High Gamma Research Articles

Anterior thalamic nucleus local field potentials during focal temporal lobe epileptic seizures.

To analyze the local field potentials (LFPs) in patients with focal drug-resistant epilepsy (DRE) from the anterior nucleus of the thalamus (ANT) during inter-ictal state and seizure state. ANT stereotactic EEG (SEEG) recordings were studied in four patients with focal temporal lobe epilepsy. SEEG data was classified as inter-ictal and ictal state and sub-categorized into electrographic (ESz), focal aware seizure (FAS), focal with impaired awareness (FIA), or focal to bilateral tonic-clonic seizure (FBTC). LFP was analyzed at 4 Hz, 8 Hz, 16 Hz, 32 Hz, high gamma (100 Hz), and ripples (200 Hz) using spectrogram analysis and a statistical comparison of normalized power spectral density (PSD) averaged during seizures versus pre-ictal baseline segments. The LFP recordings were analyzed for 162 seizures (127 ESz, 23 FAS, 6 FIA, and 6 FBTC). Based on time-frequency data (spectrogram), a broad band of activity, occurring between 2 and 6 Hz and centered at 4 Hz, and thin-band activity occurring specifically at 8 Hz on the frequency spectrogram were observed during the inter-ictal state. Statistically significant changes in LFP-PSD were seen for FAS, FIA, and FBTC. We observed a significant gain in LFP at the lower frequency band during FAS at 4 Hz, FIA, and FBTC at 4, 8, and 16 Hz while also observing increases at higher frequencies during FBTC at 100 and 200 Hz and a decrease during FAS seizures at 32 Hz. In contrast, no significant change in LFP power was seen for electrographic seizures. Our observations from a limited dataset indicate that all clinical seizure types, but not electrographic seizures, caused a change in ANT-LFP based on the magnitude of the associated power spectral density (PSD). Future work will be needed to validate the use of ANT-LFP at these frequencies as accurate measurements of seizure occurrence and severity. This work represents a first step toward understanding ANT thalamic LFP patterns during focal seizures and developing adaptive DBS strategies.

Development of a Time-Resolved Fluorescence Resonance Energy Transfer ultra-high throughput screening assay for targeting SYK and FCER1G interaction.

The spleen tyrosine kinase (SYK) and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) interaction has a major role in the normal innate and adaptive immune responses, but dysregulation of this interaction is implicated in several human diseases, including autoimmune disorders, hematological malignancies, and Alzheimer's Disease. Development of small molecule chemical probes could aid in studying this pathway both in normal and aberrant contexts. Herein, we describe the miniaturization of a time-resolved fluorescence resonance energy transfer (TR-FRET) assay to measure the interaction between SYK and FCER1G in a 1536-well ultrahigh throughput screening (uHTS) format. The assay utilizes the His-SH2 domains of SYK, which are indirectly labeled with anti-His-terbium to serve as TR-FRET donor and a FITC-conjugated phosphorylated ITAM domain peptide of FCER1G to serve as acceptor. We have optimized the assay into 384-well HTS format and further miniaturized the assay into a 1536-well uHTS format. Robust assay performance has been achieved with a Z' factor > 0.8 and signal-to-background (S/B) ratio > 15. The utilization of this uHTS TR-FRET assay for compound screening has been validated by a pilot screening of 2,036 FDA-approved and bioactive compounds library. Several primary hits have been identified from the pilot uHTS. One compound, hematoxylin, was confirmed to disrupt the SYK/FECR1G interaction in an orthogonal protein-protein interaction assay. Thus, our optimized and miniaturized uHTS assay could be applied to future scaling up of a screening campaign to identify small molecule inhibitors targeting the SYK and FCER1G interaction.

