Multichannel Analyzer Research Articles

Theta power reduction and theta–gamma coupling desynchronization are associated with working memory interference and anxiety symptoms in panic disorder: a retrospective study

BackgroundTheta-gamma coupling (TGC) describes the modulation of gamma oscillations by the theta phasic activity, which is crucial for processes such as the ordering of information during working memory (WM) performance. The mental arithmetic (MA), which involves performing calculations with numbers, is a crucial tool for evaluating and understanding the sensory processing and management abilities of WM. Evaluating TGC may provide greater insight into the neural mechanisms mediating WM deficits in panic disorder (PD).MethodsMedical and electroencephalography (EEG) records of psychiatric outpatient clinic between 1 March 2020 and 30 September 2023 were retrospectively reviewed. A total of 34 PD patients and 34 age- and sex-matched healthy controls (HCs) underwent EEG to assess the overall functional interaction of the brain using multi-channel EEG analysis, focusing on specific brain regions including the frontal, temporal, parietal, and occipital lobes. EEG recordings were conducted during two sessions: a 5-min eyes-closed resting-state (RS) and a subsequent 5-min eyes-closed MA. The TGC and the spectral power of the theta and gamma frequency bands, which are well known to be associated with WM, were analysed.ResultsCompared to those in HCs, TGC and theta power were significantly attenuated in PD patients. When analysing both HCs and PD patients together, RS TGC and relative theta power were negatively correlated with state anxiety and perceived stress scores, respectively. In contrast, TGC and relative theta power during the MA condition were positively correlated with the MA performance. Specifically, in PD patients, RS theta power across all electrodes was significantly negatively correlated with the Hamilton Anxiety Scale (HAMA) score. Linear regression analysis revealed that theta power in the T5 channel remained negatively correlated with pathological anxiety as measured by the HAMA score, even after controlling for other confounding factors.ConclusionsThis study highlights significant alterations in TGC and theta power in PD patients. PD patients exhibit reduced TGC and theta power compared to HCs, indicating deficits in the neural mechanisms underlying anxiety and/or WM in PD. These insights contribute to a better understanding of the neural basis of WM deficits in PD and suggest potential avenues for targeted therapeutic interventions.

Seismic Data Reconstruction Via A Hybrid CNN-Low-Rank Method

Convolutional Neural Networks (CNNs) have shown promising results in seismic data reconstruction due to their exceptional ability to extract local features. However, incomplete seismic data may impede CNNs’ ability to discern meaningful features, leading to a degradation of reconstruction performance. Therefore, we propose a hybrid CNN-Low-Rank (CNN-LR) method which leverages Low-Rank (LR) techniques to recover data structure information, followed by detail refinement using a plug-and-play (PnP) trained CNN within an iterative framework. This approach utilizes LR techniques to restore inherent structural information, compensating for the absence of local information, thereby enabling CNNs to infer missing traces more accurately. Specifically, we first train a network to learn the mapping from low-rank recovered data patches with randomly selected rank parameters to complete data patches. Next, we incorporate the PnP trained CNN into an iterative framework, where low-rank recovery and network refinement are interleaved within each iteration. This creates a continuous reconstruction process until a termination condition is met. Performance evaluations of our proposed algorithm, conducted on synthetic and field datasets with a high missing trace ratio, demonstrate its superiority over the traditional low-rank method (multi-channel singular spectrum analysis, MSSA) and CNN-based method (U-net). Moreover, our approach shows strong performance in reconstructing large contiguous gaps and handling higher-dimensional seismic data (including 3D and 5D), broadening its applicability and robustness in practical seismic data reconstruction tasks.

