Search Results (121)

Background/Objectives: T1-weighted magnetic resonance imaging (MRI) and the Montreal Cognitive Assessment are standard, efficient, and swift clinical and research tools used when interrogating cognitively impairing (CI) conditions, such as Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD). However, the associations between gross cognitive impairment (CI) as compared to domain-specific functioning and underlying neuroanatomical correlates have not been investigated among individuals with early-onset Mild Cognitive Impairment (MCI) or Alzheimer’s disease (EOAD), who can benefit greatly from early diagnosis and intervention strategies. Methods: We analyzed T1-weighted MRIs and Montreal Cognitive Assessment (MoCA) scores from the ADNI database in individuals < 65 years old who were either cognitively normal (CN) or had MCI or EOAD. Gray matter volume (GMV) was estimated in voxel-based morphometry (VBM) and ROI-parcellation general linear models examining associations with individual MoCA scores after adjusting for demographic covariates. Results: Results from 120 subjects (44 CN, 62 MCI, and 14 EOAD), identified significant global but also individually distinct domain-specific topographical signatures spanning the temporal, parietal, limbic, occipital, frontal lobes, and cingulate gyri. Conclusions: The results highlight neural correlates of cognitive functioning in a sample of young patients representative of the AD continuum, in addition to studying the structural MRI and functional cognitive difference. Full article

Electrically charged particles present in this layer of the Earth’s atmosphere can alter radio waves, such as those from GPS, Galileo, or BeiDou, resulting in non-estimated errors with respect to the available navigation models for the end user. For most positioning algorithms based in sequential filters, this effect is translated into a slow convergence towards a solution around the decimeter error level. If we consider that the ionosphere’s effect varies based on the user’s location and solar activity due to the atmosphere particle composition, it becomes clear that a global accurate model, valid across wide areas accounting for different seasons and timespans, is, at the very least, quite challenging. The focus of this paper is the demonstration of a global ionosphere model designed to improve the positioning accuracy of the end user through the estimation of ionospheric corrections to the broadcasted navigation message. Mathematically, this method is based on a spherical harmonic expansion model. This approach has the advantage of reducing the dependency from a highly densified station network where the ionosphere delay must be constantly estimated in dozens of locations, in favor of a simplified model that barely needs to be adjusted with a limited set of real-time data (around 40 stations). In this case, GMV’s global station network was used, which comprises geodetic-grade receivers tracking the signal in open-sky locations around the globe. The global ionospheric model is configured to process signals from GPS and Galileo constellations. To evaluate the performances of this model on the final user position estimation, several precise point positioning (PPP) solutions were computed at different locations. The results were compared with PPP solutions calculated without ionospheric corrections at the same stations. The goal of this paper is to show the significant performance improvement observed with the implementation of the global model. Full article

This paper addresses the selection and justification of ephemeris parameters to be broadcast in a LEO-PNT navigation message. The temporal evolution of LEO orbital elements is analyzed, proving that the GPS/GAL model needs to evolve to cope with LEO orbit dynamics and to ensure high-accuracy ephemeris. In addition, the ephemeris fitting process is performed systematically for different sets of parameters allowing the most convenient parameter combinations to be determined. If adequate parameters are included in an ephemeris model, the fitting error tends to reduce. Beyond ephemeris parametrization, the length of the fitting interval significantly influences the achievable accuracy—for short fitting intervals of 5–10 min with an optimal set of ephemeris parameters, a SISRE at WUL in the order of 1 to 7 mm is obtained. Full article

Background/Objectives: With the globalization of companies, the cross-cultural adjustment of expatriates working overseas is becoming an increasingly important topic. However, little research has been carried out on the brain, which is the source of the ability to adapt. Methods: Therefore, we conducted a pilot study on 10 expatriates working for Japanese local subsidiaries in the United States to analyze the relationship between their gray matter volume (GMV) measured by the Gray Matter Brain Healthcare Quotient and their cross-cultural adjustment and lifestyle. Results: As a result, in a partial correlation analysis controlled for demographic variables, there was a significant correlation between whole-brain GMV and general adjustment. A relationship was also shown between the local GMV of the default mode network and central executive network and interaction adjustment. Conclusions: This is the first pilot study to clarify the relationship between expatriates’ brain structure and cross-cultural adjustment, suggesting the effectiveness of a biological approach in cross-cultural adjustment research. Full article

