Local Field Research Articles

Preharvest Sprouting in Quinoa: A New Screening Method Adapted to Panicles and GWAS Components.

The introduction of quinoa into new growing regions and environments is of interest to farmers, consumers, and stakeholders around the world. Many plant breeding programs have already started to adapt quinoa to the environmental and agronomic conditions of their local fields. Formal quinoa breeding efforts in Washington State started in 2010, led by Professor Kevin Murphy out of Washington State University. Preharvest sprouting appeared as the primary obstacle to increased production in the coastal regions of the Pacific Northwest. Preharvest sprouting (PHS) is the undesirable sprouting of seeds that occurs before harvest, is triggered by rain or humid conditions, and is responsible for yield losses and lower nutrition in cereal grains. PHS has been extensively studied in wheat, barley, and rice, but there are limited reports for quinoa, partly because it has only recently emerged as a problem. This study aimed to better understand PHS in quinoa by adapting a PHS screening method commonly used in cereals. This involved carrying out panicle-wetting tests and developing a scoring scale specific for panicles to quantify sprouting. Assessment of the trait was performed in a diversity panel (N = 336), and the resulting phenotypes were used to create PHS tolerance rankings and undertake a GWAS analysis (n = 279). Our findings indicate that PHS occurred at varying degrees across a subset of the quinoa germplasm tested and that it is possible to access PHS tolerance from natural sources. Ultimately, these genotypes can be used as parental lines in future breeding programs aiming to incorporate tolerance to PHS.

Detection of surface enhanced Raman scattering active hotspot using near field scanning optical microscopy

Hotspots are high-intensity electromagnetic zones that form, for example, at the interstitials of plasmonic nanoaggregates, resulting in a considerable rise in the enhancement factor. However, it is inevitable to achieve specific nanometric geometry as well as a suitable technique to capture the details of hotspots. We report near-field surface-enhanced Raman scattering (SERS) spectroscopy of a well-defined gold nanoaggregate of a few nanoparticles adsorbed with a small number of target analytes. A spectrally and spatially resolved SERS measurement setup using an aperture near-field scanning optical microscope (a-NSOM) facilitated the direct observation of localized electromagnetic (EM) fields at the interstitials through SERS. Correlated optical image and corresponding nanometric geometry were captured through the home-built a-NSOM setup. Near-field SERS spectra were recorded at different sites of interest. It was evident that the interstitial positioned at the center of the tetramer provided the most intense Raman scattering, implying the possibility of a SERS-active hotspot therein. SERS bands of the spectrum of the Raman-active dye Rhodamine 6G recorded at the same hotspot coincided well with those reported so far. It was noteworthy that most of the SERS bands in such scenery got enhanced. Such direct observation with high spatial resolution is indispensable to understanding the origin of localized EM fields at “hotspots” and the EM enhancement factor in the SERS process. A finite-difference time-domain (FDTD) analysis was carried out to validate the results.

Effect of an edge dislocation on hydride growth in zirconium: elastic complex potential study

The formation of hydrides can significantly decrease the mechanical reliability of Zr servicing in the nuclear reactor. This study investigates the effect of the local stress field resulting from the hydride eigenstrain and dislocations on hydrogen transport and explores the hydride growth regulation. The stress functions, which can be extended and further applied to the realistic crystal structure and servicing status, are derived using the dislocation-based strain nucleus model and elastic complex potential method. The nonhomogeneous equation of hydrogen transport governed by diffusion and hydrostatic stress gradient is analytically solved. The results show that: (1) In the absence of dislocations, the hydride grows toward 112¯0 direction under the hydrostatic stress gradient resulting from the hydride eigenstrain. (2) The lower the temperature is, the higher the hydrogen concentration gradient in the adjacent area of the hydride is. The higher hydrogen fraction can also accelerate the growth rate. (3) Dislocation defects are capable of inducing triangle-shaped and asymmetric growth tendencies and providing new nucleation loci for hydrides. Based on the significant hydrostatic stress gradient led by dislocation singularity, this study analytically explains the autocatalysis and new-nucleation-locus effects raised by the in-situ observations.