Enhanced Peat Profiling with Electrical Resistivity Tomography and Multichannel Analysis of Surface Wave

Enhanced Peat Profiling with Electrical Resistivity Tomography and Multichannel Analysis of Surface Wave

Spatial and temporal changes in small-strain shear modulus of geogrid-stabilized crushed aggregate materials

Geogrid stabilization can be used by transportation agencies to build durable roadways over soft subgrade soil. The performance of geogrid stabilization is highly dependent on the properties of the geogrid material, the aggregate material, and the interaction between the two materials when combined. Therefore, transportation agencies need to perform their own studies to assess the performance of geogrid stabilization for their local materials. Additionally, the current knowledge base needs to be continually expanded to a variety of aggregate-geosynthetic composites to develop performance-based design methods for geosynthetic-stabilization. This study evaluates the long-term performance of two geogrids used to stabilize a crushed aggregate material. A full-scale traffic loading system was built to simulate a full half-axle (40kN) traffic load for thousands of load cycles. Two trials were completed using the same crushed aggregate material. For each trial, two geogrid-stabilized sections, and one control section were evaluated. The performance of the test sections was monitored for 4000 load cycles by measuring surface rutting and completing multichannel analysis of surface waves (MASW) to measure aggregate stiffness. Results showed that the geogrid-stabilized sections had better long-term performance than the control sections with lower degradation of the as-built aggregate stiffness. There was good agreement amongst the MASW results, rutting measurements, and Shakedown analysis. It has been concluded that MASW is an effective method for evaluating the long-term performance of geogrid stabilization in aggregate layers with a customized instrumentation plan according to the targeted measurements.

Novel method to estimate horizontal variability of shear wave velocity through multichannel analysis of surface waves

Scale of fluctuations (SOFs) of spatially variable soil properties have been regarded as one of the important parameters for performing reliability-based design in geotechnical engineering. However, the information required to estimate the SOFs in practice is limited, especially in the horizontal direction. In this study, the potential use of Multichannel Analysis of Surface Waves (MASW) to estimate the SOFs of shear wave velocity (VS) in horizontal direction is investigated through a series of numerical investigations. 2D random field models with a vertically increasing trend of VS were first simulated with different levels of variability controlled by the coefficient of variation (COV) and SOF. Afterwards, a large number of numerical MASW tests were performed using a 2D finite difference method, where the survey lines were progressively shifted. Results show that the COV of VS can be determined from the scatter of the dispersion curves, whereas the horizontal SOF of VS can be appropriately estimated from the phase velocity profile presented in the wavelength form. Additionally, in-situ MASW tests were conducted to estimate the horizontal SOF, and the obtained results align with those estimated by different methods. It is highlighted that the accuracy of the estimation depends on survey length. The interpretation using a long array reflects an averaged site condition of the survey area, thus losing the variability information. Favorable predictions are produced when survey length is shorter than 1.0 SOF. However, it should be noted that use of short survey length may limit the depth of investigation.

Estimation of shear wave velocity using rock mass property of Gemlik, Turkey

ABSTRACT It is often required to evaluate the shear wave velocity (V s ) of the sub-soil stratification for the seismic site characterisation and various engineering applications where the dynamic forces are acting on the foundation. Different correlations are available based on the Standard Penetration Test (SPT) for this purpose when the sub-soil stratification consists of soil. However, limited studies were performed to develop such correlations in case of weathered and fractured rock formations. In this paper, a correlation is developed between the depth of measurement, shear wave velocity, and Rock Mass Rating (RMR) based on Multichannel Analysis of Surface Waves (MASW) test, and the borehole data conducted in the Gemlik region of Turkey. The accuracy of the proposed correlation is checked using different statistical plots and found to be acceptable for the evaluation of V s . This correlation can be used by the practicing engineers for the preliminary estimate of V s in a fractured rock mass based on the borehole information and laboratory testing in absence of dynamic field testing for this region. Based on the findings from this study, V s is observed to be increasing with an increase in depth of investigation and RMR in a fractured rock mass of Gemlik, Turkey.

Hospital care trajectories of older adults with cancer and the associated clinical profiles.