This paper explores the usage of LEO-PNT (Positioning, Navigation, and Timing) for providing navigation integrity to GNSS (Global Navigation Satellite System) constellations. LEO mega-constellations, which are positioned between GNSSs and users, offer closer-to-the user geometry, improving performance, reducing the time to alarm (TTA) and enabling integrity monitoring without complex ground segments of any sort. The aim is to use future LEO mega-constellations as integrity monitors for a forthcoming European Global Navigation Satellite System (EGNSS) specifically focused on automotive users, which has minimal onboard satellite capabilities and no ground involvement. This plan builds on earlier studies, anticipating the performance of the upcoming LEO-PNT In-Orbit Demonstration. Full article

Nowadays, high precision and reliability of Global Navigation Satellite Systems are increasingly important in positioning applications. Machine learning is used to improve the performance of the GSHARP PPP algorithm by reducing the effect of multipath on GNSS measurements. The clustering analysis is conducted on the primary GNSS data points with the goal of discovering and analyzing patterns in the multipath interference. This study represents an early attempt to apply AI to the GSHARP PPP algorithm. Since Lightweight Machine Learning is used in this research, it is easier to integrate and might lay the groundwork for future integration of advanced deep learning methods. About 50 h of data collected from different environments (e.g., highways and urban areas) serves as the training data for these algorithms, which ensures their robustness and real-world applicability. The use of machine learning clustering inside the PPP algorithm serves as a way to improve its performance against multipath effects, as well as provide a platform for subsequent development of precision GNSS systems through AI technologies. Full article

Current Satellite-Based Augmentation Systems (SBASs) improve the positioning accuracy and integrity of GPS satellites and provide safe civil aviation navigation services for procedures from en-route to LPV-200 precision approach over specific regions. SBAS systems, such as WAAS, EGNOS, GAGAN, and MSAS, already operate. The development of operational SBAS systems is in transition due to the extension of L1 SBAS services to new regions and the improvements expected by the introduction of dual frequency multi-constellation (DFMC) services, which allow the use of more core constellations such as Galileo and the use of ionosphere-free L1/L5 signal combination. The UKSBAS Testbed is a demonstration and feasibility project in the framework of ESA’s Navigation Innovation Support Programme (NAVISP), which is sponsored by the UK’s HMG with the participation of the Department for Transport and the UK Space Agency. UKSBAS Testbed’s main objective is to deliver a new L1 SBAS signal in space (SIS) from May 2022 in the UK region using Viasat’s Inmarsat-3F5 geostationary (GEO) satellite and Goonhilly Earth Station as signal uplink over PRN 158, as well as L1 SBAS and DFMC SBAS services through the Internet. SBAS messages are generated by GMV’s magicSBAS software and fed with data from the Ordnance Survey’s station network. This paper provides an assessment of the performance achieved by the UKSBAS Testbed during the last two years of operations at the SIS and user level, including a number of experimentation campaigns performed in the aviation and maritime domains, comprising ground tests at airports, flight tests on aircraft and sea trials on a vessel. This assessment includes, among others, service availability (e.g., APV-I, LPV-200), protection levels (PL), and position errors (PE) statistics over the service area and in a network of receivers. Full article

The European Commission (EC) is taking steps towards the implementation of a Galileo Timing Service. This service is now formally part of the mission of the Galileo Second Generation, and it puts emphasis on serving critical infrastructure. Implementing a proper service implies putting all the necessary elements in place to be able to meet the defined level of performance. In order to ensure the correct processing of the service’s signals and a minimum level of performance of the user receiver, corresponding standards are needed. Therefore, a fundamental element in the Galileo Timing Service concept is the standardization of Galileo Timing Receivers. The STARLITE project (Preparation of Standards for Galileo Timing Receivers) funded by the EC is the first international initiative to develop standards for GNSS Timing Receivers. The target users for the standard are all Galileo Timing users, with a special focus on critical infrastructure within the telecommunications, finance and energy sectors. The standard leverages the specificities of the Galileo Timing Service. This will become fundamental in order to ensure the end-to-end performance for those users operating a receiver compliant with the standard. At the same time, the standard allows the use of other systems to further enhance the performance. The project helped to establish a formal Working Group (WG9) for the development of the standard under CEN/CENELEC JTC5. Full article

Advanced Receiver Autonomous Integrity Monitoring (ARAIM) represents an advancement over RAIM, designed to utilize dual-frequency and multi-constellation technologies. Originally developed for aviation, the European Commission (EC) is now exploring its broader application. This paper examines the adaptation of ARAIM for rail, maritime, and Unmanned Aerial Vehicles (UAVs) sectors. It briefly discusses aspects of the integrity concept, including architecture and user algorithms while the main focus is on characterizing local error models for local effects using real data campaigns. Full article

