Magnetic Data Research Articles

Range and sensitivity of 17O nuclear spin-lattice relaxation as a probe of aqueous electrolyte dynamics.

The study of electrolytic solutions is of relevance in many research fields, ranging from biophysics, materials, and colloid science to catalysis and electrochemistry. The dependence of solution dynamics on the nature of electrolytes and their concentrations has been the subject of many experimental and computational studies, yet it remains challenging to obtain a full understanding of the factors that govern solution behavior. Here, we provide additional insights into the behavior of aqueous solutions of alkali chlorides by combining 17O relaxation data with diffusion and viscosity data and contrast their behavior with 1H nuclear magnetic resonance relaxation data. The main findings are that 17O relaxation correlates well with viscosity data but not with diffusion data, while 1H relaxation correlates with neither. Certain ionic trends match known ion-specific series behavior, especially at high concentrations. Notably, we also examine the ranges of the interactions and conclude that the majority of the effects are tied to local water reorientation dynamics.

Computer Аssessment of the Risk of Нerniated Protrusions of the lntervertebral Discs of the Neck Based on MRl Data

The purpose of the research is assessment of the risk of herniated protrusions of intervertebral discs C4-C5, C5-C6 and C6-C7 of the cervical spine according to MR/ examination.Methods. Тhe biomechanics of the physiological processes of this department has been studied on the basis of MR/ data. A computer program «A method for assessing the risk of herniated protrusions of intervertebral discs of the cervical spine based on the results of an MRI examination» has been developed and tested. The measurements required for the above assessment were obtained during the evaluation of the MR/ examination of a particular patient, after which the data was entered into the program. Тhe calculation results were compared with the database previously obtained by the authors in the course of experimental and clinical studies.Results. Тhe model we use correctly describes the mechanical features of the vertebral junction, since it takes into account the most significant features of their structure, which affect the change in the length of the arms of the levers and the force of pressure on the center of the intervertebral disc. Based on magnetic resonance imaging data, the height of the intervertebral disc at the level of the anterior edges of the vertebral bodies and the АV value were determined, and tg was calculated. For a particular patient, the risk of intervertebral disc protrusion was obtained at the C4-C5, C5-C6 and C6-C7 levels.Conclusion. Тhe test results of the program for assessing the risk of developing an intervertebral disc protrusion in the cervical spine make it possible to describe dynamic phenomena in the cervical spine and predict an unfavorable outcome of pathology at the preclinical stage, even in the absence of clinical manifestations.

Tidal Effects on the Schumann Resonance Amplitudes Recorded by the Global Coherence Monitoring System

The main scientific result of this paper is the demonstration of the fact that tidal effects induced by the Moon affect the Schumann resonance amplitudes measured at magnetometers located at different geographical locations of the Global Coherence Monitoring System. Each magnetometer is paired with the closest monitoring station of the global tidal wave measurement network. This paper introduces the Schumann Resonance Complexity Index (SRCI), computed by using the calibrated H-rank algorithm on the local magnetic field data recorded by each magnetometer of the Global Coherence Monitoring System. Tidal wave data recorded at each monitoring station are also used to compute the Tidal Wave Complexity Index (TWCI). Eliminating diel cycles from the SRCI data yields significant statistical correlations between the SRCI and TWCI data, proving the hypothesis of tidal effects on the global network of magnetometers.

Magnetic and GPR Data Modelling via Multiscale Methods in San Pietro in Crapolla Abbey, Massa Lubrense (Naples)

ABSTRACTWe performed magnetic and GPR measurements to image the buried ruins of the Middle Age abbey San Pietro in Crapolla, on the Sorrento‐Amalfi Coast (Massa Lubrense, Southern Italy). The site represents an important religious location, which is nowadays partially buried along the cliff. An integrated study was necessary to map the buried structures and address the archaeological excavation. For this reason, we carried out the surveys on two main grids in order to reconstruct the structures of the abbey and of its related church. The magnetic data were filtered through the discrete wavelet transform (DWT) and then transformed to total gradient maps. The obtained maps were interpreted with depth from extreme points (DEXP) imaging method to assess the horizontal and depth positions of the top. The GPR data were processed and time‐depth converted. Results from the integrated interpretation of these data suggest the possible presence of different vaulted rooms and an elongated structure at 0.3‐m depth from ground surface. This latter is interpretable in terms of perimetral and internal walls of the abbey and its church. These outcomes were crucial to successfully address archaeological excavations, which targeted one of the modelled areas and unearthed a wall at the predicted depths.

