical Chatbot Built Using KeyBERT, BioBERT and GPT-2

The emergence of chatbots over the last 50 years has been the primary consequence of the need of a virtual aid. Unlike their biological anthropomorphic counterpart in the form of fellow homo sapiens, chatbots have the ability to instantaneously present themselves at the user's need and convenience. Be it for something as benign as feeling the need of a friend to talk to, to a more dire case such as medical assistance, chatbots are unequivocally ubiquitous in their utility. This paper aims to develop one such chatbot that is capable of not only analyzing human text (and speech in the near future), but also refining the ability to assist them medically through the process of accumulating data from relevant datasets. Although Recurrent Neural Networks (RNNs) are often used to develop chatbots, the constant presence of the vanishing gradient issue brought about by backpropagation, coupled with the cumbersome process of sequentially parsing each word individually has led to the increased usage of Transformer Neural Networks (TNNs) instead, which parses entire sentences at once while simultaneously giving context to it via embeddings, leading to increased parallelization. Two variants of the TNN Bidirectional Encoder Representations from Transformers (BERT), namely KeyBERT and BioBERT, are used for tagging the keywords in each sentence and for contextual vectorization into Q/A pairs for matrix multiplication, respectively. A final layer of GPT-2 (Generative Pre-trained Transformer) is applied to fine-tune the results from the BioBERT into a form that is human readable. The outcome of such an attempt could potentially lessen the need for trips to the nearest physician, and the temporal delay and financial resources required to do so.

Immunization and Host Responses to MB-1, a Live Hatchery Vaccine against Infectious Bursal Disease.

MB-1 is an attenuated infectious bursal disease virus vaccine. Previously, we observed a temporal delay of vaccine virus replication in the bursae of chicks due to maternally derived antibodies (MDAs). The mechanism that allowed its survival despite MDA neutralization remained unclear. We hypothesized that after vaccination at 1 day of age (DOA), the MB-1 virus penetrates and resides in local macrophages that are then distributed to lymphoid organs. Furthermore, MB-1's ability to survive within macrophages ensures its survival during effective MDA protection. PCR analysis of lymphoid organs from chicks with MDA, vaccinated on 1 DOA, demonstrated that the MB-1 virus was identified at low levels solely in the spleen pre-14 days of age. Fourteen days after vaccination, the virus was identified using PCR in the bursa, with viral levels increasing with time. The possible delay in viral colonization of the bursa was attributed to the presence of anti-IBDV capsid VP2 maternal IgA and IgY in the bursa interstitium. These indicate that during the period of high MDA levels, a small but viable MB-1 viral reservoir was maintained in the spleen, which might have served to colonize the bursa after MDA levels declined. Thereafter, individual immunization of chicks against Gumboro disease was achieved.

Transcriptional and proteomic analysis of the innate immune response to microbial stimuli in a model invertebrate chordate.

Inflammatory response triggered by innate immunity can act to protect against microorganisms that behave as pathogens, with the aim to restore the homeostatic state between host and beneficial microbes. As a filter-feeder organism, the ascidian Ciona robusta is continuously exposed to external microbes that may be harmful under some conditions. In this work, we used transcriptional and proteomic approaches to investigate the inflammatory response induced by stimuli of bacterial (lipopolysaccharide -LPS- and diacylated lipopeptide - Pam2CSK4) and fungal (zymosan) origin, in Ciona juveniles at stage 4 of metamorphosis. We focused on receptors, co-interactors, transcription factors and cytokines belonging to the TLR and Dectin-1 pathways and on immune factors identified by homology approach (i.e. immunoglobulin (Ig) or C-type lectin domain containing molecules). While LPS did not induce a significant response in juvenile ascidians, Pam2CSK4 and zymosan exposure triggered the activation of specific inflammatory mechanisms. In particular, Pam2CSK4-induced inflammation was characterized by modulation of TLR and Dectin-1 pathway molecules, including receptors, transcription factors, and cytokines, while immune response to zymosan primarily involved C-type lectin receptors, co-interactors, Ig-containing molecules, and cytokines. A targeted proteomic analysis enabled to confirm transcriptional data, also highlighting a temporal delay between transcriptional induction and protein level changes. Finally, a protein-protein interaction network of Ciona immune molecules was rendered to provide a wide visualization and analysis platform of innate immunity. The in vivo inflammatory model described here reveals interconnections of innate immune pathways in specific responses to selected microbial stimuli. It also represents the starting point for studying ontogeny and regulation of inflammatory disorders in different physiological conditions.