Prompt gamma energy integration: a new method for online-range verification in proton therapy with pulsed-beams

Introduction: We propose a method for prompt-gamma verification of proton range during particle therapy, called Prompt-Gamma Energy Integration (PGEI).Method: This method is based on the measurement of the total energy deposited in a set of detectors located around a patient. It is particularly suited in the case of high-instantaneous beam intensities, like for pulsed beams extracted from a synchro-cyclotron. GATE simuations were used to evaluate the sensitivity, and dedicated scintillators were tested as a function of beam intensity.Results and discussion: Simulations show that millimetric range shifts can be measured at a beam-spot scale. The sensitivity is slightly degraded as compared to the Prompt-Gamma Peak Integration Method, for which Time-of-Flight can be employed to reduce the background in single-photon detection conditions at cyclotron accelerators. Experimentally, lead tungstate scintillators have shown to cope with the high instantaneous gamma count rates for PGEI at synchro-cyclotrons.

Performance of new CO2 based mixture in CMS Improved Resistive Plate Chambers in HL-LHC environment

Resistive Plate Chamber (RPCs) detectors in the Compact Muon Solenoid operate with a gas mixture composed of 95.2% of C2H2F4, which provides a high number of ion-electron pairs, 4.5% of iC4H10, which ensures the suppression of photon-feedback effects, and 0.3% of SF6, used as an electron quencher to further operate the detector in streamer-free mode. C2H2F4 is known to be a Greenhouse gas with a global warming potential (GWP) of 1430. Consequently, several ECO-friendly alternatives to C2H2F4 have been investigated in recent years. In this context, a short-mid term approach for the upcoming years of Large Hadron Collider (LHC) operation could be to focus on reducing the GWP of the RPC gas mixture by replacing C2H2F4 with CO2. The studies are conducted at the CERN Gamma Irradiation Facility in the North Area of the Super Proton Synchrotron (SPS), where a 13.6 TBq radiation source and a muon beam from SPS mimic the conditions of Phase-II (i.e. High-Luminosity (HL)) of the LHC. This paper presents the performance of a 1.4 mm gap RPC with three different CO2 based mixtures (30 and 40% of CO2; 0.5 and 1% of SF6) under high gamma background conditions with the perspectives for the longevity campaign.

The Influence of the Sun and Moon on the Observation of Very High Energy Gamma-ray Sources Using EAS Arrays

With great advance of ground-based extensive air shower arrays, such as LHAASO and HAWC, many very high energy (VHE) gamma-ray sources have been discovered and are being monitored regardless of the day and the night. Hence, the Sun and Moon would have some impacts on the observation of gamma-ray sources, which have not been taken into account in previous analysis. In this paper, the influence of the Sun and Moon on the observation of very high energy gamma-ray sources when they are near the line of sight of the Sun or Moon is estimated. The tracks of all the known VHE sources are scanned and several VHE sources are found to be very close to the line of sight of the Sun or Moon during some period. The absorption of very high energy gamma rays by sunlight is estimated with detailed method and some useful conclusions are achieved. The main influence is the block of the Sun and Moon on gamma rays and the shadow on the cosmic ray background. The influence is investigated considering the detector angular resolution and some strategies on data analysis are proposed to avoid the underestimation of the gamma-ray emission.

GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-Resolved EEG Motor Imagery Signals.

Toward the development of effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by an electroencephalogram (EEG) is highly demanded. Traditional works classify EEG signals without considering the topological relationship among electrodes. However, neuroscience research has increasingly emphasized network patterns of brain dynamics. Thus, the Euclidean structure of electrodes might not adequately reflect the interaction between signals. To fill the gap, a novel deep learning (DL) framework based on the graph convolutional neural networks (GCNs) is presented to enhance the decoding performance of raw EEG signals during different types of motor imagery (MI) tasks while cooperating with the functional topological relationship of electrodes. Based on the absolute Pearson's matrix of overall signals, the graph Laplacian of EEG electrodes is built up. The GCNs-Net constructed by graph convolutional layers learns the generalized features. The followed pooling layers reduce dimensionality, and the fully-connected (FC) softmax layer derives the final prediction. The introduced approach has been shown to converge for both personalized and groupwise predictions. It has achieved the highest averaged accuracy, 93.06% and 88.57% (PhysioNet dataset), 96.24% and 80.89% (high gamma dataset), at the subject and group level, respectively, compared with existing studies, which suggests adaptability and robustness to individual variability. Moreover, the performance is stably reproducible among repetitive experiments for cross-validation. The excellent performance of our method has shown that it is an important step toward better BCI approaches. To conclude, the GCNs-Net filters EEG signals based on the functional topological relationship, which manages to decode relevant features for brain MI. A DL library for EEG task classification including the code for this study is open source at https://github.com/SuperBruceJia/ EEG-DL for scientific research.