Bayesian Inference of Recurrent Switching Linear Dynamical Systems with Higher-Order Dependence

Many complicated dynamical events may be broken down into simpler pieces and efficiently described by a system that shifts among a variety of conditionally dynamical modes. Building on switching linear dynamical systems, we develop a new model that extends the switching linear dynamical systems for better discovering these dynamical modes. In the proposed model, the linear dynamics of latent variables can be described by a higher-order vector autoregressive process, which makes it feasible to evaluate the higher-order dependency relationships in the dynamics. In addition, the transition of switching states is determined by a stick-breaking logistic regression, overcoming the limitation of a restricted geometric state duration and recovering the symmetric dependency between the switching states and the latent variables from asymmetric relationships. Furthermore, logistic regression evidence potentials can appear as conditionally Gaussian potentials by utilizing the Po´lya-gamma augmentation strategy. Filtering and smoothing algorithms and Bayesian inference for parameter learning in the proposed model are presented. The utility and versatility of the proposed model are demonstrated on synthetic data and public functional magnetic resonance imaging data. Our model improves the current methods for learning the switching linear dynamical modes, which will facilitate the identification and assessment of the dynamics of complex systems.

Submarine cable detection using an end-to-end neural network-based magnetic data inversion

Abstract To process magnetic anomaly data, appropriate parameters for field separation, denoising, and Euler deconvolution have to be manually selected. The traditional workflow is inefficient and cannot fulfill the rapid detection of submarine cables due to the complex processing and manual parameter tuning. This study presents an end-to-end deep learning approach for the identification and positioning of submarine cables based on magnetic anomalies. The proposed approach effectively establishes a direct mapping correlation between the magnetic field data and the position of the submarine cable. Synthetic tests suggest that our method has a better performance in terms of positioning accuracy than the conventional Euler method. Our results for the field data are comparable to those obtained using conventional techniques. Furthermore, the proposed method achieves an optimal solution by employing clustering technique and selecting the solution with the maximum confidence, which avoids spurious solutions associated with traditional methods. The proposed method can directly determine the position of the submarine cables using the raw magnetic field data. Contrary to the traditional processing workflow, field separation and denoising are not necessary in this novel approach, resulting in higher processing efficiency and a simpler processing process.

Application of Airborne Magnetic Data to Assess the Structures that Favour Gold Mineralization within Southern Parts of Katsina State, Nigeria

The Nigerian schist belts are endowed with gold mineralisation and to delineate the geological structures that favour gold mineralisation, the airborne magnetic data that cover the study area was employed. Also, the residual magnetic anomaly data of the research area was reduced to the Equator (RTE) followed by the application of the centre for exploration targeting (CET) plug-in and three source edge mapping techniques; analytic signal (AS), first vertical derivative (FVD) and the horizontal gradient magnitude (HGM), for structural delineation and subsequently the structural density map of the area was produced. Structural density varies from 0.186 km/km2 low to 0.93 km/km2 high. Portions within the study area with high structural densities are Bakori in the southwest, Shanono in the northeast, Gwarzo situated directly south of Shanono, north and south of Karaye, the border between Kafur and Rogo in the south, all within the schist. Since structures are conduits for the migration of mineralisation fluids, areas with high structural densities will be viable for gold mineralisation. Also, comparing the structural density map of the area to the analytic signal map of the area has revealed the high structural density portions to coincide with the high analytic signal zones. This implies that structures within these portions are responsible for the migration of mineralization fluid into these environments.

Merging total synthesis and NMR technology for deciphering the realistic structure of natural 2,6-dideoxyglycosides.