Radially transverse isotropic inclusions in isotropic elastic media: Local fields, neutral inclusions, effective elastic properties

Radially transverse isotropic inclusions in homogeneous isotropic elastic host media are considered. Mellin transform method is used for solution of the volume integral equation of the problem for an isolated inclusion subjected to a constant external stress (strain) field. The tensor structure of the solution is revealed with precision to three scalar functions of the radial coordinate, and the system of ordinary differential equations for these functions is derived. For multilayered radially transverse isotropic inclusions with constant elastic coefficients inside layers, explicit solution of these equations is obtained. An efficient numerical algorithm of solution for inclusions with an arbitrary number of the layers is proposed. Neutral inclusions that do not disturb homogeneous external fields applied to the medium are considered. It is shown that an inclusion with an isotropic core and radially transverse isotropic external layer can be weak neutral by appropriate choice of the layer elastic constants. The effective field method is used for determination of the effective elastic stiffness tensor of a homogeneous isotropic medium containing a random set of radially transverse isotropic inclusions.

Unraveling Exciton-Plasmon Coupling and the PIRET Mechanism in Decorated Silicon Nanowires.

Exciton-plasmon coupling is a fascinating physical phenomenon that has been investigated in various metal semiconductor systems. Intentionally chosen silicon nanowires (SiNWs) systems act as a host material for providing exciton as well as silicon oxide as a thin dielectric. A clear blue-shift in photoluminescence (PL) peak and a significant increase in visible range absorption were observed for metal nanoparticle (MNP) decorated SiNWs (D-SiNWs) which signifies the presence of exciton-plasmon coupling. A further investigation reveals that the possibility of the occurrence of the plasmon-induced resonance energy transfer (PIRET) mechanism is higher. The PL intensity enhancement in Au-decorated SiNWs is higher (∼38 times) in comparison to that in Pt due to the presence of a strong and localized electric field of plasmons near the interface of metal and semiconductors. Moreover, splitting in PL for gold-decorated SiNWs might be due to the presence of dipole-quadrupole coupling along with dipole-dipole coupling, which further increases the strength of the PIRET mechanism.

Characterization of cascaded arc He plasma in a compact linear plasma device using voltammetry and optical emission spectroscopy

Cascaded arc plasma has been widely applied in linear plasma devices (LPDs) to produce high flux plasma for the study of plasma-material interaction. In this work, cascaded arc He plasma produced in an LPD with a compact arrangement is investigated by voltammetry and optical emission spectroscopy (OES). The results show that the cathode potential increases with the discharge current while it firstly decreases and then increases as increasing the gas flow rate. A local reverse electric field is observed at low gas flow rates between two cascaded plates (i.e. floating electrodes) near the cathode. The OES’ results reveal that as the gas flow rate increases, the intensity of He I lines increases and the electron excitation temperature (T exc ) decreases. As increasing the discharge current, the intensity of He lines exhibits various trends at different gas flow rates, showing a monotonic decline at 1.94 slm and a first increase followed by a reduction at 3.52 slm. The T exc increases with the discharge current. These findings could preliminarily shed light on the properties of cascaded arc of He plasma in the compact LPD and aid in the optimization of the device to generate the high-flux divertor-relevant plasma.

Design and implementation of dynamic beam shaping in high power laser processing by means of a Deformable Mirror

Optimising the laser intensity distribution in high power laser processes, such as laser welding, laser cladding or laser hardening, can be used to tailor the local thermal fields and thermal cycles which, in turn, determine the final process results. Deformable Mirrors allow to dynamically shape the beam profile and previous studies showed their potential. However, only limited flexibility in achievable beam shapes is shown at higher power levels. In addition the relation between desired laser intensity profiles and required mirror surface profiles is nontrivial. In this work the design and implementation of a dynamic beam shaping system, capable of handling high laser powers (up to 1 kW), is presented and evaluated. To that end, several distinctly different laser intensity profiles are defined, corresponding mirror surfaces are determined and realised with the beam shaping system. Measurements of the laser intensity profiles were compared with laser intensity profiles simulated using a previously presented mathematical framework and showed a good agreement. From the measurements it was concluded that the setup is suitable for high laser powers (up to 1 kW) and is characterised by large depth of focus (<14% change in dimensions at a distance of 100 mm from the focal plane).

Enhanced Magnetoimpedance Effect in Co-Based Micron Composite CoFeNiSiB Ribbon Strips Coated by Carbon and FeCoGa Nanofilms for Sensing Applications.

