Spike Shape Research Articles

Feature diffusion reconstruction mechanism network for crop spike head detection.

Monitoring crop spike growth using low-altitude remote sensing images is essential for precision agriculture, as it enables accurate crop health assessment and yield estimation. Despite the advancements in deep learning-based visual recognition, existing crop spike detection methods struggle to balance computational efficiency with accuracy in complex multi-scale environments, particularly on resource-constrained low-altitude remote sensing platforms. To address this gap, we propose FDRMNet, a novel feature diffusion reconstruction mechanism network designed to accurately detect crop spikes in challenging scenarios. The core innovation of FDRMNet lies in its multi-scale feature focus reconstruction and lightweight parameter-sharing detection head, which can effectively improve the computational efficiency of the model while enhancing the model's ability to perceive spike shape and texture.FDRMNet introduces a Multi-Scale Feature Focus Reconstruction module that integrates feature information across different scales and employs various convolutional kernels to capture global context effectively. Additionally, an Attention-Enhanced Feature Fusion Module is developed to improve the interaction between different feature map positions, leveraging adaptive average pooling and convolution operations to enhance the model's focus on critical features. To ensure suitability for low-altitude platforms with limited computational resources, we incorporate a Lightweight Parameter Sharing Detection Head, which reduces the model's parameter count by sharing weights across convolutional layers. According to the evaluation experiments on the global wheat head detection dataset and diverse rice panicle detection dataset, FDRMNet outperforms other state-of-the-art methods with mAP@.5 of 94.23%, 75.13% and R 2 value of 0.969, 0.963 between predicted values and ground truth values. In addition, the model's frames per second and parameters in the two datasets are 227.27,288 and 6.8M, respectively, which maintains the top three position among all the compared algorithms. Extensive qualitative and quantitative experiments demonstrate that FDRMNet significantly outperforms existing methods in spike detection and counting tasks, achieving higher detection accuracy with lower computational complexity.The results underscore the model's superior practicality and generalization capability in real-world applications. This research contributes a highly efficient and computationally effective solution for crop spike detection, offering substantial benefits to precision agriculture practices.

Evaluation of the Spike Diversity of Seven Hexaploid Wheat Species and an Artificial Amphidiploid Using a Quadrangle Model Obtained from 2D Images

The spike shape and morphometric characteristics are among the key characteristics of cultivated cereals, being associated with their productivity. These traits are often used for the plant taxonomy and authenticity of hexaploid wheat species. Manual measurement of spike characteristics is tedious and not precise. Recently, the authors of this study developed a method for wheat spike morphometry utilizing 2D image analysis. Here, this method is applied to study variations in spike size and shape for 190 plants of seven hexaploid (2n = 6x = 42) species and one artificial amphidiploid of wheat. Five manually estimated spike traits and 26 traits obtained from digital image analysis were analyzed. Image-based traits describe the characteristics of the base, center and apex of the spike and common parameters (circularity, roundness, perimeter, etc.). Estimates of similar traits by manual measurement and image analysis were shown to be highly correlated, suggesting the practical importance of digital spike phenotyping. The utility of spike traits for classification into types (spelt, normal and compact) and species or amphidiploid is shown. It is also demonstrated that the estimates obtained made it possible to identify the spike characteristics differing significantly between species or between accessions within the same species. The present work suggests the usefulness of wheat spike shape analysis using an approach based on characteristics obtained by digital image analysis.

Effects of hand dominance on myoelectric signal of non‑fatigued lumbar multifidus muscle during single arm lifts.

