Urban Air Mobility has the potential to substantially reduce travel times in some cases of urban-related transportation. Travel time savings strongly depend on fast processing at vertiports, which ...presents a key challenge considering demand levels’ vertiports would experience when becoming an established mode of transport. This article sheds light on the passenger throughput vertiport airfields can manage and how the operations are sensitive to changes. One main contribution of this article is the introduction of hourly passenger throughput per area as a performance indicator that allows to compare vertiports of different sizes. VoloCity is studied as a reference vehicle and the resulting space requirement of the carefully specified baseline scenario is 188 square-meters per passenger per hour. A total of 13 prominent eVTOL designs are included in the study from which the current design space between maximum vehicle dimension and number of seats is deducted. The study shows that vehicles with a small maximum dimension yield the highest passenger throughput capacity. CityAirbus performs best (46.3 m
2
/PAX/h) with a diameter of 7.92 m and Archer Maker performs worst (221 m
2
/PAX/h) with a diameter of 12.2 m. How the performance indicators can be used as rules-of-thumb in the first-order estimations of vertiport throughput capacity or space requirement is described by means of illustrative examples. The insights presented in this paper might be useful for researches, vehicle developers, and municipalities alike.
Novel electric aircraft designs coupled with intense efforts from academia, government and industry led to a paradigm shift in urban transportation by introducing UAM. While UAM promises to introduce ...a new mode of transport, it depends on ground infrastructure to operate safely and efficiently in a highly constrained urban environment. Due to its novelty, the research of UAM ground infrastructure is widely scattered. Therefore, this paper selects, categorizes and summarizes existing literature in a systematic fashion and strives to support the harmonization process of contributions made by industry, research and regulatory authorities. Through a document term matrix approach, we identified 49 Scopus-listed scientific publications (2016–2021) addressing the topic of UAM ground infrastructure with respect to airspace operation followed by design, location and network, throughput and capacity, ground operations, cost, safety, regulation, weather and lastly noise and security. Last listed topics from cost onwards appear to be substantially under-represented, but will be influencing current developments and challenges. This manuscript further presents regulatory considerations (Europe, U.S., international) and introduces additional noteworthy scientific publications and industry contributions. Initial uncertainties in naming UAM ground infrastructure seem to be overcome; vertiport is now being predominantly used when speaking about vertical take-off and landing UAM operations.
Urban Air Mobility is a novel concept of transportation with unknown market potential. Even in conservative estimates, thousands of operations could be expected on a single vertiport. This exceeds ...known heliport operations, which is the most comparable existing mode of transport—by far. Vertiport operations, in particular the dynamics on the airfield, are not well understood; in the following article, we want to address this research gap. By using means of agent-based simulation, the following design drivers were identified: peaks in demand, imbalance between arrivals and departures, pad operations and gate operations. We calculate a practical hourly capacity of 264 movements for our baseline scenario consisting of 4 pads, 12 gates and 20 stand. We are further able to shown that avoiding this peak and staying below a maximum imbalance between arrivals and departures of less than 33 ensures an average passenger delay of less than 3 min. Lastly, we present a parameter study varying the number of pads and gates, the length of approach/departure and boarding/de-boarding and the level of demand. The results of this study are aggregated into a graphical design heuristic displaying the interchangeability of the mentioned aspects.
Participation in multimodal leisure activities, such as playing a musical instrument, may be protective against brain aging and dementia in older adults (OA). Potential neuroprotective correlates ...underlying musical activity remain unclear.
This cross-sectional study investigated the association between lifetime musical activity and resting-state functional connectivity (RSFC) in three higher-order brain networks: the Default Mode, Fronto-Parietal, and Salience networks.
We assessed 130 cognitively unimpaired participants (≥ 60 years) from the baseline cohort of the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study. Lifetime musical activity was operationalized by the self-reported participation in musical instrument playing across early, middle, and late life stages using the Lifetime of Experiences Questionnaire (LEQ). Participants who reported musical activity during all life stages (n = 65) were compared to controls who were matched on demographic and reserve characteristics (including education, intelligence, socioeconomic status, self-reported physical activity, age, and sex) and never played a musical instrument (n = 65) in local (seed-to-voxel) and global (within-network and between-network) RSFC patterns using pre-specified network seeds.