The longitudinal hospital care experiences of older adults with cancer, from the treatment decision-making process until their end of life, remain unexplored. We examined the hospital care trajectories of these patients and identified associated clinical determinants. We linked the ELCAPA multicenter cohort study (patients aged ≥70 with a solid tumor and having been referred for a geriatric assessment between 2012 and 2019) and the Greater Paris University Hospitals' clinical data warehouse. Individual care trajectories, defined as series of consultations, hospital admissions (in day, acute, or rehabilitation units), and emergency room (ER) visits, were clustered using multichannel sequence analysis. Cluster membership determinants were identified among socio-demographic, oncological, and geriatric parameters by logistic regression analysis. Seven hundred seven patients (median age: 82; metastatic cancer: 45.2%; 10 998 care episodes) were included. Four trajectory clusters were identified: cluster A (n = 149, 21.1%) with in-hospital surgical trajectories, cluster B (n = 198, 28.0%) with outpatient care trajectories with chemotherapy and/or radiotherapy, cluster C (n = 302, 42.7%) without any hospital cancer treatments, and cluster D (n = 58, 8.2%) with mostly chemotherapy and high hospital care consumption. Cluster belonging determinants included metastatic status and cancer site (for cluster A); cognition, mobility, and mood status (unimpaired parameters for cluster B and impaired for cluster C); and younger age (for cluster D). While highlighting varied hospital care experiences among older patients with cancer, we found that age remains an independent determinant of chemotherapy-dominant care trajectories.

Experimental investigation of the radial structure of energetic particle driven GAM in TCV

Abstract High amplitude energetic particle geodesic acoustic mode (EGAM) oscillations driven by Neutral Beam (NBI) injected in the direction counter to the toroidal plasma current are observed in the TCV tokamak. The modes appear at frequencies close to the geodesic acoustic mode (GAM) frequency, corresponding to the mode radii calculated without plasma elongation corrections. The spatial structure of the EGAM density oscillation is analyzed using multichannel Soft X-Ray (SXR) and broadband light emission diagnostics. The analysis of spatiotemporal emission data shows a non-rotating structure of the density oscillations. The non-rotating mode discrimination is the additional new capability of the multichannel spatiotemporal SXR data analysis technique in TCV. We present the discrimination method of assessing the standing character of the EGAM wave. The structure of EGAM density oscillations in TCV is consistent with the theoretical GAM poloidal structure, namely a m=1 standing wave with density oscillations amplitude proportional to sin(θ), where the poloidal angle θ is measured from the equatorial plane. The poloidal structure of magnetic the field oscillations is analyzed using a poloidal array of magnetic coils. The structure of the EGAM-induced magnetic field oscillations in TCV is a m=2 standing wave. Time evolution of EGAMs suggests that a nonlinear EGAM chirping is observed. The chirping depends on the EGAM radial location, which varies as the NBI deposition is varied through a vertical shift of the plasma magnetic axis. The chirping disappears at the plasma periphery. A fast periodic radial shift of the EGAMs radial location is also observed to occur during the single chirp.

Educational assortative mating and couples’ linked occupational trajectories in China

Educational assortative mating profoundly influences couples' division of labor; however, we know little about how it shapes couples' paired occupational trajectories. We employed multi-channel sequence analysis to discern types of couples' linked occupational trajectories based on the couple-level data from China Labor-force Dynamics Survey (CLDS), and multinomial logistic models to examine how educational assortative mating is associated with couples' occupational trajectories. For most occupational types, husbands had more advantaged or at least similar occupational trajectories than their wives. Couples in educational hypergamy were likely to have occupational trajectory types with husbands having some advantages; couples in educational hypogamy were likely to have occupational trajectory types with wives having some advantages. The specialization and resource bargaining perspectives provide more powerful explanations than the “doing gender” perspective. Chinese couples tend to choose the occupational arrangement that maximizes the family's economic interests rather than the one that best conforms to gender norms and expectations.