Some evidence indicates that lower back muscles located at the non‑dominant side of the body are more fatigue resistant than their opposite counterparts presumably due to preferential use of the dominant hand. The aim of the study was to determine if any distinction exists in the surface electromyographic activity of corresponding contralateral non‑fatigued lumbar multifidus (LM) muscles as a function of hand dominance. The relative to maximum root mean square, the median frequency (MdF) and spike shape parameters were computed from the surface myoelectric signals of ipsilateral and contralateral lumbar multifidus muscle of 46 adult healthy subjects (27 right‑handed, 19 left‑handed) during voluntary contractions evoked by the single arm lifts in prone position. Activation of LM as a contralateral muscle to lifted arm was greater than as ipsilateral muscle, independently of handedness. Regardless if LM performed ipsi‑ or contralateral action to the lifted arm, the mean spike amplitude, slope, number of peaks per spike and spike duration were greater and mean spike frequency as well as MdF were smaller in the muscle of dominant than non‑dominant side. Combined changes of spike shape measures indicate increased recruitment, lower firing rates and higher synchronization of motor units in the LM of dominant side as compared to its counterpart.

Phenotypic characterization of two-row barley (Hordeum vulgare L. ssp. vulgare) germplasm conserved in Osman Tosun Genebank of Türkiye by multivariate analysis model

AbstractBarley is a crucial cereal crop with a diverse genetic heritage that includes landraces-traditionally cultivated variants that have adapted to varying agro-climatic conditions over centuries. Preserving barley landraces in genebanks is of utmost importance for safeguarding genetic diversity and aiding future breeding endeavors.This study aims an agro-morphological characterization of a selected collection of two row barley landraces conserved in the Osman Tosun Genebank. A total of 262 barley accessions were assessed in controlled field conditions to analyze various agro-morphological traits. The study unveiled notable disparities in the morphological traits of the genotypes, specifically in flag leaf anthocyanin, flag leaf sheath wax, spike shape, spike density, lemma color, grain color, lodging tendency, days to 50% flowering, plant height, spike length, spikelet quantity, and thousand grain weight, among other critical agronomical characteristics. To scrutinize the morphological disparities, the research utilized principal component analysis and ascertained that nearly 77.22% of the overall variance was accounted for by the first two principal components. The first four principal components accounted for 90.96% of the total variation, thus indicating significant genetic diversity among genotypes. The results of the cluster analysis revealed the presence of diverse genetic resources within the collection, with distinct groups of genotypes exhibiting similar traits being identified. The results of the agro-morphological characterization are a valuable resource for researchers and breeders, aiding them in making informed decisions regarding the management and application of barley landraces in breeding programs.

Unsupervised spike sorting for multielectrode arrays based on spike shape features and location methods.

Microelectrode arrays (MEAs) enable simultaneous measurement of spike trains from numerous neurons, owing to advancements in microfabrication technology. These probes are highly valuable for comprehending the intricate dynamics of neuronal networks. Spike sorting is a pivotal step in comprehensively analyzing the activity of neuronal networks from extracellular recordings. However, the accuracy of spike sorting is relatively low due to the dense sampling of spikes in MEAs. Here, we propose an unsupervised pipeline named UMAP-COM method, which utilizes combined features to address this problem. These combined features comprise dominant spike shape features extracted by the uniform manifold approximation and projection (UMAP), as well as spike locations estimated by the center of mass (COM). We validate the UMAP-COM method on publicly available datasets from different kinds of probes, demonstrating that it is more accurate than other spike sorting methods. Furthermore, we conduct separate evaluations of spike shape feature extraction methods and spike localization methods. In this comparison, UMAP emerges as the superior feature extraction method, demonstrating its effectiveness in accurately representing spike shapes. Additionally, we find that the COM method outperforms other spike localization methods, highlighting its ability to enhance the accuracy of spike sorting.

Identification and map-based cloning of an EMS-induced mutation in wheat gene TaSP1 related to spike architecture.