Older participants with lifetime musical activity showed significantly higher local RSFC between the medial prefrontal cortex (Default Mode Network seed) and temporal as well as frontal regions, namely the right temporal pole and the right precentral gyrus extending into the superior frontal gyrus, compared to matched controls. There were no significant group differences in global RSFC within or between the three networks.
We show that playing a musical instrument during life relates to higher RSFC of the medial prefrontal cortex with distant brain regions involved in higher-order cognitive and motor processes. Preserved or enhanced functional connectivity could potentially contribute to better brain health and resilience in OA with a history in musical activity.
German Clinical Trials Register (DRKS00007966, 04/05/2015).
White matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer's disease (AD) and their advanced detection and quantification can be beneficial for research ...and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.
We used a pseudo-randomly selected dataset (
= 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media were compared to manual reference segmentation (RS).
Across tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice's coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.
To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.
Although convolutional neural networks (CNNs) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet ...applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap as they allow the visualization of key input image features that drive the decision of the model. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge.
We trained a CNN for the detection of AD in N = 663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including in total N = 1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection.
Across the three independent datasets, group separation showed high accuracy for AD dementia versus controls (AUC ≥ 0.91) and moderate accuracy for amnestic MCI versus controls (AUC ≈ 0.74). Relevance maps indicated that hippocampal atrophy was considered the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r ≈ -0.86, p < 0.001).
The relevance maps highlighted atrophy in regions that we had hypothesized a priori. This strengthens the comprehensibility of the CNN models, which were trained in a purely data-driven manner based on the scans and diagnosis labels. The high hippocampus relevance scores as well as the high performance achieved in independent samples support the validity of the CNN models in the detection of AD-related MRI abnormalities. The presented data-driven and hypothesis-free CNN modeling approach might provide a useful tool to automatically derive discriminative features for complex diagnostic tasks where clear clinical criteria are still missing, for instance for the differential diagnosis between various types of dementia.
•Composite scores provide reliable metrics of domain function in multicenter cohort.•Visuo-spatial domain composite scores relate to anatomic changes in AD spectrum.•Domain scores relate to ...network-specific resting-state connectivity in AD spectrum.
Cognitive decline has been found to be associated with gray matter atrophy and disruption of functional neural networks in Alzheimer’s disease (AD) in structural and functional imaging (fMRI) studies. Most previous studies have used single test scores of cognitive performance among monocentric cohorts. However, cognitive domain composite scores could be more reliable than single test scores due to the reduction of measurement error. Adopting a multicentric resting state fMRI (rs-fMRI) and cognitive domain approach, we provide a comprehensive description of the structural and functional correlates of the key cognitive domains of AD.
We analyzed MRI, rs-fMRI and cognitive domain score data of 490 participants from an interim baseline release of the multicenter DELCODE study cohort, including 54 people with AD, 86 with Mild Cognitive Impairment (MCI), 175 with Subjective Cognitive Decline (SCD), and 175 Healthy Controls (HC) in the AD-spectrum. Resulting cognitive domain composite scores (executive, visuo-spatial, memory, working memory and language) from the DELCODE neuropsychological battery (DELCODE-NP), were previously derived using confirmatory factor analysis. Statistical analyses examined the differences between diagnostic groups, and the association of composite scores with regional atrophy and network-specific functional connectivity among the patient subgroup of SCD, MCI and AD.
Cognitive performance, atrophy patterns and functional connectivity significantly differed between diagnostic groups in the AD-spectrum. Regional gray matter atrophy was positively associated with visuospatial and other cognitive impairments among the patient subgroup in the AD-spectrum. Except for the visual network, patterns of network-specific resting-state functional connectivity were positively associated with distinct cognitive impairments among the patient subgroup in the AD-spectrum.
Consistent associations between cognitive domain scores and both regional atrophy and network-specific functional connectivity (except for the visual network), support the utility of a multicentric and cognitive domain approach towards explicating the relationship between imaging markers and cognition in the AD-spectrum.
INTRODUCTION
Soluble amyloid beta (Aβ) oligomers have been suggested as initiating Aβ related neuropathologic change in Alzheimer's disease (AD) but their quantitative distribution and chronological ...sequence within the AD continuum remain unclear.