Objective: This study compares machine learning (ML) and logistic regression (LR) algorithms in developing a predictive model for sPCa using the seven predictive variables from the Barcelona (BCN-MRI) predictive model. Method: A cohort of 5005 men suspected of having PCa who underwent MRI and targeted and/or systematic biopsies was used for training, testing, and validation. A feedforward neural network (FNN)-based SimpleNet model (GMV) and a logistic regression-based model (BCN) were developed. The models were evaluated for discrimination ability, precision–recall, net benefit, and clinical utility. Both models demonstrated strong predictive performance. Results: The GMV model achieved an area under the curve of 0.88 in training and 0.85 in test cohorts (95% CI: 0.83–0.90), while the BCN model reached 0.85 and 0.84 (95% CI: 0.82–0.87), respectively (p > 0.05). The GMV model exhibited higher recall, making it more suitable for clinical scenarios prioritizing sensitivity, whereas the BCN model demonstrated higher precision and specificity, optimizing the reduction of unnecessary biopsies. Both models provided similar clinical benefit over biopsying all men, reducing unnecessary procedures by 27.5–29% and 27–27.5% of prostate biopsies at 95% sensitivity, respectively (p > 0.05). Conclusions: Our findings suggest that both ML and LR models offer high accuracy in sPCa detection, with ML exhibiting superior recall and LR optimizing specificity. These results highlight the need for model selection based on clinical priorities. Full article

Background/Objectives: Schizophrenia (SZ) is a complex psychiatric disorder characterized by neurodegenerative processes, but the structural brain alterations associated with its progression remain poorly understood. This study investigated structural brain changes in SZ, particularly in the fronto-temporal and limbic regions, and explored their relationship with symptom severity, with a focus on mood- and emotion-related symptoms. Methods: We analyzed structural MRI data from 74 SZ patients and 91 healthy controls (HCs) using voxel-based morphometry (VBM) to compare whole-brain grey matter volumes (GMVs). The analysis focused on the fronto-temporal and limbic regions, and correlations between GMV and symptom severity were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Generalized Psychopathology (GP) scale. Results: SZ patients exhibited significant reductions in GMV in the fronto-temporal and limbic regions, including the dorsolateral prefrontal cortex (dlPFC) and the temporal pole, compared to HCs. Notably, a significant positive association was found between GMV in the right inferior temporal gyrus (ITG) and the severity of generalized psychopathology, as well as with anxiety, depression, mannerisms, and unusual thought content. Further post hoc analysis identified a specific cluster of mood-related symptoms contributing to the GP scale, which correlated with GMV changes in the right ITG. Conclusions: Our findings provide new evidence of structural brain alterations in SZ, particularly in the fronto-temporal and limbic regions, suggesting a progressive neurodegenerative pattern. The role of the right ITG in mood- and emotion-related symptoms requires further exploration, as it could offer insights into SZ pathophysiology and aid in distinguishing SZ from other mood-related disorders. Full article

Background/Objectives: Advancements in biomedical imaging technologies over the past few decades have made it increasingly possible to measure the long-term effects of exercise on the central nervous system. This study aims to compare the brain morphology and functional connectivity of wrestlers and handball players, exploring sport-specific neural adaptations. Methods: Here, we examined 26 elite male athletes (13 wrestlers and 13 handball players) using anatomical and resting-state functional magnetic resonance imaging (fMRI) measurements. Connectivity maps are derived using the seed-based correlation analysis of resting-state fMRI, while voxel-based morphometry (VBM) is employed to identify anatomical differences. Additionally, the cortical thickness and global volumetric values of the segmented images are examined to determine the distinctions between elite wrestlers and handball players using non-parametric statistical tests. Results: Wrestlers exhibited greater grey matter volume (GMV) in the right middle temporal gyrus, left middle frontal gyrus, and right posterior cingulate gyrus (uncorr., p < 0.001). On the other hand, wrestlers showed increased functional connectivity in the left superior temporal gyrus, left parahippocampal gyrus, the left anterior orbital gyrus, and right superior frontal gyrus–medial frontal region (P(_FWE) < 0.05). In addition, wrestlers showed greater cortical thickness in several brain regions. Conclusions: The increased GMV, cortical thickness, and functional connectivity observed in wrestlers highlight the presence of sport-specific neural adaptations. While this research provides valuable insights into the neuroplastic effects of various athletic disciplines, further studies involving additional sports and control groups are needed for a more comprehensive understanding. Full article

