This letter investigates the optimal hovering altitude of a single UAV toprovide coverage over any convex quadrilateral region on the ground. The UAVemploys a directional antenna with a tiltable beam, producing an ellipticalcoverage pattern. Two scenarios are considered: (1) inscribing the largestellipse within the quadrilateral to cover its interior, and (2) circumscribingthe smallest ellipse about the quadrilateral to ensure full coverage. We derivethe optimal UAV altitude and antenna tilt conditions in both scenarios for asimplified yet widely accepted path loss model and present numerical resultsfor coverage efficiency. The work contributes to the development ofenergy-efficient UAV-based communication systems. <<<

AbstractThe burgeoning interest in in situ multiplexed gene expression profiling technologies has opened new avenues for understanding cellular behavior and interactions. In this study, we present a comparative benchmark analysis of six in situ gene expression profiling methods, including both commercially available and academically developed methods, using publicly accessible mouse brain datasets. We find that standard sensitivity metrics, such as the number of unique molecules detected per cell, are not directly comparable across datasets due to substantial differences in the incidence of off-target molecular artifacts impacting specificity. To address these challenges, we explored various potential sources of molecular artifacts, developed novel metrics to control for them, and utilized these metrics to evaluate and compare different in situ technologies. Finally, we demonstrate how molecular false positives can seriously confound spatially-aware differential expression analysis, requiring caution in the interpretation of downstream results. Our analysis provides guidance for the selection, processing, and interpretation of in situ spatial technologies. <<<

Hua Yang, Yang Xun, Yali Shen, Hongtao Wang, Yu Tao, Huihan Wang, Xinyue Zhang, Rongqiu Liu, Huarong Yu, Li Wei, Jinsong Yan, Xiaoyu Zhu, Hua You <<<

Xinyuan Liang, Lianglong Sun, Xuhong Liao, Tianyuan Lei, Mingrui Xia, Dingna Duan, Zilong Zeng, Qiongling Li, Zhilei Xu, Weiwei Men, Yanpei Wang, Shuping Tan, Jia-Hong Gao, Shaozheng Qin, Sha Tao, Qi Dong, Tengda Zhao, Yong He <<<

AbstractCortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence. <<<

Shuyang Yao, Arvid Harder, Fahimeh Darki, Yu-Wei Chang, Ang Li, Kasra Nikouei, Giovanni Volpe, Johan N Lundström, Jian Zeng, Naomi Wray, Yi Lu, Patrick F Sullivan, Jens Hjerling-Leffler <<<

AbstractUnderstanding the temporal and spatial brain locations etiological for psychiatric disorders is essential for targeted neurobiological research. Integration of genomic insights from genome-wide association studies with single-cell transcriptomics is a powerful approach although past efforts have necessarily relied on mouse atlases. Leveraging a comprehensive atlas of the adult human brain, we prioritized cell types via the enrichment of SNP-heritabilities for brain diseases, disorders, and traits, progressing from individual cell types to brain regions. Our findings highlight specific neuronal clusters significantly enriched for the SNP-heritabilities for schizophrenia, bipolar disorder, and major depressive disorder along with intelligence, education, and neuroticism. Extrapolation of cell-type results to brain regions reveals important patterns for schizophrenia with distinct subregions in the hippocampus and amygdala exhibiting the highest significance. Cerebral cortical regions display similar enrichments despite the known prefrontal dysfunction in those with schizophrenia highlighting the importance of subcortical connectivity. Using functional MRI connectivity from cases with schizophrenia and neurotypical controls, we identified brain networks that distinguished cases from controls that also confirmed involvement of the central and lateral amygdala, hippocampal body, and prefrontal cortex. Our findings underscore the value of single-cell transcriptomics in decoding the polygenicity of psychiatric disorders and offer a promising convergence of genomic, transcriptomic, and brain imaging modalities toward common biological targets. <<<

Elena Beanato, Hyuk-June Moon, Fabienne Windel, Pierre Vassiliadis, Maximillian J. Wessel, Traian Popa, Menoud Pauline, Esra Neufeld, Emanuela De Falco, Baptiste Gauthier, Melanie Steiner, Olaf Blanke, Friedhelm C. Hummel <<<

Because of the depth of the hippocampal-entorhinal complex (HC-EC) in the brain, understanding of its role in spatial navigation via neuromodulation was limited in humans. Here, we aimed to better elucidate this relationship in healthy volunteers, using transcranial temporal interference electric stimulation (tTIS), a noninvasive technique allowing to selectively neuromodulate deep brain structures. We applied tTIS to the right HC-EC in either continuous or intermittent theta-burst stimulation patterns (cTBS or iTBS), compared to a control condition, during a virtual reality–based spatial navigation task and concomitant functional magnetic resonance imaging. iTBS improved spatial navigation performance, correlated with hippocampal activity modulation, and decreased grid cell–like activity in EC. Collectively, these data provide the evidence that human HC-EC activity can be directly and noninvasively modulated leading to changes of spatial navigation behavior. These findings suggest promising perspectives for patients suffering from cognitive impairment such as following traumatic brain injury or dementia. <<<