Gap filling between GRACE and GRACE-FO missions: assessment of interpolation techniques

We propose a benchmark for comparing gap-filling techniques used on global time-variable gravity field time-series. The Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On missions provide products to study the Earth’s time-variable gravity field. However, the presence of missing months in the measurements poses challenges for understanding specific Earth processes through the gravity field. We reproduce, adapt, and compare satellite-monitoring and interpolation techniques for filling these missing months in GRACE and GRACE Follow-On products on a global scale. Satellite-monitoring techniques utilize solutions from Swarm and satellite laser ranging, while interpolation techniques rely on GRACE and/or Swarm solutions. We assess a wide range of interpolation techniques, including least-squares fitting, principal component analysis, singular spectrum analysis, multichannel singular spectrum analysis, auto-regressive models, and the incorporation of prior data in these techniques. To inter-compare these techniques, we employ a remove-and-restore approach, removing existing GRACE products and predicting missing months using interpolation techniques. We provide detailed comparisons of the techniques and discuss their strengths and limitations. The auto-regressive interpolation technique delivers the best score according to our evaluation metric. The interpolation based on a least-squares fitting of constant, trend, annual, and semi-annual cycles offers a simple and effective prediction with a good score. Through this assessment, we establish a starting benchmark for gap-filling techniques in Earth’s time-variable gravity field analysis.

Revealing the synergistic contribution of PWV and CAPE to extreme precipitation throughout China

Precipitable water vapor (PWV) and convective available potential energy (CAPE) are two key variables affecting the formation and persistence of rainfall. Most previous studies only independently and qualitatively analyzed the long-term relationship between PWV/CAPE and extreme precipitation, but their synergistic contribution of PWV and CAPE to extreme precipitation (EP) was rarely investigated. Therefore, a novel model named PCEP (comprising PWV, CAPE, and EP), that integrates Global Navigation Satellite System (GNSS)-derived PWV and the fifth-generation ECMWF reanalysis (ERA5)-derived CAPE, is proposed in this study, where the joint contribution of PWV and CAPE on EP was investigated. Precipitation data is derived from the China Meteorological Administration (CMA). The daily PWV, CAPE and precipitation from 219 GNSS collocated meteorological stations in China from 2011 to 2018 were collected to perform the PCEP model. The tendency and periodic information of the three variables were revealed based on the multichannel singular spectral analysis and Lomb-scale methods. Moreover, the power-law relationships of PWV to loge(EP) varied with the seasons in China, while the linear relationships existed between loge(CAPE) and loge(EP). Finally, to solve the collinearity issue among PWV, CAPE and EP that occurred on the regional scale, the partial least square (PLS) method was first introduced to investigate their relationships on the seasonal scale. The PLS method found that PWV and CAPE also complement each other to EP on the seasonal scale, on the basis of regional complementarity. Additionally, the qualitative relationship between PWV, CAPE and the frequency of EP was elucidated. These results showed that the close relationships between high PWV and CAPE and the intensity and frequency of EP events on the annual and seasonal scales throughout China.

ABRASION INVESTIGATION USING SHEAR WAVE VELOCITY AND POISSON’S RATIO APPROACHES IN URAI VILLAGE NORTH BENGKULU REGENCY

The coastal areas of North Bengkulu Regency, particularly Urai Village, have been severely impacted by widespread abrasion, posing a high risk of coastal erosion within Bengkulu Province. This study aims to assess the extent of coastal degradation and support disaster mitigation efforts by investigating the properties and structure of rocks using geophysical methods, specifically the Multichannel Analysis of Surface Waves (MASW). The research focuses on determining shear wave velocity (Vs) to model the rock layers and produce a stratigraphic profile with a minimal misfit value. The obtained Vs30 values, ranging from 146 m/s to 603 m/s, indicate that the coastal region primarily comprises soft soils, which are highly susceptible to deformation, including abrasion. These findings provide essential data for understanding the underlying causes of coastal erosion and contribute to future disaster mitigation strategies.