STaRNet: A spatio-temporal and Riemannian network for high-performance motor imagery decoding

Brain–computer interfaces (BCIs), representing a transformative form of human–computer interaction, empower users to interact directly with external environments through brain signals. In response to the demands for high accuracy, robustness, and end-to-end capabilities within BCIs based on motor imagery (MI), this paper introduces STaRNet, a novel model that integrates multi-scale spatio-temporal convolutional neural networks (CNNs) with Riemannian geometry. Initially, STaRNet integrates a multi-scale spatio-temporal feature extraction module that captures both global and local features, facilitating the construction of Riemannian manifolds from these comprehensive spatio-temporal features. Subsequently, a matrix logarithm operation transforms the manifold-based features into the tangent space, followed by a dense layer for classification. Without preprocessing, STaRNet surpasses state-of-the-art (SOTA) models by achieving an average decoding accuracy of 83.29% and a kappa value of 0.777 on the BCI Competition IV 2a dataset, and 95.45% accuracy with a kappa value of 0.939 on the High Gamma Dataset. Additionally, a comparative analysis between STaRNet and several SOTA models, focusing on the most challenging subjects from both datasets, highlights exceptional robustness of STaRNet. Finally, the visualizations of learned frequency bands demonstrate that temporal convolutions have learned MI-related frequency bands, and the t-SNE analyses of features across multiple layers of STaRNet exhibit strong feature extraction capabilities. We believe that the accurate, robust, and end-to-end capabilities of the STaRNet will facilitate the advancement of BCIs.

Hybrid framework of fatigue: connecting motivational control and computational moderators to gamma oscillations.

There is a need to develop a comprehensive account of time-on-task fatigue effects on performance (i.e., the vigilance decrement) to increase predictive accuracy. We address this need by integrating three independent accounts into a novel hybrid framework. This framework unites (1) a motivational system balancing goal and comfort drives as described by an influential cognitive-energetic theory with (2) accumulating microlapses from a recent computational model of fatigue, and (3) frontal gamma oscillations indexing fluctuations in motivational control. Moreover, the hybrid framework formally links brief lapses (occurring over milliseconds) to the dynamics of the motivational system at a temporal scale not otherwise described in the fatigue literature. EEG and behavioral data was collected from a brief vigilance task. High frequency gamma oscillations were assayed, indexing effortful controlled processes with motivation as a latent factor. Binned and single-trial gamma power was evaluated for changes in real- and lagged-time and correlated with behavior. Functional connectivity analyses assessed the directionality of gamma power in frontal-parietal communication across time-on-task. As a high-resolution representation of latent motivation, gamma power was scaled by fatigue moderators in two computational models. Microlapses modulated transitions from an effortful controlled state to a minimal-effort default state. The hybrid models were compared to a computational microlapse-only model for goodness-of-fit with simulated data. Findings suggested real-time high gamma power exhibited properties consistent with effortful motivational control. However, gamma power failed to correlate with increases in response times over time, indicating electrophysiology and behavior relations are insufficient in capturing the full range of fatigue effects. Directional connectivity affirmed the dominance of frontal gamma activity in controlled processes in the frontal-parietal network. Parameterizing high frontal gamma power, as an index of fluctuating relative motivational control, produced results that are as accurate or superior to a previous microlapse-only computational model. The hybrid framework views fatigue as a function of a energetical motivational system, managing the trade-space between controlled processes and competing wellbeing needs. Two gamma computational models provided compelling and parsimonious support for this framework, which can potentially be applied to fatigue intervention technologies and related effectiveness measures.