Quenched Co-based ribbon strips are widely used in the fields of magnetic amplifier, magnetic head material, magnetic shield, electric reactor, inductance core, sensor core, anti-theft system label, and so on. In this study, Co-based composite CoFeNiSiB ribbon strips with a micron width were fabricated by micro-electro-mechanical systems (MEMS) technology. The carbon and FeCoGa nanofilms were deposited for surface modification. The effect of carbon and FeCoGa nanofilm coatings on the crystal structure, surface morphology, magnetic properties, and magnetoimpedance (MI) effect of composite ribbon strips were systematically investigated. The results show that the surface roughness and coercivity of the composite ribbon strips are minimum at a thickness of the carbon coating of 60 nm. The maximum value of MI effect is 41% at 2 MHz, which is approximately 2.4 times greater than plain ribbon and 1.6 times greater than FeCoGa-coated composite ribbon strip. The addition of a carbon layer provides a conductive path for high frequency currents, which effectively reduces the characteristic frequency of the composite ribbon strip. The FeCoGa coating is able to close the flux path and reduce the coercivity, which, in turn, increases the transverse permeability and improves the MI effect. The findings indicate that a successful combination of carbon layer and magnetostrictive FeCoGa nanofilm layer can improve the MI effect and magnetic field sensitivity of the ribbon strips, demonstrating the potential of the composite strips for local and micro area field sensing applications.

Delineation of intracavitary electrograms for the automatic quantification of decrement-evoked potentials in the coronary sinus with deep-learning techniques.

Cardiac arrhythmias cause depolarization waves to conduct unevenly on the myocardial surface, potentially delaying local components with respect to a previous beat when stimulated at faster frequencies. Despite the diagnostic value of localizing the distinct local electrocardiogram (EGM) components for identifying regions with decrement-evoked potentials (DEEPs), current software solutions do not perform automatic signal quantification. Electrophysiologists must manually measure distances on the EGM signals to assess the existence of DEEPs during pacing or extra-stimuli protocols. In this work, we present a deep learning (DL)-based algorithm to identify decrement in atrial components (measured in the coronary sinus) with respect to their ventricular counterparts from EGM signals, for disambiguating between accessory pathways (APs) and atrioventricular re-entrant tachycardias (AVRTs). Several U-Net and W-Net neural networks with different configurations were trained on a private dataset of signals from the coronary sinus (312 EGM recordings from 77 patients who underwent AP or AVRT ablation). A second, separate dataset was annotated for clinical validation, with clinical labels associated to EGM fragments in which decremental conduction was elucidated. To alleviate data scarcity, a synthetic data augmentation method was developed for generating EGM recordings. Moreover, two novel loss functions were developed to minimize false negatives and delineation errors. Finally, the addition of self-attention mechanisms and their effect on model performance was explored. The best performing model was a W-Net model with 6 levels, optimized solely with the Dice loss. The model obtained precisions of 91.28%, 77.78% and of 100.0%, and recalls of 94.86%, 95.25% and 100.0% for localizing local field, far field activations, and extra-stimuli, respectively. The clinical validation model demonstrated good overall agreement with respect to the evaluation of decremental properties. When compared to the criteria of electrophysiologists, the automatic exclusion step reached a sensitivity of 87.06% and a specificity of 97.03%. Out of the non-excluded signals, a sensitivity of 96.77% and a specificity of 95.24% was obtained for classifying them into decremental and non-decremental potentials. Current results show great promise while being, to the best of our knowledge, the first tool in the literature allowing the delineation of all local components present in an EGM recording. This is of capital importance at advancing processing for cardiac electrophysiological procedures and reducing intervention times, as many diagnosis procedures are performed by comparing segments or late potentials in subsequent cardiac cycles.

Lost in Rotation: How TiO2 and ZnO Nanoparticles Disrupt Coordinated Epithelial Cell Rotation.

Coordinated cell movement is a cardinal feature in tissue organization that highlights the importance of cells working together as a collective unit. Disruptions to this synchronization can have far-reaching pathological consequences, ranging from developmental disorders to tissue repair impairment. Herein, it is shown that metal oxide nanoparticles (NPs), even at low and non-toxic doses (1 and 10µg mL-1), can perturb the coordinated epithelial cell rotation (CECR) in micropatterned human epithelial cell clusters via distinct nanoparticle-specific mechanisms. Zinc oxide (ZnO) NPs are found to induce significant levels of intracellular reactive oxygen species (ROS) to promote mitogenic activity. Generation of a new localized force field through changes in the cytoskeleton organization and an increase in cell density leads to the arrest of CECR. Conversely, epithelial cell clusters exposed to titanium dioxide (TiO2) NPs maintain their CECR directionality but display suppressed rotational speed in an autophagy-dependent manner. Thus, these findings reveal that nanoparticles can actively hijack the nano-adaptive responses of epithelial cells to disrupt the fundamental mechanics of cooperation and communication in a collective setting.