Seismic Site Characterization of Coimbatore city, Tamil Nadu, India using the Multi-channel Analysis of Surface Waves (MASW) test and Correlations between shear-wave velocity and SPT - N

Seismic Site Characterization involves the qualitative assessment of top-soil properties that have the capability of amplifying the generated earthquake ground motions. The geotechnical properties of topsoil refer to the top 30-m subsurface profile which plays a vital role in seismic microzonation and Ground Response Analysis (GRA) studies. Among various geotechnical parameters, shear-wave velocity (Vs) of the top 30 m subsurface is mainly linked to seismic site characterization and amplification studies. The average shear-wave velocity of the top 30 m subsurface, Vs(30), has been used for seismic site classification in accordance with the National Earthquake Hazard Reduction Program (NEHRP) and various building codes. In this study, an attempt has been made to retrieve the geospatial variation of average shear-wave velocity for Coimbatore city using the active Multi-channel Analysis of Surface Waves (MASW) test which is one of the non-destructive geophysical tests. To retrieve the spatial distribution of shear-wave velocity (Vs), the test was carried out at 35 locations in the vicinity of important structures, schools, colleges, and hospitals within the city. The seismic records have been acquired in the field and analyzed using the winMASW software. From the one-dimensional MASW test, the study area has an average Vs(30) in the range of 640 m/s to 909 m/s and has been classified as site-class “BC” (soft rock) according to NEHRP standards. These test results have been validated using the collected SPT bore log data from various locations, including 40 sites in the vicinity of the conducted MASW tests. The site-specific correlation between the shear-wave velocity (Vs) and the corrected SPT N- Value, N1(60), and between Vs and shear modulus (G) have been developed for Coimbatore city with a regression coefficient of 0.79 and 0.83 respectively. From the fundamental site period map, the study area has a site period in the range of 0.1 to 0.2 s, which indicates that 1- to 2- storey buildings that are densely distributed throughout the city may lead to damage in case of probable future earthquakes. This study bridges the connectivity from the evaluated bedrock acceleration using the Seismic Hazard Analysis (SHA) and provides insights for evaluating surface acceleration using GRA studies.

Estimation of shallow structure along the hinagu fault by applying seismic interferometry to DAS observations conducted along national route 3 in Kumamoto prefecture, Japan

Distributed acoustic sensing (DAS) is a newly developed geophysical observation method and has attracted wide attention in seismology for realizing ultra-high-density observations. DAS uses fiber-optic cables and measures the strain at every point along the cable. This advantage renders DAS an effective tool for investigating near-surface geotechnical properties. Near fault zones, it is important to obtain detailed geotechnical information in advance because of the potential for significant damage in an earthquake. In this study, we recorded continuous ground motion for approximately 1 month using a 40 km-long fiber-optic communication cable running under National Route 3 in Kumamoto Prefecture, Japan. The cross-correlation function (CCF) was calculated using ambient noise, and three-station interferometry was applied to improve the signal-to-noise ratio of the CCF. Using the reconstructed CCF between channels, we calculated the dispersion curves by conducting multichannel surface wave analysis and estimated the one-dimensional velocity structure of each section from the fundamental modes of the dispersion curves. We obtained the detailed shallow S-wave velocity structure to a depth of 180 m along the Hinagu Fault for approximately 2.5 km. The obtained velocity structure showed that the low-velocity region increased abruptly with depth from the center to the latter half of the analyzed section. This velocity change occurs when the national highway running parallel to the fault gradually leaves the fault, suggesting a structural change from solid volcanic layers to thick shallow sedimentary layers derived from the Yatsushiro Plain.Graphical abstract

Integrating deep learning and discrete cosine transform for surface waves full waveform inversion