Modification of WS2 thin film properties using high dose gamma irradiation

The tunability of the transition metal dichalcogenide properties has gained attention from numerous researchers due to their wide application in various fields including quantum technology. In the present work, WS2 has been deposited on fluorine doped tin oxide substrate and its properties have been studied systematically. These samples were irradiated using gamma radiation for various doses, and the effect on structural, morphological, optical and electrical properties has been reported. The crystallinity of the material is observed to be decreased, and the results are well supported by x-ray diffraction, Raman spectroscopy techniques. The increase in grain boundaries has been supported by the agglomeration observed in the scanning electron microscopy micrographs. The XPS results of WS2 after gamma irradiation show evolution of oxygen, carbon, C=O, W–O and SO4 −2 peaks, confirming the addition of impurities and formation of point defect. The gamma irradiation creates point defects, and their density increases considerably with increasing gamma dosage. These defects crucially altered the structural, optical and electrical properties of the material. The reduction in the optical band gap with increased gamma irradiation is evident from the absorption spectra and respective Tauc plots. The I–V graphs show a 1000-fold increase in the saturation current after 100 kGy gamma irradiation dose. This work has explored the gamma irradiation effect on the WS2 and suggests substantial modification in the material and enhancement in electrical properties.

Minimum spanning tree analysis of EEG resting-state functional networks in schizophrenia

Schizophrenia is a serious and complex mental disease, known to be associated with various subtle structural and functional deviations in the brain. Recently, increased attention is given to the analysis of brain-wide, global mechanisms, strongly altering the communication of long-distance brain areas in schizophrenia. Data of 32 patients with schizophrenia and 28 matched healthy control subjects were analyzed. Two minutes long 64-channel EEG recordings were registered during resting, eyes closed condition. Average connectivity strength was estimated with Weighted Phase Lag Index (wPLI) in lower frequencies: delta and theta, and Amplitude Envelope Correlation with leakage correction (AEC-c) in higher frequencies: alpha, beta, lower gamma and higher gamma. To analyze functional network topology Minimum Spanning Tree (MST) algorithms were applied. Results show that patients have weaker functional connectivity in delta and alpha frequency bands. Concerning network differences, the result of lower diameter, higher leaf number, and also higher maximum degree and maximum betweenness centrality in patients suggest a star-like, and more random network topology in patients with schizophrenia. Our findings are in accordance with some previous findings based on resting-state EEG (and fMRI) data, suggesting that MST network structure in schizophrenia is biased towards a less optimal, more centralized organization.

Nanocomposite Scintillators Loaded With Hafnium Oxide and Phosphorescent Host and Guest for Gamma Spectroscopy.

Gamma sensitive plastic scintillators are of critical importance in the fields of nuclear nonproliferation, medical imaging, and high energy physics. However, there is often a trade-off between high light yield and high loading of high-Z components, both of which play an essential role in gamma ray detection. This work takes advantage of triplet exciton harvesting to increase gamma light yield by utilizing 1,3-di(9H-carbazol-9-yl)benzene and 9,9-dimethyl-9H-fluorene as triplet hosts to facilitate Dexter energy transfer to bis[2-(4,6-difluorophenyl)pyridinato-C2,N](picolinato)iridium(III) (FIrPic), a blue light emitting phosphorescent dye. A plastic scintillator containing 20 wt % MF, 10 wt % mCP, and 2 wt % FIrPic has a high gamma light yield of 14 800 Ph/MeV. Incorporating 20-35 wt % hafnium oxide nanoparticles into this organic matrix results in nanocomposites that demonstrate a gamma photopeak energy resolution of 6.4-9.7% at 662 keV while still retaining a high gamma light yield between 8800 and 10 800 Ph/MeV.