A candidate gene TaSP1 related to spike shape was cloned, and the gene-specific marker was developed to efficiently track the superior haplotype in common wheat. Spike shape, an important factor that affects wheat grain yield, is mainly defined by spike length (SPL), spikelet number (SPN), and compactness. Zhoumai32 mutant 1160 (ZM1160), a mutant obtained from ethyl methane sulfonate (EMS) treatment of hexaploid wheat variety Zhoumai32, was used to identify and clone the candidate gene that conditioned the spike shape. Genetic analysis of an F2 population derived from a cross of ZM1160 and Bainong207 suggested that the compact spike shape in ZM1160 was controlled by a single recessive gene, and therefore, the mutated gene was designated as Tasp1. With polymorphic markers identified through bulked segregant analysis (BSA), the gene was mapped to a 2.65-cM interval flanked by markers YZU0852 and MIS46239 on chromosome 7D, corresponding to a 0.42-Mb physical interval of Chinese spring (CS) reference sequences (RefSeq v1.0). To fine map TaSP1, 15 and seven recombinants were, respectively, screened from 1599 and 1903 F3 plants derived from the heterozygous F2 plants. Finally, TaSP1 was delimited to a 21.9Kb (4,870,562 to 4,892,493bp) Xmis48123-Xmis48104 interval. Only one high-confidence gene TraesCS7D02G010200 was annotated in this region, which encodes an unknown protein with a putative vWA domain. Quantitative reverse transcription PCR (qRT-PCR) analysis showed that TraesCS7D02G010200 was mainly expressed in the spike. Haplotype analysis of 655 wheat cultivars using the candidate gene-specific marker Xg010200p2 identified a superior haplotype TaSP1b with longer spike and more spikelet number. TaSP1 is beneficial to the improvement in wheat spike shape.

Interdependence of cellular and network properties in respiratory rhythm generation

How breathing is generated by the preBötzinger complex (preBötC) remains divided between two ideological frameworks, and a persistent sodium current (INaP) lies at the heart of this debate. Although INaP is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or "pacemaker" activity. In contrast, burstlet theory considers INaP dispensable because rhythm emerges from "preinspiratory" spiking activity driven by feed-forward network interactions. Using computational modeling, we find that small changes in spike shape can dissociate INaP from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and preinspiratory spiking without altering the role of INaP. Our results support a unifying hypothesis where INaP and excitatory network interactions, but not intrinsic bursting or preinspiratory spiking, are critical interdependent features of preBötC rhythmogenesis.

Identification of molecular markers and candidate regions associated with grain number per spike in Pubing3228 using SLAF-BSA.

Grain number per spike, a pivotal agronomic trait dictating wheat yield, lacks a comprehensive understanding of its underlying mechanism in Pubing3228, despite the identification of certain pertinent genes. Thus, our investigation sought to ascertain molecular markers and candidate regions associated with grain number per spike through a high-density genetic mapping approach that amalgamates site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). To facilitate this, we conducted a comparative analysis of two wheat germplasms, Pubing3228 and Jing4839, known to exhibit marked discrepancies in spike shape. By leveraging this methodology, we successfully procured 2,810,474 SLAF tags, subsequently resulting in the identification of 187,489 single nucleotide polymorphisms (SNPs) between the parental strains. We subsequently employed the SNP-index association algorithm alongside the extended distribution (ED) association algorithm to detect regions associated with the trait. The former algorithm identified 24 trait-associated regions, whereas the latter yielded 70. Remarkably, the intersection of these two algorithms led to the identification of 25 trait-associated regions. Amongst these regions, we identified 399 annotated genes, including three genes harboring non-synonymous mutant SNP loci. Notably, the APETALA2 (AP2) transcription factor families, which exhibited a strong correlation with spike type, were also annotated. Given these findings, it is plausible to hypothesize that these genes play a critical role in determining spike shape. In summation, our study contributes significant insights into the genetic foundation of grain number per spike. The molecular markers and candidate regions we have identified can be readily employed for marker-assisted breeding endeavors, ultimately leading to the development of novel wheat cultivars possessing enhanced yield potential. Furthermore, conducting further functional analyses on the identified genes will undoubtedly facilitate a comprehensive elucidation of the underlying mechanisms governing spike development in wheat.

Spike Analysis of the Neural Activities Across the Rats' Auditory Brain Structures.