Summary Accurate estimations of near-surface S-wave velocity (Vs) models hold particular significance in geological and engineering investigations. On the one hand, the popular Multichannel Analysis of Surface Waves (MASW) is limited to the 1D and the plane wave assumptions. On the other hand, the more advanced and computationally expensive full-waveform inversion (FWI) approach is often solved within a deterministic framework that hampers an accurate uncertainty assessment and makes the final predictions heavily reliant on the starting model. Here we combine deep learning with Discrete Cosine Transforms (DCT) to solve the FWI of surface waves and to efficiently estimate the inversion uncertainties. Our neural network approach effectively learns the inverse non-linear mapping between DCT-compressed seismograms and DCT-compressed S-velocity models. The incorporation of DCT into the deep learning framework provides several advantages: it notably reduces parameter space dimensionality and alleviates the ill-conditioning of the problem. Additionally, it decreases the complexity of the network architecture and the computational cost for the training phase compared to training in the full domain. A Monte Carlo simulation is also used to propagate the uncertainties from the data to the model space. We first test the implemented inversion method on synthetic data to showcase the generalization capabilities of the trained network and to explore the implications of incorrect noise assumptions in the recorded seismograms and inaccurate wavelet estimations. Further, we demonstrate the applicability of the implemented method to field data. In this case, available borehole information is used to validate our predictions. In both the synthetic and field applications, the predictions provided by the proposed method are compared with those of a deterministic FWI and the outcomes of a network trained in the full data and model spaces. Our experiments confirm that the implemented deep-learning inversion efficiently and successfully solves the FWI problem and yields more accurate and stable results than a network trained without the DCT compression. This opens the possibility to efficiently train a neural network that provides accurate instantaneous predictions of Vs near-surface models and related uncertainties.

Leveraging Sales Data Analytics to Optimize Pharmaceutical Drug Launches: A Technical Analysis

This technical article quantifies the impact of sales data analytics on pharmaceutical drug launch optimization through advanced predictive modeling and real-time market analysis. The article examines data from 150 drug launches between 2018-2023, analyzing the correlation between analytics implementation and market success. Findings demonstrate that machine learning models reduce forecast variance from ±25% to ±8%, while real-time analytics processing 2.5 million data points per cycle enables 72-hour market response times. Advanced analytics platforms achieve 89% accuracy in predicting prescriber value through multi-channel engagement analysis. The article reveals that integrating AI-driven territory optimization improves field force efficiency by 34%, while automated data validation achieves 99.8% accuracy. Implementation results show consistent outperformance across key metrics, including a 45% higher market penetration rate and a 23% improvement in launch trajectories compared to traditional approaches.

SERS-Encoded Nanoprobes Based on Silver-Coated Gold Nanorods for Cell Sorting.

Optically-encoded probes have great potential for applications in the fields of biosensing and imaging. By employing specific encoding methods, these probes enable the detection of multiple target molecules and high-resolution imaging within the same sample. Among the various encoding methods, surface-enhanced Raman scattering (SERS) spectral encoding stands out due to its extremely narrow linewidth. Compared to fluorescence spectral encoding, SERS encoding significantly reduces crosstalk between adjacent peaks, thereby achieving a larger encoding capacity and enabling multi-channel parallel analysis. This article presents the design and construction of two novel sets of SERS-encoded probes based on noble metal core-shell nanostructures. Two different encoding strategies are successfully applied to encode the SERS spectra of the probes: 1D encoding based on the wavenumber of characteristic peaks in the SERS spectrum, and 2D encoding combining both wavenumber and intensity of characteristic peaks in the SERS spectrum. In addition, this study also demonstrates the potential application of 1D encoded probes in cell sorting. These studies verify the feasibility of applying these two encoding methods to SERS core-shell probes and provide new insights into the construction of optically encoded probes.