Background/Objectives: Interest in diversity is growing worldwide. Today, an understanding and social acceptance of diverse people is becoming increasingly important. Therefore, in this study, we aimed to clarify the relationship between an individual’s gray matter volume (GMV), which is thought to reflect brain health, and their understanding of diversity (gender, sexuality (LGBTQ), and origin). Methods: GMV was determined as the value of the Gray Matter Brain Healthcare Quotient (GM-BHQ) based on MRI image analysis. Meanwhile, participants’ understanding and acceptance of diversity was calculated based on their answers to the psychological questions included in the World Values Survey Wave 7 (WVS7). Results: Our analysis indicated that, in the group of participants with the highest understanding of diversity (PHUD. n = 11), not only the GMV at the whole brain level (t = 2.587, p = 0.027, Cohen’s d = 0.780) but also the GMV of the central executive network (CEN: t = 2.700, p= 0.022, Cohen’s d = 0.814) and saliency network (SN: t = 3.100, p = 0.011, Cohen’s d = 0.935) were shown to be significantly higher than the theoretical value estimated from sex, age, and BMI at the 5% level. In addition, the GMV of the default mode network (DMN: t = 2.063, p = 0.066, Cohen’s d = 0.622) was also higher than the theoretical value at the 10% level. Meanwhile, in the group of others (n = 10), there was no significant difference from the theoretical value. These differences between PHUD and others were also observed when comparing the two with and without controlling for educational and occupational covariates at the 5% or 10% levels. Conclusions: These results suggest that understanding diversity requires a healthy brain, centered on three networks that govern rational judgment, emotion regulation, other-awareness, self-awareness, and the valuing of actions. This is the first study to show that brain structure is related to an understanding and acceptance of the diversity of people. Full article

Background/Objectives: Violent behaviors are uncommon in patients with schizophrenia (Sch), but when present, exacerbate stigma and challenge treatment. The following study aimed to identify the structural abnormalities associated with violent behaviors in Sch by implementing a validated tool specifically designed to evaluate violent behaviors in psychiatric populations, as well as by performing region-of-interest neuroimaging analyses, focused on areas commonly associated with the neurobiology of violence and aggression. Methods: Eighty-three participants were divided into three groups: Sch with violent behaviors (Sch+V, n = 34), Sch without violent behaviors (Sch-V, n = 28), and healthy controls (HC, n = 21). Structural neuroimaging analyses were performed across groups to assess gray matter volume (GMV) and cortical thickness (CT) differences in regions previously implicated in aggressive behaviors. Results: The data revealed significant reductions in GMV in the right amygdala and diminished cortical thickness (CT) in the bilateral dorsolateral prefrontal cortices (dlPFC) in patients with Sch+V compared to patients with Sch-V and HCs. Right amygdalar volume also demonstrated a negative correlational trend with hostility scores in patients with Sch+V. Conclusions: These findings underscore disruptions in the structural integrity of the dlPFC—responsible for inhibitory control—and the amygdala—central to emotional processing in violent patients with Sch. Future research should aim to investigate potential functional interactions at a network level to gain a deeper understanding of the neurobiological underpinnings of violent behaviors in this population. Full article

Pepper golden mosaic virus (PepGMV) is a bipartite begomovirus of pepper and tomato from North America. In ‘Anaheim’ pepper plants PepGMV-Mo strain (Mo) causes systemic yellow foliar mosaic symptoms, while PepGMV-D strain (D) causes distortion of 1st–6th expanding leaves, and asymptomatic infection of subsequently developing leaves, like other known ‘recovery’ phenotypes. Infections established with DNA-A Mo and D components expressing red-shifted green fluorescent protein in place of coat protein and in situ hybridization, showed PepGMV-Mo localized to phloem and mesophyll cells, while -D was mesophyll restricted. Alignment of PepGMV-Mo and -D DNA-B components revealed three indels upstream of the BC1 gene that encodes the movement protein (MP). To determine if this non-coding region (*BC1) D-strain MP putative promoter contributed to ‘recovery’, plants were inoculated with chimeric DNA-B Mo/D components harboring reciprocally exchanged *BC1, and wild-type DNA-A Mo and D components. Symptoms were reminiscent but not identical to wild-type -Mo or -D infection, respectively, suggesting ‘recovery’ cannot be attributed solely to the *BC1. Both BC1 and D*BC1 were targeted by post-transcriptional gene silencing; however, ‘recovered’ leaves accumulated fewer transcripts and 21–24 nt vsiRNAs. Thus, inefficient in planta movement of PepGMV-D is associated with a non-pepper-adapted ‘defective’ BC1 that facilitates hyper-efficient PTGS, leading to BC1 transcript degradation that in turn limits virus spread, thereby recapitulating disease ‘tolerance’. Full article