Tinnitus is a health condition that affects a large population. Clinical diagnosis and treatment have been developed for treating tinnitus for years. However, there are still limitations because researchers have yet to elucidate the mechanisms underlying how tinnitus neural signals develop in brain structures. Abnormal neural interactions among the brain areas are considered to play an important role in tinnitus generation. Researchers have been studying neural activities in the auditory brain structures, including the dorsal cochlear nucleus (DCN), inferior colliculus (IC), and auditory cortex (AC), to seek a better understanding of the information flow among these brain regions, especially in comparison with both health and tinnitus conditions. In this project, neural activities from the DCN, IC, and AC were collected and analyzed before and after the animals were noise-exposed and before and after their auditory cortices were electrically stimulated. These conditions in rats were used to estimate healthy animals, noise-trauma-induced tinnitus, and after auditory cortex electrical stimulation (ACES) treatment. The signal processing algorithms started with the raw measurement data and focused on the local field potentials (LFPs) and spikes in the time domain. The firing rate, shape of spikes, and time differences among channels were analyzed in the time domain, and phase-phase correlation was used to test the phase-frequency information. All the analysis results were summarized in plots and color-heat maps and also used to identify if any neural signal differs and cross-channel relation changes at various animal conditions and discussed.

Fluctuation-response relations for integrate-and-fire models with an absolute refractory period.

We study the problem of relating the spontaneous fluctuations of a stochastic integrate-and-fire (IF) model to the response of the instantaneous firing rate to time-dependent stimulation if the IF model is endowed with a non-vanishing refractory period and a finite (stereotypical) spike shape. This seemingly harmless addition to the model is shown to complicate the analysis put forward by Lindner Phys. Rev. Lett. (2022), i.e., the incorporation of the reset into the model equation, the Rice-like averaging of the stochastic differential equation, and the application of the Furutsu-Novikov theorem. We derive a still exact (although more complicated) fluctuation-response relation (FRR) for an IF model with refractory state and a white Gaussian background noise. We also briefly discuss an approximation for the case of a colored Gaussian noise and conclude with a summary and outlook on open problems.

Strontium concentration spikes as evidence for fluid-driven carbonate dissolution during subduction

Carbonate dissolution, the process by which carbonate minerals are stoichiometrically dissolved by an aqueous fluid, likely plays an important role in liberating carbon from subducting slabs and may thus make significant contributions to global carbon fluxes. It is therefore necessary to understand the fluid infiltration and flow geometries associated with this process. Despite its widespread use as a powerful tracer of fluid-rock interaction, strontium (Sr) has yet to be widely applied to carbonate dissolution scenarios. Previous work has identified a partially altered metacarbonate layer from Syros, Greece, that has undergone significant carbonate dissolution leading to ∼90% CO2 loss (Ague and Nicolescu, 2014). A bulk-rock compositional profile along this layer has a distinctive spike-shaped Sr profile. Sr concentrations are uniform in the altered region behind the reaction front, increase to form a spike just ahead of the front, and taper off to a baseline value moving farther into the unaltered metacarbonate rock. The origin of this type of spike shape and its potential utility for better understanding carbonate dissolution processes remain unaddressed. Here, we present a numerical diffusion-reaction model which demonstrates that both carbonate dissolution and multidimensional transport of Sr, in which the primary advective flow direction is perpendicular to the propagation of the diffusion front, are required to produce this shape. This model, as well as newly acquired Sr concentration data for calcite (former aragonite) and epidote, also indicate that the infiltration of a fluid with an elevated Sr concentration is necessary. We suggest that such spike-shaped features may aid in identifying carbonate dissolution in other settings, such as vein-selvage systems in metacarbonate rocks or reaction rinds on carbonate-bearing mélange blocks.

Integrate-and-fire-type models of the lateral superior olive.