Experimental investigation on treating dredged silt ground using vibratory probe compaction combined with well-point dewatering

This study improved the vibratory probe compaction (VPC) technique by combining it with well-point dewatering to address the challenges of treating newly dredged silt ground. Specific methods were presented to determine the operating frequency based on multi-channel analysis of surface waves (MASW) results, as well as the spacing between compaction points derived from vertical vibration velocity measurements. The effects of well-point dewatering were analyzed through field monitoring of groundwater level, pore water pressure, and ground settlement. A comparative evaluation of the reinforcement of the improved and conventional VPC techniques was conducted through in-situ tests. The results indicate that continuous dewatering suppresses the excessive rise of excess pore water pressure during compaction, effectively eliminating equipment tilting and settlement due to sandblasting water, and enhancing construction efficiency by over 40%. The average standard penetration blow count (N 63.5) increases from 4.3 to 11.4, the ground bearing capacity reaches 140.8 kPa and the average ground settlement is 42.5 cm. The cone resistance and sleeve resistance also exhibit higher values, and the risk of soil liquefaction is effectively eliminated. The experiments and practices provide some successful experiences for the wider application of this technique in similar newly reclamation grounds.

Novel fast full-wavefield modeling of air-coupled surface waves and its implications for non-contact pavement testing

We present a novel approach for deriving and modeling air-coupled surface waves with applications in non-contact non-destructive testing (NDT). It is based on the fast Fourier-Bessel series system in conjunction with the unconditionally stable dual-variable and position matrix method. Parametric studies, including sensitivity analysis, are conducted to assess the feasibility of using non-contact air-coupled measurements for pavement testing, focusing on Green's functions, time-domain waveforms, and experimental frequency-velocity spectra (FVS, i.e., the estimated Green's functions from acquired truncated wavefield). The predicted experimental FVS presented in this study are synthetic dispersion images, which are distinguished from the measured experimental FVS (i.e., measured dispersion images from multichannel analysis of surface wave (MASW) test). With the derived complete solution of air-coupled dynamic responses, we find that: (1) Striking similarities between the theoretical Green's functions of vertical displacement (on the pavement surface) and pressure (in the air), as well as in their corresponding experimental FVS. (2) The proposed accurate and efficient full-wave modeling of air-coupled surface waves avoids the need for good contact between geophones/accelerometers and pavement surface. This facilitates direct inversion of shear wave velocity profiles by fitting the predicted experimental FVS to the measured one. (3) Sensitivity analysis demonstrates no significant loss of information in the pressure measured in the air, supporting the feasibility of using non-contact measurement for non-destructive testing. These results suggest that non-contact air-coupled measurements hold great promise as a viable alternative to contact measurements in non-destructive testing.

Experimental and theoretical study on the physico-mechanical characteristics and radiation shielding capability of hardened alumina sludge waste-cement pastes containing MnFe2O4-nanoparticles

This research investigates the impact of incorporating low-cost MnFe2O4 spinel nanoparticles (MF-NPs) at varying concentrations (0.5, 1, and 2 mass%) on the mechanical and physical properties of blended cement pastes. These pastes were produced by replacing different proportions (5, 10, and 15 mass%) of ordinary Portland cement (OPC) with activated alumina sludge waste (AAS), to promote sustainability. Also, the research examined the gamma radiation shielding effectiveness of certain hardened composites against a 137Cs gamma radiation source with an energy of 661.64 keV using a NaI (Tl) detector (Oxford Model) with 3″ × 3″, amplifier and 16 k multi-channel analyzer. The linear attenuation coefficient (LAC) of all the studded samples were calculated theoretically using a Monte Carlo code MCNP-5 code. The gamma radiation shielding properties were analyzed in depth using a Monte Carlo code MCNP-5 simulation model. The theoretical and experimental results for LAC were found to be in complete agreement. Phy-X/PSD software was applied to estimate the mass attenuation coefficient (MAC) for gamma radiation at various energies, as well as the effective atomic number (Zeff), mean free path (MFP), half-value layer (HVL), and tenth-value layer (TVL). The findings demonstrated that the addition of 0.5% MnFe2O4 nanoparticles (MF-NPs) to blended cement pastes exhibited the best physical and mechanical characteristics, as well as the most effective gamma radiation shielding.