Local Electric Fields Drives the Proton-Coupled Electron Transfer within Cytochrome P450 Reductase

Local Electric Fields Drives the Proton-Coupled Electron Transfer within Cytochrome P450 Reductase

Deep Learning-Based Design Method for Acoustic Metasurface Dual-Feature Fusion.

Existing research in metasurface design was based on trial-and-error high-intensity iterations and requires deep acoustic expertise from the researcher, which severely hampered the development of the metasurface field. Using deep learning enabled the fast and accurate design of hypersurfaces. Based on this, in this paper, an integrated learning approach was first utilized to construct a model of the forward mapping relationship between the hypersurface physical structure parameters and the acoustic field, which was intended to be used for data enhancement. Then a dual-feature fusion model (DFCNN) based on a convolutional neural network was proposed, in which the first feature was the high-dimensional nonlinear features extracted using a data-driven approach, and the second feature was the physical feature information of the acoustic field mined using the model. A convolutional neural network was used for feature fusion. A genetic algorithm was used for network parameter optimization. Finally, generalization ability verification was performed to prove the validity of the network model. The results showed that 90% of the integrated learning models had an error of less than 3 dB between the real and predicted sound field data, and 93% of the DFCNN models could achieve an error of less than 5 dB in the local sound field intensity.

Angle-Resolved Polarimetry with Quasi-Bound States in the Continuum Plasmonic Metamaterials via 3D Aerosol Nanoprinting.

Three-dimensional (3D) plasmonic metamaterials, featuring well-arranged subwavelength nanostructures, facilitate effective coupling between electrical dipoles and incident electromagnetic waves. This coupling allows for unique optical responses including localized surface plasmon resonance (LSPR) and quasi-bound states in the continuum (q-BIC). While 3D plasmonic metamaterials with LSPR and q-BIC have been independently explored for sensors, achieving simultaneous optical responses in the near-infrared region remains challenging. Here, we present 3D plasmonic metamaterials that integrate LSPR and q-BIC within a single π-shaped plasmonic structure, fabricated using a 3D aerosol nanoprinting technique. This printing technique controls the local electrostatic field to precisely position charged metallic nanoaerosols, enabling parallel printing of π-shaped plasmonic structures under ambient conditions. The printed π-shaped plasmonic structures exhibit two distinct optical modes: x-polarization-sensitive LSPR and transverse magnetic mode-sensitive q-BIC within the near-infrared region. Exploiting these dual optical responses, we demonstrate simultaneous polarization detection and incident angle analysis by integrating the π-shaped plasmonic structures into commercial Fourier-transform infrared spectroscopy, termed "numerical aperture-detective polarimetry". This approach holds promise for evaluating alignment in optical and imaging systems with light distribution analysis. Furthermore, the 3D aerosol nanoprinting technique provides an avenue for fabricating 3D plasmonic metamaterials with intricate geometries and optical properties, expanding their potential applications in nano-optics.

Quasi-bound state in the continuum in a dielectric double-gap split-ring metasurface structure with large split angles

It was reported previously that the quality factor of a symmetry-protected quasi-BIC mode increases as the degree of structure asymmetry is reduced. In this work, we propose and investigate an alternative approach to increase the quality factor of a quasi-BIC mode without reducing the degree of asymmetry. Specifically, we calculate the quality factor of the quasi-BIC mode of a double-gap dielectric split-ring metasurface for different split angles. It is found that the quality factor increases exponentially with the increase of the split angles while the degree of asymmetry of the structure is constant. To explain the phenomena, multipole moment decomposition of the local electromagnetic field is conducted to calculate the change of major multipole moments versus the split angles. It is revealed that the double-gap split-ring array structure stores more energy in the higher order multipoles, and the rate of radiation energy loss stays constant when the two splitting angles increase simultaneously. Additionally, the enhancement of third harmonic generation is investigated in the double-gap split-ring metasurface structure.