Neurons of the lateral superior olive (LSO) in the auditory brainstem play a fundamental role in binaural sound localization. Previous theoretical studies developed various types of neuronal models to study the physiological functions of the LSO. These models were usually tuned to a small set of physiological data with specific aims in mind. Therefore, it is unclear whether and how they can be related to each other, how widely applicable they are, and which model is suitable for what purposes. In this study, we address these questions for six different single-compartment integrate-and-fire (IF) type LSO models. The models are divided into two groups depending on their subthreshold responses: passive (linear) models with only the leak conductance and active (nonlinear) models with an additional low-voltage-activated potassium conductance that is prevalent among the auditory system. Each of these two groups is further subdivided into three subtypes according to the spike generation mechanism: one with simple threshold-crossing detection and voltage reset, one with threshold-crossing detection plus a current to mimic spike shapes, and one with a depolarizing exponential current for spiking. In our simulations, all six models were driven by identical synaptic inputs and calibrated with common criteria for binaural tuning. The resulting spike rates of the passive models were higher for intensive inputs and lower for temporally structured inputs than those of the active models, confirming the active function of the potassium current. Within each passive or active group, the simulated responses resembled each other, regardless of the spike generation types. These results, in combination with the analysis of computational costs, indicate that an active IF model is more suitable than a passive model for accurately reproducing temporal coding of LSO. The simulation of realistic spike shapes with an extended spiking mechanism added relatively small computational costs.

Automated Processing of Nano-Impact Electrochemistry Signals Using Data-Driven Template Matching

Nano-impact electrochemistry (NIE) is an advanced electrochemical technique that has gained significant attention in recent years due to its ability to investigate properties of individual entities, such as nanoparticles, cells, or even single molecules1 . A typical NIE experiment involves investigating entities freely moving in solution and colliding with an ultramicroelectrode held at a specific potential, allowing individual entities to be electrochemically detected during the collision.The typical NIE responses are the staircase and blip types (spikes),2 with the latter being more commonly observed in NIE experiments. Analysis of spike signals, however, is more complicated due to their irregular and asymmetric shapes. To analyze NIE signals, most studies rely on peak find functions using height threshold for spike identification3 coupled to peak area calculation based on the assumption that the spike shape follows certain distribution functions4. This approach only partially captures the information present in the NIE signal and may result in an inaccurate analysis as demonstrated in Scheme 1, left.To address this issue, we propose a new algorithm, which leverages unsupervised machine learning and image template-matching technology. The algorithm consists of several steps. First, the raw data are denoised. This is done by applying the time-frequency analysis to the data to identify the spike frequency and remove higher-frequency noise using a bandpass filter. Background subtraction is then conducted to align the denoised curve to an approximate zero baseline. Further, some of the current spikes are sampled using a conventional height threshold method to generate templates. A set of templates is generated by clustering the corresponding feature parameters. Template matching is carried out by computing the normalized cross-correlation coefficient of each template on the offset signal. Finally, once the two end points of the spikes have been well-defined parameters characterizing the shape of the current spikes are extracted. Optionally, a new set of templates can be generated for the rematch with the data.The developed algorithm permit precisely detecting the two sides of the spike and extracting critical shape-related parameters, leading to a more accurate and detailed analysis of the NIE signals (Scheme 1, right). Furthermore, by generating templates that reflect the distinguishing features of spikes, observed current signals can be classified into different types, revealing underlying physical phenomena. This method can aid in the standardization of data processing and NIE signal interpretation across various experiments and applications. It can also be used as a pre-processing step when training classification neural networks, which can automate the spike identification process and develop NIE models. As a result, the proposed algorithm has the potential to provide valuable insights into the properties of single entities and advance our understanding of electrochemical reactions at the nanoscale.Reference1. Baker LA. Perspective and Prospectus on Single-Entity Electrochemistry. J Am Chem Soc. 2018;140(46):15549-15559. doi:10.1021/jacs.8b097472. Kwon SJ, Zhou H, Fan FRF, Vorobyev V, Zhang B, Bard AJ. Stochastic electrochemistry with electrocatalytic nanoparticles at inert ultramicroelectrodes—theory and experiments. Phys Chem Chem Phys. 2011;13(12):5394-5402. doi:10.1039/C0CP02543G3. Little CA, Xie R, Batchelor-McAuley C, et al. A quantitative methodology for the study of particle–electrode impacts. Phys Chem Chem Phys. 2018;20(19):13537-13546. doi:10.1039/C8CP01561A4. Peak Finding and Measurement. https://terpconnect.umd.edu/~toh/spectrum/PeakFindingandMeasurement.htm Figure 1