The structural identification and efficient synthesis of bioactive 2,6-dideoxyglycosides are daunting challenges. Here, we report the total synthesis and structural revision of a series of 2,6-dideoxyglycosides from folk medicinal plants Ecdysanthera rosea and Chonemorpha megacalyx, which feature pregnane steroidal aglycones bearing an 18,20-lactone and glycans consisting of 2,6-dideoxy-3-O-methyl-β-pyranose residues, including ecdysosides A, B, and F and ecdysantheroside A. All the eight possible 2,6-dideoxy-3-O-methyl-β-pyranoside stereoisomers (of the proposed ecdysantheroside A) have been synthesized that testify the effective gold(I)-catalyzed glycosylation methods for the synthesis of various 2-deoxy-β-pyranosidic linkages and lays a foundation via nuclear magnetic resonance data mapping to identify these sugar units which occur promiscuously in the present and other natural glycosides. Moreover, some synthetic natural compounds and their isomers have shown promising anticancer, immunosuppressive, anti-inflammatory, and anti-Zika virus activities.

Music and the aging brain – Exploring the role of long-term Carnatic music training on cognition and gray matter volumes

Objectives: Aging is a natural process and is often associated with an increased incidence of cognitive impairment. Physical exercise, diet, and leisure activities (music, dance, and art) are some of the lifestyle factors that contribute to healthy aging. The present study aims to explore the differences in cognitive functioning between aging individuals involved in musical activity throughout their lifetime and the ones who were not. Materials and Methods: Fifty-one healthy elderly individuals (50–80 years of age) residing in an urban locality were selected for the study from the Tata Longitudinal Study of Aging cohort. Participants were divided into two groups: Active musicians trained in Carnatic music for more than five years (n = 18) and age-matched non-musicians (n = 33). Addenbrooke cognitive examination-III, Hindi mental status examination, and trail-making test-B (TMT-B) were used to assess cognitive functioning. A Generalized Linear Regression Model was performed including covariates such as gender, age, and years of education. We also looked at the available brain magnetic resonance imaging data of a subset of our study population to inspect the volumetric differences between musicians and non-musicians. Results: Our results showed that musicians had significantly better visuospatial abilities as compared to non-musicians (P = 0.043). Musicians (130.89 ± 45.16 s) also took less time to complete the TMT-B task than non-musicians (148.73 ± 39.65 s), although it was not a statistically significant difference (P =0.150). In addition, brain imaging data suggested that musicians had increased gray matter volumes in the right precuneus, right post-central gyrus, right medial and superior frontal gyrus, right orbital gyrus, left middle temporal gyrus, left cuneus, left fusiform gyrus, and bilateral cingulate gyrus. Conclusion: Our findings are indicative of music being an important attribute in improving cognitive reserve and predicting cognitive resilience. These findings pave the way to explore the utility of non-pharmacological interventions, such as Music Therapy (especially Carnatic music in the Indian context), as a potential factor for improving cognitive reserve in elderly individuals.

Side Collision Detection Model for Visually Impaired Using Monocular Object-specific Distance Estimation and Multimodal Real-World Location Calculation

Targeting the potential risk of side-vehicle collisions when the visually impaired crosses roads, this study proposed a side collision detection model, including monocular distance estimation, multimodal real-world location estimation, future location prediction and collision warning strategies tailored for visually impaired pedestrians. The proposed model employs YOLOv8 and DeepSort for vehicle detection and tracking, utilizing shallow neural networks for distance estimation based on image information and vehicle position data. Predicted vehicle distances are combined with magnetic field sensor and GPS data to compute and store real-world vehicle locations, and these location data will be used for linear regression to forecast future locations. A warning strategy is then implemented to alert users. Experimental validation shows that the monocular distance estimation network has an Absolute Relative Error of 0.043 and an ALE (Average Localization Error) of 1.249m. In real-world location estimation, the view angle ALE is 0.019, and the location ALE is 1.778m. Regarding location prediction, the accuracy in distinguishing stationary and moving vehicles reaches 0.962, and the predicted curve, based on ground truth and predicted locations, exhibits good alignment. The proposed warning strategy, evaluated on Kitti Tracking Dataset and a self-created dataset, accurately detects the majority of potential collision risks.