No temporal decay of cognitive control in the congruency sequence effect.

Cognitive control theories describe the active maintenance of goal representations over temporal delays as central for adaptive behavior. Dynamic adaptations of goal representations are often measured as the congruency sequence effect (CSE), which describes a reduced congruency effect in trials following incongruent trials compared to congruent trials. Previous studies questioned active maintenance of CSEs and instead found that CSEs decrease rapidly over time (Duthoo et al., 2014; Egner et al., 2010). However, in these studies, CSEs can be attributed to both, control adaptations following conflict and binding effects due to repetition of stimulus (S) and response (R) features. In four experiments, we demonstrate that CSEs originating solely from control adaptions were not affected by temporal delays. Additional within-subject conditions partially replicated previous research showing a decrease in CSEs in task designs allowing for S-R binding effects and controlled for task complexity as a potential moderator. Together, results support theories which predict an active maintenance or retrieval of cognitive control. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Stereopsis from interocular temporal delay: disentangling the effects of target versus background luminance

Stereopsis from interocular temporal delay: disentangling the effects of target versus background luminance

Excitation and Inhibition Delays within a Feedforward Inhibitory Pathway Modulate Cerebellar Purkinje Cell Output in Mice.

The cerebellar cortex computes sensorimotor information from many brain areas through a feedforward inhibitory (FFI) microcircuit between the input stage, the granule cell (GC) layer, and the output stage, the Purkinje cells (PCs). Although in other brain areas FFI underlies a precise excitation versus inhibition temporal correlation, recent findings in the cerebellum highlighted more complex behaviors at GC-molecular layer interneuron (MLI)-PC pathway. To dissect the temporal organization of this cerebellar FFI pathway, we combined ex vivo patch-clamp recordings of PCs in male mice with a viral-based strategy to express Channelrhodopsin2 in a subset of mossy fibers (MFs), the major excitatory inputs to GCs. We show that although light-mediated MF activation elicited pairs of excitatory and inhibitory postsynaptic currents in PCs, excitation (E) from GCs and inhibition (I) from MLIs reached PCs with a wide range of different temporal delays. However, when GCs were directly stimulated, a low variability in E/I delays was observed. Our results demonstrate that in many recordings MF stimulation recruited different groups of GCs that trigger E and/or I, and expanded PC temporal synaptic integration. Finally, using a computational model of the FFI pathway, we showed that this temporal expansion could strongly influence how PCs integrate GC inputs. Our findings show that specific E/I delays may help PCs encoding specific MF inputs.SIGNIFICANCE STATEMENT Sensorimotor information is conveyed to the cerebellar cortex by mossy fibers. Mossy fiber inputs activate granule cells that excite molecular interneurons and Purkinje cells, the sole output of the cerebellar cortex, leading to a sequence of synaptic excitation and inhibition in Purkinje cells, thus defining a feedforward inhibitory pathway. Using electrophysiological recordings, optogenetic stimulation, and mathematical modeling, we demonstrated that different groups of granule cells can elicit synaptic excitation and inhibition with various latencies onto Purkinje cells. This temporal variability controls how granule cells influence Purkinje cell discharge and may support temporal coding in the cerebellar cortex.

Inhibitory stabilized network behaviour in a balanced neural mass model of a cortical column

Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their “paradoxical response”, where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation–inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation–inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.

Pulse fluence noise dynamics at free-space propagation.

The dynamics of fluence noise of an optical pulse at free-space (e.g.,vacuum) propagation has been studied. It has been shown that the fluence noise with high spatial frequency is effectively cleaned out from the primary smooth pulse either by spatial walk-off or by temporal delay at a relatively small propagation distance. This effect can be referred to as spatial and temporal self-filtering and is of major interest in ultra-high-power and ultra-short-pulse applications. The study comprises a rigorous theory and a few relevant numerical simulation examples.

High-risk LEO satellite network path detection based on spatial and temporal delay anomaly analysis

High-risk LEO satellite network path detection based on spatial and temporal delay anomaly analysis