Neuronal Spike Shapes (NSS): A straightforward approach to investigate heterogeneity in neuronal excitability states

The mammalian brain exhibits a remarkable diversity of neurons, contributing to its intricate architecture and functional complexity. The analysis of multimodal single-cell datasets enables the investigation of cell types and states heterogeneity. In this study, we introduce the Neuronal Spike Shapes (NSS), a straightforward approach for the exploration of excitability states of neurons based on their Action Potential (AP) waveforms. The NSS method describes the AP waveform based on a triangular representation complemented by a set of derived electrophysiological (EP) features. To support this hypothesis, we validate the proposed approach on two datasets of murine cortical neurons, focusing it on GABAergic neurons. The validation process involves a combination of NSS-based clustering analysis, features exploration, Differential Expression (DE), and Gene Ontology (GO) enrichment analysis. Results show that the NSS-based analysis captures neuronal excitability states that possess biological relevance independently of cell subtype. In particular, Neuronal Spike Shapes (NSS) captures, among others, a well-characterized fast-spiking excitability state, supported by both electrophysiological and transcriptomic validation. Gene Ontology Enrichment Analysis reveals voltage-gated potassium (K+) channels as specific markers of the identified NSS partitions. This finding strongly corroborates the biological relevance of NSS partitions as excitability states, as the expression of voltage-gated K+ channels regulates the hyperpolarization phase of the AP, being directly implicated in the regulation of neuronal excitability.

Generation of ultrashort Rayleigh wave pulses using the combination of temporal and spatial pulse compression technique

Rayleigh waves generated by electromagnetic acoustic transducers (EMATs) have been widely used in nondestructive testing and evaluations. To improve the signal to noise ratio (SNR) and spatial resolution of Rayleigh waves simultaneously, the combination of temporal and spatial pulse compression (TSPC) technique is proposed. By analyzing the topology diagram of the typical pulse compression technique, a frequency modulated signal acts as the stretcher and a wavelength modulated meander line coil acts as the compressor. Experimental results indicate that the ultrasound fields of Rayleigh waves using the proposed TSPC technique show a spike shape in the spatial domain. Compared with the typical meander-line coil EMATs, the TSPC technique shows significant improvement of the generated Rayleigh waves. The SNR has increased by 12 dB while the main lobe width has decreased by about 98%.

Spike Optimization to Improve Properties of Ferroelectric Tunnel Junction Synaptic Devices for Neuromorphic Computing System Applications.

The continuous advancement of Artificial Intelligence (AI) technology depends on the efficient processing of unstructured data, encompassing text, speech, and video. Traditional serial computing systems based on the von Neumann architecture, employed in information and communication technology development for decades, are not suitable for the concurrent processing of massive unstructured data tasks with relatively low-level operations. As a result, there arises a pressing need to develop novel parallel computing systems. Recently, there has been a burgeoning interest among developers in emulating the intricate operations of the human brain, which efficiently processes vast datasets with remarkable energy efficiency. This has led to the proposal of neuromorphic computing systems. Of these, Spiking Neural Networks (SNNs), designed to closely resemble the information processing mechanisms of biological neural networks, are subjects of intense research activity. Nevertheless, a comprehensive investigation into the relationship between spike shapes and Spike-Timing-Dependent Plasticity (STDP) to ensure efficient synaptic behavior remains insufficiently explored. In this study, we systematically explore various input spike types to optimize the resistive memory characteristics of Hafnium-based Ferroelectric Tunnel Junction (FTJ) devices. Among the various spike shapes investigated, the square-triangle (RT) spike exhibited good linearity and symmetry, and a wide range of weight values could be realized depending on the offset of the RT spike. These results indicate that the spike shape serves as a crucial indicator in the alteration of synaptic connections, representing the strength of the signals.

Characterization of extracellular spike waveforms recorded in wallaby primary visual cortex.