Achieving high energy storage density and efficiency in (Na0.5Bi0.5)TiO3-based lead-free ceramics

Due to the demands of miniaturization, weight reduction and green development for electronic devices, development of lead-free dielectric ceramic capacitors with high recoverable energy density (Wrec) and energy storage efficiency (η) attracts much attention. To this end, (1-x)[0.75(Na0.5Bi0.5)TiO3-0.25SrTiO3]-xNdNbO4 (abbreviated as: NBST-xNN) ceramics were fabricated through a solid-state reaction method. After adding NN, the non-perovskite phase of Bi2Ti2O7 (BTO) with low dielectric constant (εr) and loss (tan δ) is generated. Finite element software (COMSOL) was used to explore the influence of the BTO phase on breakdown strength (Eb). The simulation result indicates that the BTO phase with a low εr concentrates a larger local electric field (LEF), and thus weakens the LEF loading in the main perovskite phase, which is beneficial for enhancing Eb. Moreover, NN doping significantly decreases the oxygen vacancy concentration in NBST ceramics, which plays a key role in improving Eb. On the other hand, as NN content increases, the hysteresis of the polarization (P)-electric field (E) loops is substantially suppressed, and the polarization saturation is delayed, which can be ascribed to the appearance of the BTO phase having a linear dielectric characteristic and to the enhanced fluctuations of composition and charge by NN doping. Benefitting from the above factors, the optimal energy storage performance (ESP) with a Wrec of 4.14 J/cm3 and an η of 90 % is obtained in NBST-0.08NN ceramics. Meanwhile, the ESP of NBST-0.08NN ceramics shows good charge-discharge properties and thermal stability. In conclusion, these results demonstrate that NBST-0.08NN ceramics are promising candidates as environment-friendly dielectric capacitor materials.

Associating LOFAR Galactic Faraday structures with the warm neutral medium

Faraday tomography observations with the Low Frequency Array (LOFAR) have unveiled a remarkable network of structures in polarized synchrotron emission at high Galactic latitudes. The observed correlation between LOFAR structures, dust polarization, and emission suggests a connection to the neutral interstellar medium (ISM). We investigated this relationship by estimating the rotation measure (RM) of the warm neutral (partially ionized) medium (WNM) in the local ISM. Our work combines UV spectroscopy from FUSE and dust polarization observations from with LOFAR data. We derived electron column densities from UV absorption spectra toward nine background stars, within the field of published data from the LOFAR two-meter sky survey. The associated RMs were estimated using a local magnetic field model fitted to the dust polarization data of A comparison with Faraday spectra at the position of the stars suggests that LOFAR structures delineate a slab of magnetized WNM and synchrotron emission, located ahead of the bulk of the warm ionized medium. This conclusion establishes an astrophysical framework for exploring the link between Faraday structures and the dynamics of the magnetized multiphase ISM. It will be possible to test it on a larger sample of stars when maps from the full northern sky survey of LOFAR become available.

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats

AbstractSocial behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activity when two animals synchronize their behavior to obtain a mutual reinforcement. In a previous work, we showed that the activity of the prelimbic cortex (PrL) was enhanced during cooperation in rats, especially in the ones leading most cooperative trials (leader rats). In this study, we investigated the specific cells in the PrL contributing to cooperative behaviors. To this end, we collected rats’ brains at key moments of the learning process to analyze the levels of c-FOS expression in the main cellular groups of the PrL. Leader rats showed increased c-FOS activity in cells expressing D1 receptors during cooperation. Besides, we analyzed the levels of anxiety, dominance, and locomotor behavior, finding that leader rats are in general less anxious and less dominant than followers. We also recorded local field potentials (LFPs) from the PrL, the nucleus accumbens septi (NAc), and the basolateral amygdala (BLA). A spectral analysis showed that delta activity in PrL and NAc increased when rats cooperated, while BLA activity in delta and theta bands decreased considerably during cooperation. The PrL and NAc also increased their connectivity in the high theta band during cooperation. Thus, the present work identifies the specific PrL cell types engaged in this behavior, as well as the way this information is propagated to selected downstream brain regions (BLA, NAc).