METHODS
A total of 526 participants in early clinical stages of AD and controls from a longitudinal cohort were neurobiologically classified for amyloid and tau pathology applying the AT(N) system. Aβ and tau oligomers in the quantified cerebrospinal fluid (CSF) were measured using surface‐based fluorescence intensity distribution analysis (sFIDA) technology.
RESULTS
Across groups, highest Aβ oligomer levels were found in A+ with subjective cognitive decline and mild cognitive impairment. Aβ oligomers were significantly higher in A+T− compared to A−T− and A+T+. APOE ε4 allele carriers showed significantly higher Aβ oligomer levels. No differences in tau oligomers were detected.
DISCUSSION
The accumulation of Aβ oligomers in the CSF peaks early within the AD continuum, preceding tau pathology. Disease‐modifying treatments targeting Aβ oligomers might have the highest therapeutic effect in these disease stages.
Highlights
Using surface‐based fluorescence intensity distribution analysis (sFIDA) technology, we quantified Aβ oligomers in cerebrospinal fluid (CSF) samples of the DZNE‐Longitudinal Cognitive Impairment and Dementia (DELCODE) cohort
Aβ oligomers were significantly elevated in mild cognitive impairment (MCI)
Amyloid‐positive subjects in the subjective cognitive decline (SCD) group increased compared to the amyloid‐negative control group
Interestingly, levels of Aβ oligomers decrease at advanced stages of the disease (A+T+), which might be explained by altered clearing mechanisms
Urban air mobility (UAM) is the idea of creating a future mobility market through the introduction of a new mode of aerial transport with substantial travel time advantages. A key factor diminishing ...travel time savings is vertiport processes. So far, vertiport throughput capacity has only been studied in a static manner using analytical methods, which has been found to be insufficient. This paper wants to increase the level of understanding of operational dynamics on vertiport airfields by being the first to apply agent-based simulation. For this purpose, an existing vertiport model consisting of pads, gates and stands was refined through two means. First, a sensitivity study with over 100 simulations was executed shedding light on the driving processes on a vertiport airfield. Second, an expert interview series with 17 participants was conducted, letting the experts evaluate the model and specify relevant parameter values. Three main results should find mention here: (1) Pad operations were identified to be most impactful on passenger delays. (2) Pad and gate processes have a threshold capacity beyond which delays increase exponentially. (3) A refined vertiport model is presented, including the 27 most relevant parameters and their value specification. In conclusion, this paper finds that optimized vertiport airfield design is crucial to UAM operations, and dynamic passenger and vehicle interactions cannot be neglected.
Inferior frontal sulcal hyperintensities (IFSHs) on fluid-attenuated inversion recovery (FLAIR) sequences have been proposed to be indicative of glymphatic dysfunction. Replication studies in large ...and diverse samples are nonetheless needed to confirm them as an imaging biomarker. We investigated whether IFSHs were tied to Alzheimer's disease (AD) pathology and cognitive performance. We used data from 361 participants along the AD continuum, who were enrolled in the multicentre DELCODE study. The IFSHs were rated visually based on FLAIR magnetic resonance imaging. We performed ordinal regression to examine the relationship between the IFSHs and cerebrospinal fluid-derived amyloid positivity and tau positivity (Aβ42/40 ratio ≤ 0.08; pTau181 ≥ 73.65 pg/mL) and linear regression to examine the relationship between cognitive performance (i.e., Mini-Mental State Examination and global cognitive and domain-specific performance) and the IFSHs. We controlled the models for age, sex, years of education, and history of hypertension. The IFSH scores were higher in those participants with amyloid positivity (OR: 1.95, 95% CI: 1.05-3.59) but not tau positivity (OR: 1.12, 95% CI: 0.57-2.18). The IFSH scores were higher in older participants (OR: 1.05, 95% CI: 1.00-1.10) and lower in males compared to females (OR: 0.44, 95% CI: 0.26-0.76). We did not find sufficient evidence linking the IFSH scores with cognitive performance after correcting for demographics and AD biomarker positivity. IFSHs may reflect the aberrant accumulation of amyloid β beyond age.
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