Fabrication, structure, characterization and emulsion application of citrate agar

Citric acid esterified agar (CA) with different degrees of substitution (DS) was prepared, and CA gel was used to stabilize O/W emulsions. Compared with native agar (NA), CA had lower gel strength, higher transparency, and higher water contact angle. Further analysis of DS, group content ratio, Fourier transform infrared, and nuclear magnetic resonance data showed that the CA underwent cross-linking reaction. Emulsion properties revealed that CA gel emulsion (CAGE) had smaller particle size and lower ζ-potential than the NA gel emulsion (NAGE). Meanwhile, confocal laser scanning microscopy confirmed that CA gel stabilized emulsions by forming a protective film around the oil droplets. Stability tests showed that CAGE (prepared with CA gel [DS = 0.145]) was more stable than NAGE at pH 3–11. Rheological results further confirmed that emulsion stability was influenced by electrostatic repulsion and gel adsorption. The application prospect of CAGE was evaluated by encapsulating vitamin D3 and curcumin.

Improved ellipsoid fitting aided geomagnetic sensor calibration algorithm

Aiming at the problems that the traditional single ellipsoid fitting fails to eliminate the errors of the geomagnetic sensor and does not consider the geomagnetic anomaly information, etc., this paper proposes a robust least squares combined with the Levenberg–Marquardt (LM-RLS) algorithm to fit an accurate ellipsoid to achieve accurate data calibration. According to the geomagnetic sensor error model, the total amount of geomagnetism is used as the constraint, the fitted ellipsoid coefficients of RLS are used as the initial values, and the LM algorithm is used to calculate the magnetic field dispersion points to the nearest point of the fitted ellipsoid surface. Then, the initial calibration value is solved by the criterion of the minimum weighted sum of squares of the closest point distance. Finally, the accurate ellipsoid is obtained to realize data calibration. The results of the dynamic experiment show that after the ellipsoid is precisely fitted by the LM-RLS algorithm, the sum of the absolute values of the distance from the magnetic field discrete data to the ellipsoid surface is reduced by 48.33% (RLS) and 43.10% (RWTLS). The relative errors of the magnetic field in the X, Y, and Z axes are reduced from 0.48%, 0.78%, 1.48% (RLS) and 0.30%, 0.58%, 1.14% (RWTLS) to 0.10%, 0.04% 0.16 %, respectively. The accuracy of geomagnetic calibration is improved by 68.06% (RLS) and 61.02% (RWTLS) in the dynamic experiment. The algorithm improves the accuracy of geomagnetic measurement, which provides a new idea for the calibration of three-axis geomagnetic sensors.

Using Euler Deconvolution as Part of a Mineral Exploration Project

Mineral exploration projects can make considerable use of a variety of geophysical techniques and datasets, including magnetic and gravity data. The interpretation of large quantities of data can be very time consuming, so semi-automatic interpretation techniques are often used to provide initial estimates of the parameters (primarily the location and depth) of the sources of anomalies. Euler deconvolution is a commonly used interpretation method for potential fields which has a number of advantages over many other techniques, such as working in the presence of remanent magnetisation, and not being restricted to a particular model such as a contact. A second-order version of Euler’s equation is introduced here, which is much less affected by trends in the data than the standard method and additionally produces depth parabolas, which simplify the interpretation of results. The method was applied to aeromagnetic data from a mineral exploration project in Southern Africa and provided plausible results.

Effects of bilateral tDCS over DLPFC on response inhibition, craving, and brain functional connectivity in Internet gaming disorder: Arandomized, double-blind, sham-controlled trial with fMRI.