Field-based soil-plant uptake measurements of natural radionuclides for key vegetables and ghaf leaves in Abu Dhabi

With the thriving fossil fuel and nuclear based industries in the nation, radioecology has become necessary for the radiation safety and emergency-preparedness for the United Arab Emirates (UAE). Environmental radiation transport modelling in the UAE and the Arabian Peninsula are severely limited, as we discuss in this paper, due to lack of experiments specific to arid desert climates. To fill the missing gaps in the baseline arid region radioecological database, especially for the soil-plant uptake studies, rigorous field works have been conducted for the first time on the soil and plant in the farms and open fields of the UAE. We present Abu Dhabi based measurements of activity concentrations of radionuclides of natural origins, in soils, key vegetables (cucumber, tomato, and bell pepper), and leaves of ghaf - a prominent native tree. The empirical data are utilized to get the first published estimates of UAE-specific plant-soil concentration ratios (CR), measuring root uptake of radionuclides in nonleafy vegetables and native trees. Such systematic studies are very rare for arid sandy soils. For the 27 samples analyzed, the activity concentrations' (unit Bq kg−1) ranges are: 169–1746 for 40K, 12–19.5 for 226Ra, and 2.7–23.1 for 228Ra. Likewise, wide variability is seen in the averages of concentration ratios also, ranging in 1.05–4.94 for 40K, 0.14–1.82 for 226Ra, and 0.53–2.78 for 228Ra. A net bioaccumulation (concentration ratio >1) of some of these natural radionuclides is found in many samples, but no significant doses or hazard indices are found due to these three radionuclides in the UAE's soils and vegetations. The paper discusses the careful work through tens of field sampling exercises, well controlled sample processing, high resolution gamma spectrometry, and treatment of data from gamma counting rates to accumulated dose rate estimations.

EEG spectral power in developmental coordination disorder and attention-deficit/hyperactivity disorder: a pilot study.

Developmental coordination disorder (DCD) and attention-deficit/hyperactivity disorder (ADHD) overlap in symptoms and often co-occur. Differentiation of DCD and ADHD is crucial for a better understanding of the conditions and targeted support. Measuring electrical brain activity with EEG may help to discern and better understand the conditions given that it can objectively capture changes and potential differences in brain activity related to externally measurable symptoms beneficial for targeted interventions. Therefore, a pilot study was conducted to exploratorily examine neurophysiological differences between adults with DCD and/or ADHD at rest. A total of N = 46 adults with DCD (n = 12), ADHD (n = 9), both DCD + ADHD (n = 8), or typical development (n = 17) completed 2 min of rest with eyes-closed and eyes-open while their EEG was recorded. Spectral power was calculated for frequency bands: delta (0.5-3 Hz), theta (3.5-7 Hz), alpha (7.5-12.5 Hz), beta (13-25 Hz), mu (8-13 Hz), gamma (low: 30-40 Hz; high: 40-50 Hz). Within-participants, spectral power in a majority of waveforms significantly increased from eyes-open to eyes-closed conditions. Groups differed significantly in occipital beta power during the eyes-open condition, driven by the DCD versus typically developing group comparison. However, other group comparisons reached only marginal significance, including whole brain alpha and mu power with eyes-open, and frontal beta and occipital high gamma power during eyes-closed. While no strong markers could be determined to differentiate DCD versus ADHD, we theorize that several patterns in beta activity were indicative of potential motor maintenance differences in DCD at rest. Therefore, larger studies comparing EEG spectral power may be useful to identify neurological mechanisms of DCD and continued differentiation of DCD and ADHD.