AbstractThe hippocampal-entorhinal system uses cognitive maps to represent spatial knowledge and other types of relational information, such as the transition probabilities between objects. However, objects can often be characterized in terms of different types of relations simultaneously, e.g. semantic similarities learned over the course of a lifetime as well as transitions experienced over a brief timeframe in an experimental setting. Here we ask how the hippocampal formation handles the embedding of stimuli in multiple relational structures that differ vastly in terms of their mode and timescale of acquisition: Does it integrate the different stimulus dimensions into one conjunctive map, or is each dimension represented in a parallel map? To this end, we reanalyzed functional magnetic resonance imaging (fMRI) data from Garvert et al. (2017) that had previously revealed an entorhinal map which coded for newly learnt statistical regularities. We used a triplet odd-one-out task to construct a semantic distance matrix for presented items and applied fMRI adaptation analysis to show that the degree of similarity of representations in bilateral hippocampus decreases as a function of semantic distance between presented objects. Importantly, while both maps localize to the hippocampal formation, this semantic map is anatomically distinct from the originally described entorhinal map. This finding supports the idea that the hippocampal-entorhinal system forms parallel cognitive maps reflecting the embedding of objects in diverse relational structures. <<<

Noninvasive prenatal testing (NIPT) for the sex chromosome aneuploidies (45,X, 47,XXY, 47,XXX, and 47,XYY) differs significantly from that for the autosomal aneuploidies (trisomy 13, 18, and 21). As a group, sex chromosome aneuploidies occur more commonly (1/400) than any one isolated autosomal aneuploidy, the phenotypic variation is greater, the role of mosaicism more challenging, and the positive predictive value of a high-risk NIPT result is substantially lower. These considerations should be identified during pretest counseling, the inclusion of sex chromosome testing offered separately, and the differences from autosomal aneuploidy NIPT clearly delineated. <<<

Nga Yan Tse, Aswin Ratheesh, Ye Ella Tian, Colm G. Connolly, Christopher G. Davey, Saampras Ganesan, Ian H. Gotlib, Ben J. Harrison, Laura K. M. Han, Tiffany C. Ho, Alec J. Jamieson, Jaclyn S. Kirshenbaum, Yong Liu, Xiaohong Ma, Amar Ojha, Jiang Qiu, Matthew D. Sacchet, Lianne Schmaal, Alan N. Simmons, John Suckling, Dongtao Wei, Xiao Yang, Tony T. Yang, Robin F. H. Cash, Andrew Zalesky <<<

Classical optimization and learning-based methods are the two reigningparadigms in deformable image registration. While optimization-based methodsboast generalizability across modalities and robust performance, learning-basedmethods promise peak performance, incorporating weak supervision and amortizedoptimization. However, the exact conditions for either paradigm to perform wellover the other are shrouded and not explicitly outlined in the existingliterature. In this paper, we make an explicit correspondence between themutual information of the distribution of per-pixel intensity and labels, andthe performance of classical registration methods. This strong correlationhints to the fact that architectural designs in learning-based methods isunlikely to affect this correlation, and therefore, the performance oflearning-based methods. This hypothesis is thoroughly validated withstate-of-the-art classical and learning-based methods. However, learning-basedmethods with weak supervision can perform high-fidelity intensity and labelregistration, which is not possible with classical methods. Next, we show thatthis high-fidelity feature learning does not translate to invariance to domainshift, and learning-based methods are sensitive to such changes in the datadistribution. Finally, we propose a general recipe to choose the best paradigmfor a given registration problem, based on these observations. <<<

Zhaolian Lu, Shanlan Mo, Duo Xie, Xiangwei Zhai, Shanjun Deng, Kantian Zhou, Kun Wang, Xueling Kang, Hao Zhang, Juanzhen Tong, Liangzhen Hou, Huijuan Hu, Xuefei Li, Da Zhou, Leo Tsz On Lee, Li Liu, Yaxi Zhu, Jing Yu, Ping Lan, Jiguang Wang, Zhen He, Xionglei He, Zheng Hu <<<

In the last ten years, different concepts of electric vertical take-off and landing aircrafts (eVTOLs) have been tested. This article addresses the problem of the choice of the best configuration. VTOLs built since the fifties are presented and their advantages, disadvantages, and problems are discussed. Three representative eVTOLs, one for each main configuration, are compared on five main parameters and three reference missions. The parameters are disk loading, total hover time, cruise speed, practical range, and flight time. The performance of the eVTOLs on the urban, extra-urban, and long-range mission is evaluated computing the time and energy required. The results show that the best configuration depends on the mission. The multirotor is more efficient in hover. The vectored thrust jet is more efficient in cruise and has a higher range. The lift + cruise is a compromise. <<<

Rasmus Siersbæk, Jesper Grud Skat Madsen, Biola Maria Javierre, Ronni Nielsen, Emilie Kristine Bagge, Jonathan Cairns, Steven William Wingett, Sofie Traynor, Mikhail Spivakov, Peter Fraser, Susanne Mandrup <<<