Impaired inhibitory control accompanied by enhanced craving is hallmark of addiction. This study investigated the effects of transcranial direct current stimulation (tDCS) on response inhibition and craving in Internet gaming disorder (IGD). We examined the brain changes after tDCS and their correlation with clinical variables. Twenty-four males with IGD were allocated randomly to an active or sham tDCS group, and data from 22 participants were included for analysis. Participants self-administered bilateral tDCS over the dorsolateral prefrontal cortex (DLPFC) for 10 sessions. Stop-signal tasks were conducted to measure response inhibition and participants were asked about their cravings for Internet gaming at baseline and post-tDCS. Functional magnetic resonance imaging data were collected at pre- and post-tDCS, and group differences in resting-state functional connectivity (rsFC) changes from the bilateral DLPFC and nucleus accumbens were examined. We explored the relationship between changes in the rsFC and behavioral variables in the active tDCS group. A significant group-by-time interaction was observed in response inhibition. After tDCS, only the active group showed a decrease in the stop-signal reaction time (SSRT). Although craving decreased, there were no significant group-by-time interactions or group main effects. The anterior cingulate cortex (ACC) showed group differences in post- versus pre-tDCS rsFC from the right DLPFC. The rsFC between the ACC and left middle frontal gyrus was negatively correlated with the SSRT. Our study provides preliminary evidence that bilateral tDCS over the DLPFC improves inhibitory control and could serve as a therapeutic approach for IGD.

Revelations of vortex phases and pinning mechanism in GdBa2Cu3O7-δ superconductors: a magneto-electric and magnetization study

Abstract Rare earth (RE) and barium (Ba) based cuprate superconductors have garnered considerable attention in both fundamental research and a wide array of engineering and technological applications. Examining the impact of magnetic Gd3+ ions on the GdBa2Cu3O7-δ (GdBCO) system, this study reveals that the presence of Gd3+ ion has tilted the magnetic hysteresis loop, thereby affecting the critical current density (Jc) at low temperatures. Through comprehensive magnetic and magnetotransport data analyses of the GdBCO sample, we have thoroughly explored the intricate behavior of vortices in response to magnetic fields and temperature variations, providing insight into the governing mechanism of vortex pinning. Remarkably, the absolute zero temperature pinning potential (U0) experiences a significant reduction from a very high value of 3.18 eV to 0.45 eV with a magnetic field increase to 40 KOe, following a H^-0:53 law, indicating 3D plastically crippled vortices in weak pinning sites due to point defects. In various technological domains, particularly those involving high temperatures and strong magnetic fields, understanding and optimizing the pinning force (Fp) and the pinning potential (U) of the vortices are pivotal for enhancing performance and efficiency. Consequently, we have meticulously analyzed the nature of Fp and U with the aid of the thermally activated flux flow (TAFF) model. Ultimately, we compiled a comprehensive phase diagram delineating the evolution of various vortex phases.

Commonality and variance of resting-state networks in common marmoset brains

Animal models of brain function are critical for the study of human diseases and development of effective interventions. Resting-state network (RSN) analysis is a powerful tool for evaluating brain function and performing comparisons across animal species. Several studies have reported RSNs in the common marmoset (Callithrixjacchus; marmoset), a non-human primate. However, it is necessary to identify RSNs and evaluate commonality and inter-individual variance through analyses using a larger amount of data. In this study, we present marmoset RSNs detected using > 100,000 time-course image volumes of resting-state functional magnetic resonance imaging data with careful preprocessing. In addition, we extracted brain regions involved in the composition of these RSNs to understand the differences between humans and marmosets. We detected 16 RSNs in major marmosets, three of which were novel networks that have not been previously reported in marmosets. Since these RSNs possess the potential for use in the functional evaluation of neurodegenerative diseases, the data in this study will significantly contribute to the understanding of the functional effects of neurodegenerative diseases.

Progressive thalamic nuclear atrophy in blepharospasm and blepharospasm-oromandibular dystonia