Passive single-sphere multi-detector spectrometry system for profiling of neutron fields in the thermal to 20 MeV energy range

This study explores the development and application of a custom-designed single-sphere multi-detector spectrometer (SSMDSS) for characterizing neutron fields. Stray neutrons in reactor and accelerator facilities present complex, energy-diverse fields. Accurately assessing these fields is crucial for personnel safety. The SSMDSS system is designed to address this challenge, offering a compact and passive dosimetry solution for constrained workspaces. We studied the performance of SSMDSS in two environments: radio-nuclide based neutron sources and stray neutron fields at a research reactor hall. Our investigation demonstrates that SSMDSS provide reliable neutron energy distributions. The performance of the SSMDSS was compared with commercially available ROSPEC system. SSMDSS exhibits superior resolution due to its design, leading to a more accurate measurement of low-energy fluence when compared with ROSPEC. This distinction is reflected in various measured parameters, including average energy and fluence-to-dose conversion coefficients. Inside the reactor hall, SSMDSS measured a fluence-to-dose conversion coefficient of 121 pSv.cm2 compared to ROSPEC's 83 pSv.cm2. Additionally, SSMDSS measured a higher average energy (0.25 MeV) compared to ROSPEC (0.14 MeV). While ROSPEC remains a valuable tool for real-time data collection in dynamic fields with high gamma backgrounds, SSMDSS presents itself as a viable alternative for neutron spectrometry in neutron work fields due to its compact design and passive dosimetry capabilities. This makes it particularly suitable for deployment in constrained workspaces with potential stray neutron exposure.

Improving auditory attention decoding by classifying intracranial responses to glimpsed and masked acoustic events

Abstract Listeners with hearing loss have trouble following a conversation in multitalker environments. While modern hearing aids can generally amplify speech, these devices are unable to tune into a target speaker without first knowing to which speaker a user aims to attend. Brain-controlled hearing aids have been proposed using auditory attention decoding (AAD) methods, but current methods use the same model to compare the speech stimulus and neural response, regardless of the dynamic overlap between talkers which is known to influence neural encoding. Here, we propose a novel framework that directly classifies event-related potentials (ERPs) evoked by glimpsed and masked acoustic events to determine whether the source of the event was attended. We present a system that identifies auditory events using the local maxima in the envelope rate of change, assesses the temporal masking of auditory events relative to competing speakers, and utilizes masking-specific ERP classifiers to determine if the source of the event was attended. Using intracranial electrophysiological recordings, we showed that high gamma ERPs from recording sites in auditory cortex can effectively decode the attention of subjects. This method of AAD provides higher accuracy, shorter switch times, and more stable decoding results compared with traditional correlational methods, permitting the quick and accurate detection of changes in a listener’s attentional focus. This framework also holds unique potential for detecting instances of divided attention and inattention. Overall, we extend the scope of AAD algorithms by introducing the first linear, direct-classification method for determining a listener’s attentional focus that leverages the latest research in multitalker speech perception. This work represents another step toward informing the development of effective and intuitive brain-controlled hearing assistive devices.

Functional Connectivity Alterations in Patients with Post-stroke Epilepsy Based on Source-level EEG and Graph Theory.

We investigated the differences in functional connectivity based on the source-level electroencephalography (EEG) analysis between stroke patients with and without post-stroke epilepsy (PSE). Thirty stroke patients with PSE and 35 stroke patients without PSE were enrolled. EEG was conducted during a resting state period. We used a Brainstorm program for source estimation and the connectivity matrix. Data were processed according to EEG frequency bands. We used a BRAPH program to apply a graph theoretical analysis. In the beta band, radius and diameter were increased in patients with PSE than in those without PSE (2.699 vs. 2.579, adjusted p = 0.03; 2.261 vs. 2.171, adjusted p = 0.03). In the low gamma band, radius was increased in patients with PSE than in those without PSE (2.808 vs. 2.617, adjusted p = 0.03). In the high gamma band, the radius, diameter, average eccentricity, and characteristic path length were increased (1.828 vs. 1.559, adjusted p < 0.01; 2.653 vs. 2.306, adjusted p = 0.01; 2.212 vs. 1.913, adjusted p < 0.01; 1.425 vs. 1.286, adjusted p = 0.01), whereas average strength, mean clustering coefficient, and transitivity were decreased in patients with PSE than in those without PSE (49.955 vs. 55.055, adjusted p < 0.01; 0.727 vs. 0.810, adjusted p < 0.01; 1.091 vs. 1.215, adjusted p < 0.01). However, in the delta, theta, and alpha bands, none of the functional connectivity measures were different between groups. We demonstrated significant alterations of functional connectivity in patients with PSE, who have decreased segregation and integration in brain network, compared to those without PSE.