Extracellular recordings were made from 642 units in the primary visual cortex (V1) of a highly visual marsupial, the Tammar wallaby. The receptive field (RF) characteristics of the cells were objectively estimated using the non-linear input model (NIM), and these were correlated with spike shapes. We found that wallaby cortical units had 68% regular spiking (RS), 12% fast spiking (FS), 4% triphasic spiking (TS), 5% compound spiking (CS) and 11% positive spiking (PS). RS waveforms are most often associated with recordings from pyramidal or spiny stellate cell bodies, suggesting that recordings from these cell types dominate in the wallaby cortex. In wallaby, 70-80% of FS and RS cells had orientation selective RFs and had evenly distributed linear and nonlinear RFs. We found that 47% of wallaby PS units were non-orientation selective and they were dominated by linear RFs. Previous studies suggest that the PS units represent recordings from the axon terminals of non-orientation selective cells originating in the lateral geniculate nucleus (LGN). If this is also true in wallaby, as strongly suggested by their low response latencies and bursty spiking properties, the results suggest that significantly more neurons in wallaby LGN are already orientation selective. In wallaby, less than 10% of recorded spikes had triphasic (TS) or sluggish compound spiking (CS) waveforms. These units had a mixture of orientation selective and non-oriented properties, and their cellular origins remain difficult to classify.

Dark matter spikes around Sgr A* in γ-rays

AbstractWe use H.E.S.S.γ-ray observations of Sgr A* to derive novel limits on the Dark Matter (DM) annihilation cross-section. We quantify their dependence on uncertainties i) in the DM halo profile, which we vary from peaked to cored, and ii) in the shape of the DM spike around Sgr A*, dynamically heated by the nuclear star cluster. For peaked halo profiles and depending on the heating of the spike, our limits are the strongest existing ones for DM masses above a few TeV. Our study contributes to assessing the influence of the advancements in our knowledge of the Milky Way on determining the properties of DM particles.

Numerical Analysis and Design Optimization Of Bluff Body Using Spike

The drag force caused on the re-entry vehicle and for missile, cursing at supersonic speed will result in Aerodynamic heating of the body. To minimize the aerodynamic heating and drag, designing of bluff body is an important aspect. This paper deals with the design optimization of bluff body using spike. Computational studies have been made in ANSYS FLUENT to obtain the effect of spike shape and length over a bluff body at supersonic Mach number of 2 at zero angle of attack. In this paper numerical analysis on conical bluff body integrated with different spike configurations were carried out using ANSYS software packages. Computations have been made on three spike configurations i.e., sharp, blunt and aerospike of different lengths. Larger the recirculation zone, reduces coefficient of drag. It has been observed that with an increase in spike length the pressure fluctuations increase and with the change in shape to blunt spike and sharp spike the fluctuations decrease.

Sodium channel slow inactivation normalizes firing in axons with uneven conductance distributions

The Na+ channels that are important for action potentials show rapid inactivation, a state in which they do not conduct, although the membrane potential remains depolarized.1,2 Rapid inactivation is a determinant of millisecond-scale phenomena, such as spike shape and refractory period. Na+ channels also inactivate orders of magnitude more slowly, and this slow inactivation has impacts on excitability over much longer timescales than those of a single spike or a single inter-spike interval.3,4,5,6,7,8,9,10 Here, we focus on the contribution of slow inactivation to the resilience of axonal excitability11,12 when ion channels are unevenly distributed along the axon. We study models in which the voltage-gated Na+ and K+ channels are unevenly distributed along axons with different variances, capturing the heterogeneity that biological axons display.13,14 In the absence of slow inactivation, many conductance distributions result in spontaneous tonic activity. Faithful axonal propagation is achieved with the introduction of Na+ channel slow inactivation. This "normalization" effect depends on relations between the kinetics of slow inactivation and the firing frequency. Consequently, neurons with characteristically different firing frequencies will need to implement different sets of channel properties to achieve resilience. The results of this study demonstrate the importance of the intrinsic biophysical properties of ion channels in normalizing axonal function.