Abstract The thalamus is considered a key region in the neuro-mechanisms of blepharospasm. However, previous studies considered it as a single, homogeneous structure, disregarding potentially useful information about distinct thalamic nuclei. Herein, we aimed to examine: (1) whether gray matter volume differs across thalamic subregions/nuclei in patients with blepharospasm and blepharospasm-oromandibular dystonia; (2) causal relationships among abnormal thalamic nuclei; and (3) whether these abnormal features can be used as neuroimaging biomarkers to distinguish patients with blepharospasm from blepharospasm-oromandibular dystonia and those with dystonia from healthy controls. Structural magnetic resonance imaging data were collected from 56 patients with blepharospasm, 20 with blepharospasm-oromandibular dystonia, and 58 healthy controls. Differences in thalamic nuclei volumes between groups and their relationships to clinical information were analyzed in patients with dystonia. Granger causality analysis was employed to explore the causal effects among abnormal thalamic nuclei. Support vector machines were used to test whether these abnormal features could distinguish patients with different forms of dystonia and those with dystonia from healthy controls. Compared with healthy controls, patients with blepharospasm exhibited reduced gray matter volume in the lateral geniculate and pulvinar inferior nuclei, whereas those with blepharospasm-oromandibular dystonia showed decreased gray matter volume in the ventral anterior and ventral lateral anterior nuclei. Atrophy in the pulvinar inferior nucleus in blepharospasm patients and in the ventral lateral anterior nucleus in blepharospasm-oromandibular dystonia patients were negatively correlated with clinical severity and disease duration, respectively. The proposed machine learning scheme yielded a high accuracy in distinguishing blepharospasm patients from healthy controls (accuracy: 0.89), blepharospasm-oromandibular dystonia patients from healthy controls (accuracy: 0.82), and blepharospasm from blepharospasm-oromandibular dystonia patients (accuracy: 0.94). Most importantly, granger causality analysis revealed that a progressive driving-pathway from pulvinar inferior nuclear atrophy extends to lateral geniculate nuclear atrophy, and then to ventral lateral anterior nuclear atrophy with increasing clinical severity in patients with blepharospasm. These findings suggest that the pulvinar inferior nucleus in the thalamus is the focal origin of blepharospasm, extending to pulvinar inferior nuclear atrophy, and subsequently extending to the ventral lateral anterior nucleus causing involuntary lower facial and masticatory movements known as blepharospasm-oromandibular dystonia. Moreover, our results also provide potential targets for neuro-modulation especially deep brain stimulation in patients with blepharospasm and blepharospasm-oromandibular dystonia.

Changes in Clinical and Network Functional Connectivity Parameters in Motor Networks and Cerebellum Based on Resting-State Functional Magnetic Resonance Imaging Data in Patients with Post-Stroke Hemiparesis Receiving Interactive Brain Stimulation Neurotherapy

Introduction. Interactive brain stimulation (IBS) neurotherapy is an advanced neurofeedback technology (NFB) that involves the organization of a feedback “target” based on signals recorded by functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). The NFB allows patients to volitionally self-regulate their current brain activity and may therefore be a useful treatment option for diseases with altered activation and functional connectivity (FC) patterns.
 Our objective was to assess the effects of IBS on the FC changes in motor networks and correlations between clinical and network parameters in patients with post-stroke hand paresis.
 Materials and methods. Patients with a history of stroke 2 months were randomized into a main group (n = 7) and a control group (n = 7). All the patients followed the stroke physical rehabilitation for 3 weeks. The main group received IBS training, where the patients learned to imagine movements of the paretic hand trying to amplify the fMRI signal from the primary motor cortex (M1) and the supplementary motor area (SMA) on the lesion side with simultaneous desynchronizing the μ- and β-2 EEG rhythms in the central leads. Clinical tests and MRI were performed prior to and immediately after the treatment. FC matrices were constructed using CONN software based on resting-state fMRI data.
 Results. By the end of the training, M1–M1 functional connectivity in the control group weakened, while no changes were observed in the main group. The FC strength was positively correlated with the grip strength (ρ = 0.69; p 0.01) and with the results of the Box and Blocks test (BBT score, ρ = 0.72; p 0.01) and the Fugl-Meyer assessment for upper extremity (FM-UE score, ρ = 0.87; p 0.005). Ipsilesional SMA connectivity with contralesional cerebellum weakened (p 0.05 in the main group). Its strength was negatively correlated with the BBT and FM-UE scores (both tests ρ = –0.44; p 0.05).
 Conclusions. Volitional control of M1 and SMA activity in the lesion hemisphere during the post-stroke IBS training alters the architecture of the entire motor network affecting clinically significant FC types. We studied a possible mechanism of this technology and its potential use in treatment programs.