The Devonian clastic wedge and underlying strata of southwestern Canadian Arctic Archipelago: stratigraphic revisions

The Devonian clastic wedge (DCW) and underlying carbonate platforms and basinal mudrocks of the study area are re-examined using legacy seismic data and X-ray fluorescence surveys of borehole chip samples. The Ordovician–Devonian basinal succession of Melville Island is consolidated under the name Ibbett Bay Group within the Northwest Territories, whereas equivalent strata in Nunavut are grouped into the Cape Phillips Formation. The Kitson Formation black shale is correlative with the upper Ibbett Bay Group. Six horizons with high TOC and high gamma response are traced in the Ordovician–Devonian, with the fourth (4a) approximating the Silurian/Devonian boundary; the upper two (4b, 5) are Emsian and Eifelian. In the direction of progradation, the base of Kitson Formation rises stratigraphically from gamma horizon 4a to 5. The upper Kitson represents basinal toes of westward prograding DCW clinoforms. The Blackley and Cape de Bray formations of Embry and Klovan (Embry, A.F., and Klovan, J.E. 1976. The middle-upper devonian clastic wedge of the franklinian geosyncline. Bulletin of Canadian Petroleum Geology, 24: 485–639. https://pubs.geoscienceworld.org/cspg/bcpg/article/24/4/485/57135) are not traceable enough to warrant their formation rank. We revert to the original usage of Tozer and Thorsteinsson (Tozer, E.T., and Thorsteinsson, R. 1964. Western Queen Elizabeth Islands, Arctic Archipelago. Geological Survey of Canada, Memoir 332: 242 p. doi:10.4095/100556) where these units are members within the Weatherall Formation. The distinctive seismic character of the Cape de Bray in western and central Melville Island warrants its recognition as a formal member; elsewhere, it is informal as it cannot be consistently traced. The Blackey is treated as a formal member in an outcrop area of ∼2000 km 2 where it was defined; it is not recognized in the subsurface. Onset of the DCW is tentatively linked to flexural subsidence and crustal thickening caused by the Romanzof Orogeny in the hinterland.

Optical properties of thin films monitored in real-time at high gamma radiation doses using long period fiber gratings

In this work, we report an all-optical-fiber-based method to monitor in real-time the changes in thin film optical properties when exposed to harsh environments such as high doses of gamma radiation. The method is based on a long period grating (LPG) inscribed in a radiation resistant optical fiber, which is coated with a thin film to be analyzed. Due to impact of the environment on the film properties, the transmission spectrum of the LPG changes. To validate this methodology, we deposited oxides of various metals, i.e. aluminum (Al2O3), titanium (TiO2), and tantalum (Ta2O5), as well as a polymeric film, namely polystyrene (PS), on the LPG surface and measured the resonant wavelength shift induced by high doses of gamma exposure (dose rate of 2.3 kGy/h, up to a total dose of 46 kGy). The changes could be observed in real-time up to maximum reached dose and during the recovery period. The results are significantly dependent on thin film material. Among the oxides, TiO2 thin film demonstrated the highest susceptibility to irradiation, whereas Al2O3 exhibited the least impact. Additionally, a good recovery potential for Ta2O5 thin film was observed, hinting at its promising application in dosimetry. Conversely, the PS film exhibited a permanent effect induced by irradiation. This is the first real-time experimental study of the impact of high dose gamma radiation on thin film optical properties using a universal optical-fiber-based device. The findings pave the way for assessing radiation hardness of thin film materials or utilizing such a method to optimize material treatment involving ionizing radiation.