Neurometric amplitude modulation detection in the inferior colliculus of Young and Aged rats

Amplitude modulation is an important acoustic cue for sound discrimination, and humans and animals are able to detect small modulation depths behaviorally. In the inferior colliculus (IC), both firing rate and phase-locking may be used to detect amplitude modulation. How neural representations that detect modulation change with age are poorly understood, including the extent to which age-related changes may be attributed to the inherited properties of ascending inputs to IC neurons. Here, simultaneous measures of local field potentials (LFPs) and single-unit responses were made from the inferior colliculus of Young and Aged rats using both noise and tone carriers in response to sinusoidally amplitude-modulated sounds of varying depths. We found that Young units had higher firing rates than Aged for noise carriers, whereas Aged units had higher phase-locking (vector strength), especially for tone carriers. Sustained LFPs were larger in Young animals for modulation frequencies 8–16 Hz and comparable at higher modulation frequencies. Onset LFP amplitudes were much larger in Young animals and were correlated with the evoked firing rates, while LFP onset latencies were shorter in Aged animals. Unit neurometric thresholds by synchrony or firing rate measures did not differ significantly across age and were comparable to behavioral thresholds in previous studies whereas LFP thresholds were lower than behavior.

Brain complexity in stroke recovery after bihemispheric transcranial direct current stimulation in mice.

Stroke is one of the leading causes of disability worldwide. There are many different rehabilitation approaches aimed at improving clinical outcomes for stroke survivors. One of the latest therapeutic techniques is the non-invasive brain stimulation. Among non-invasive brain stimulation, transcranial direct current stimulation has shown promising results in enhancing motor and cognitive recovery both in animal models of stroke and stroke survivors. In this framework, one of the most innovative methods is the bihemispheric transcranial direct current stimulation that simultaneously increases excitability in one hemisphere and decreases excitability in the contralateral one. As bihemispheric transcranial direct current stimulation can create a more balanced modulation of brain activity, this approach may be particularly useful in counteracting imbalanced brain activity, such as in stroke. Given these premises, the aim of the current study has been to explore the recovery after stroke in mice that underwent a bihemispheric transcranial direct current stimulation treatment, by recording their electric brain activity with local field potential and by measuring behavioural outcomes of Grip Strength test. An innovative parameter that explores the complexity of signals, namely the Entropy, recently adopted to describe brain activity in physiopathological states, was evaluated to analyse local field potential data. Results showed that stroke mice had higher values of Entropy compared to healthy mice, indicating an increase in brain complexity and signal disorder due to the stroke. Additionally, the bihemispheric transcranial direct current stimulation reduced Entropy in both healthy and stroke mice compared to sham stimulated mice, with a greater effect in stroke mice. Moreover, correlation analysis showed a negative correlation between Entropy and Grip Strength values, indicating that higher Entropy values resulted in lower Grip Strength engagement. Concluding, the current evidence suggests that the Entropy index of brain complexity characterizes stroke pathology and recovery. Together with this, bihemispheric transcranial direct current stimulation can modulate brain rhythms in animal models of stroke, providing potentially new avenues for rehabilitation in humans.

STN localization using local field potentials based on wavelet packet features and stacking ensemble learning

Background:DBS entails the insertion of an electrode into the patient brain, enabling Subthalamic nucleus (STN) stimulation. Accurate delineation of STN borders is a critical but time-consuming task, traditionally reliant on the neurosurgeon experience in deciphering the intricacies of microelectrode recording (MER). While clinical outcomes of MER have been satisfactory, they involve certain risks to patient safety. Recently, there has been a growing interest in exploring the potential of local field potentials (LFP) due to their correlation with the STN motor territory. Method:A novel STN detection system, integrating LFP and wavelet packet transform (WPT) with stacking ensemble learning, is developed. Initial steps involve the inclusion of soft thresholding to increase robustness to LFP variability. Subsequently, non-linear WPT features are extracted. Finally, a unique ensemble model, comprising a dual-layer structure, is developed for STN localization. We harnessed the capabilities of support vector machine, Decision tree and k-Nearest Neighbor in conjunction with long short-term memory (LSTM) network. LSTM is pivotal for assigning adequate weights to every base model. Results:Results reveal that the proposed model achieved a remarkable accuracy and F1-score of 89.49% and 91.63%. Comparison with existing methods:Ensemble model demonstrated superior performance when compared to standalone base models and existing meta techniques. Conclusion:This framework is envisioned to enhance the efficiency of DBS surgery and reduce the reliance on clinician experience for precise STN detection. This achievement is strategically significant to serve as an invaluable tool for refining the electrode trajectory, potentially replacing the current methodology based on MER.