Crystal structures and crystallographic classification of titanium silicophosphates – with a note on structure and composition of silicophosphates “M 3P5SiO19”

Abstract The crystal structures of TiIII 4[Si2O(PO4)6] ( P 3 ‾ $P\overline{3}$ , Z = 3, a = 14.733(1), c = 7.363(1) Å, R1 = 0.040, wR2 = 0.098, 7649 ind. refl., 170 variables), FeII 0.79TiIII 2.42TiIV 0.79[Si2O(PO4)6] ( P 3 ‾ $P\overline{3}$ , Z = 3, a = 14.6534(2), c = 7.3829(1) Å, R1 = 0.036, wR2 = 0.088, 4026 ind. refl., 171 variables), and TiIII 2TiIV 6(PO4)6[Si2O(PO4)6] ( R 3 ‾ $R\overline{3}$ , Z = 1, a = 8.446(2), c = 44.21(2) Å, R1 = 0.047, wR2 = 0.120, 1373 ind. refl., 109 variables) have been refined from single-crystal data. The structures show hexagonal closest packing of phosphate groups with metal cations and [Si2O] groups occupying octahedral voids [□(PO4)6]. The close relationship of these and other silicophosphate structures to the NiAs and β-Fe2(SO4)3 (see also NaZr2(PO4)3 “NASICON”) structure types is rationalized by group/subgroup considerations. This symmetry approach shows that systematic twinning is highly likely in silicophosphates, thus possibly leading to faulty crystal structure refinements. Our investigation strongly suggests that the proper composition of silicophosphates “M III 3P5SiO19” (M = Cr, V, Fe, Mo) reported in literature is actually M III 4-[Si2O(PO4)6]. In the mixed-valent compounds oxidation states were assigned to the cation sites by comparison to Ti2O3, TiP2O7 and FeTiO3. The powder reflectance spectrum of dark-blue FeII 0.79TiIII 2.42TiIV 0.79[Si2O(PO4)6] shows a strong IVCT transition at ν ˜ $\widetilde{\nu }$  = 17,500 cm−1, and magnetic susceptibility data agree very well with the proposed oxidation states.

Exploring ophiolitic deposits offshore Scoglio d’Affrica islet (northern Tyrrhenian Sea): A comprehensive geophysical model of the shallow crustal dynamics

The islet of Scoglio d’Affrica (Tuscany Archipelago, northern Tyrrhenian Sea) is an emerging segment of the Elba-Pianosa Ridge. This ridge is a major tectonic-structural high formed by Eocene-Early Miocene clastic succession which separates the Tuscany shelf from the Corsica basin. The distinctive structural setting of the Scoglio d’Affrica region is a result of crustal fragmentation during the extensional tectonic regime of the northern Tyrrhenian Sea. Along the Elba Pianosa Ridge, a complex interplay between Miocene magmatism, active submarine gas emissions and mud volcanism has been observed. Currently, the Scoglio d’Affrica region experiences active mud volcanism, accompanied by diffuse seafloor gas leakages and sporadic violent mud-water mixed eruptions, as exemplified by the most recent event in 2017.In this study, we present a comprehensive analysis of shipborne magnetic data, swath bathymetry, single and multichannel seismic profiles of Scoglio d’Affrica region focalized to provide a comprehensive geophysical model of shallow crustal dynamics.Forward and inverse magnetic models reveal the presence of a continuous high magnetic susceptibility body running along a NNW-SSE direction, parallel to the main tectonic lineaments. This high magnetic source is interpreted as an ophiolite/high grade serpentinite deposit embedded in Eocene siliciclastic layers resulting from the disrupting of the Corsica Alpine basement. This deposits are related to sedimentary gravity processes originated from peripheral highs and accumulated in intra-wedge basins subsequently deformed during the Oligocene. Our reconstruction provides previously unknown details about geometry and distribution of shallow ophiolite-like deposits thereby improving the comprehension the intricate structural evolution of Elba-Pianosa Ridge featured by a multiphase tectonic deformation and shallow manifestations of fluid/gas circulation.