Growth and characterization of 6LiI:Ag crystal scintillators for thermal and epithermal neutron detection on the lunar surface

This paper discusses crystal growth and characterization of 1.0-inch 6LiI:Ag scintillators for thermal and epithermal neutron detection on the lunar surface as part of the Lunar Vehicle Radiation Dosimeter project. Zone purification method was employed to purify the raw material of 6LiI, and the crystals were grown using the Bridgman method. X-ray luminescence spectrum was measured to confirm the presence of Ag+ in the crystal lattice of 6LiI. The feasibility of neutron detection under 252Cf fast neutron irradiation was investigated. A hydrogen-rich paraffin wax moderator was used to slow down fast neutrons to obtain thermal and epithermal neutrons. The charge comparison method was used to perform pulse shape discrimination. The maximum value of the Figure of Merit was obtained to be 1.3, which demonstrates the capability of using 6LiI:Ag crystal scintillators in high neutron and gamma mixed fields. The energy resolution of the thermal neutron peak varied with the thickness of scintillators, achieving 12.0 % for the 0.5 cm thick samples. The potential for further improvement of the scintillation performance of 6LiI:Ag crystal relies on reducing impurities and color centers.

NaI gamma camera performance for high energies: Effects of crystal thickness, photomultiplier tube geometry and light guide thickness.

Gamma camera imaging, including single photon emission computed tomography (SPECT), is crucial for research, diagnostics, and radionuclide therapy. Gamma cameras are predominantly based on arrays of photon multipliers tubes (PMTs) that read out NaI(Tl) scintillation crystals. In this way, standard gamma cameras can localize ɣ-rays with energies typically ranging from 30 to 360keV. In the last decade, there has been an increasing interest towards gamma imaging outside this conventional clinical energy range, for example, for theragnostic applications and preclinical multi-isotope positron emission tomography (PET) and PET-SPECT. However, standard gamma cameras are typically equipped with 9.5mm thick NaI(Tl) crystals which can result in limited sensitivity for these higher energies. Here we investigate to what extent thicker scintillators can improve the photopeak sensitivity for higher energy isotopes while attempting to maintain spatial resolution. Using Monte Carlo simulations, we analyzed multiple PMT-based configurations of gamma detectors with monolithic NaI (Tl) crystals of 20 and 40mm thickness. Optimized light guide thickness together with 2-inch round, 3-inch round, 60×60 mm2 square, and 76×76 mm2 square PMTs were tested. For each setup, we assessed photopeak sensitivity, energy resolution, spatial, and depth-of-interaction (DoI) resolution for conventional (140keV) and high (511keV) energy ɣ using a maximum-likelihood algorithm. These metrics were compared to those of a "standard" 9.5mm-thick crystal detector with 3-inch round PMTs. Estimated photopeak sensitivities for 511keV were 27% and 53% for 20 and 40mm thick scintillators, which is respectively, 2.2 and 4.4 times higher than for 9.5mm thickness. In most cases, energy resolution benefits from using square PMTs instead of round ones, regardless of their size. Lateral and DoI spatial resolution are best for smaller PMTs (2-inch round and 60×60 mm2 square) which outperform the more cost-effective larger PMT setups (3-inch round and 76×76 mm2 square), while PMT layout and shape have negligible (<10%) effect on resolution. Best spatial resolution was obtained with 60×60 mm2 PMTs; for 140keV, lateral resolution was 3.5mm irrespective of scintillator thickness, improving to 2.8 and 2.9mm for 511keV with 20 and 40mm thick crystals, respectively. Using the 3-inch round PMTs, lateral resolutions of 4.5 and 3.9mm for 140keV and of 3.5 and 3.7mm for 511keV were obtained with 20 and 40mm thick crystals respectively, indicating a moderate performance degradation compared to the 3.5 and 2.9mm resolution obtained by the standard detector for 140 and 511keV. Additionally, DoI resolution for 511keV was 7.0 and 5.6mm with 20 and 40mm crystals using 60×60 mm2 square PMTs, while with 3-inch round PMTs 12.1 and 5.9mm were obtained. Depending on PMT size and shape, the use of thicker scintillator crystals can substantially improve detector sensitivity at high gamma energies, while spatial resolution is slightly improved or mildly degraded compared to standard crystals.