23 papers · ranked by Valyu relevance
Siva Venkadesh, Wen-Jieh Linn, Yuhe Tian, G Allan Johnson + 1 more
We integrate tracer-derived projection polarity from ∼1,200 mouse injections with species-specific diffusion MRI (dMRI) tractography to construct directed connectomes for mouse, marmoset, rhesus macaque, and human. We model brain circuitry as a directed connectome, in which asymmetric pathways capture the forward flow…
Siva Venkadesh, Wen-Jieh Linn, Yuhe Tian, G Allan Johnson + 1 more
Understanding how brain networks support cognition requires knowing not only which regions are connected but the direction in which neuronal signals propagate. However, directed connectivity cannot be measured non-invasively in primates or humans, limiting systems-level inference. Here we integrate projection polarity…
Kayson Fakhar, Fatemeh Hadaeghi, Caio Seguin, Shrey Dixit + 4 more
Communication in brain networks is the foundation of cognitive function and behavior. A multitude of evolutionary pressures, including the minimization of metabolic costs while maximizing communication efficiency, contribute to shaping the structure and dynamics of these networks. However, how communication efficiency…
Carlo Cafaro, Shannon Ray, Paul M. Alsing
We present an information geometric characterization of quantum driving schemes specified by su (2; C) time-dependent Hamiltonians in terms of both complexity and efficiency concepts. Specifically, starting from pure output quantum states describing the evolution of a spin-1/2 particle in an external time-dependent…
Hanzhang Chen, Xiangzhi Zhang, Shufeng Gong, Feng Yao + 3 more
Networks with Restrictions Authors: ['Hanzhang Chen' 'Xiangzhi Zhang' 'Shufeng Gong' 'Feng Yao' 'Song Yu' 'Yanfeng Zhang' 'Ge Yu'] Path planning is a fundamental problem in road networks, with the goal of finding a path that optimizes objectives such as shortest distance or minimal travel time. Existing methods…
Leonardo Bellocchi, Vito Latora, Nikolas Geroliminis
Spatial systems that experience congestion can be modeled as weighted networks whose weights dynamically change over time with the redistribution of flows. This is particularly true for urban transportation networks. The aim of this work is to find appropriate network measures that are able to detect critical zones for…
Kevin Y. Chen
Finding the shortest path between two points in a graph is a fundamental problem that has been well-studied over the past several decades. Shortest path algorithms are commonly applied to modern navigation systems, so our study aims to improve the efficiency of an existing algorithm on large-scale Euclidean networks.…
Ming Hu, Shuhai Jiang, Kangqian Zhou, Xunan Cao + 2 more
'Andrey V. Savkin'] The A algorithm is widely used in mobile robot path planning; however, it faces challenges such as unsmooth planned paths, redundant nodes, and extensive search areas. This paper proposes a hybrid algorithm combining an improved A algorithm with the Dynamic Window Approach. By quantifying grid…
Olena Doroshenko
Pathfinding in complex topographies poses a challenge with applications extending from urban planning to autonomous navigation. While numerous algorithms offer potential solutions, their comparative efficiency and reliability when confronted with nonlinear terrains remain to be systematically evaluated. This study…
Wei-Chang Yeh
This paper proposes earliest and latest path algorithms based on binary weight allocation, assigning weights of 2(i-1) and 2(m-i) to the i-th arc in a network. While traditional shortest path algorithms optimize only distance, our approach leverages Binary-Addition-Tree ordering to efficiently identify…
N. Mookhambika, J. Raja, K. Srihari
In a sensor network, a sensor node does not aggregate the data packets efficiently, since the packet is dropped for poor connection between the sensor nodes in the network. The sensor node location is varied in every area, so infrequent to share the information with its neighbor by the sender node. The communication is…
Yongliang Shi, Shucheng Huang, Mingxing Li, Wenling Li
Path planning is a core technology for mobile robots. However, existing state-of-the-art methods suffer from issues such as excessive path redundancy, too many turning points, and poor environmental adaptability. To address these challenges, this paper proposes a novel global and local fusion path-planning algorithm.…
Stefan Zondag, Jasper Schuurmans, Arnab Chaudhuri, Robin Visser + 6 more
Photocatalysis for small molecule activation has seen significant advancements over the past decade, yet its scale-up remains a challenge due to photon attenuation effects. A promising solution lies in harnessing high photonic intensities paired with continuous-flow reactor technology. However, a deep grasp of photon…
Authors not listed
Every ten years the photovoltaic market grows tenfold, driven by increasing cell efficiencies and lower manufacturing and installation costs. If the next decade maintains this trend it must be via a technological transformation: The first commercial silicon-based devices that exceed the 29.4% efficiency limit of…
Shin-ichi Koda, Shinji Saito
This study introduces correlated flat-bottom elastic network model (CFB-ENM), an extension of our recently developed flat-bottom elastic network model (FB-ENM) for generating plausible reaction paths. While FB-ENM improved upon the widely used image-dependent pair potential (IDPP) by addressing unintended structural…
Zengyang Gong, Yuxiang Zeng, Lei Chen
Querying the shortest path between two vertexes is a fundamental operation in a variety of applications, which has been extensively studied over static road networks. However, in reality, the travel costs of road segments evolve over time, and hence the road network can be modeled as a time-dependent graph. In this…
Tianjiao Wang, Zengfu Wang, Bill Moran, Xinyu Wang + 2 more
'Zeashan Hameed Khan'] This paper compares three automated path-planning algorithms based on publicly available data. The algorithms include a Dijkstra-based algorithm (DBA) that improves on the straightforward application of Dijkstra’s algorithm, which restricts the path only to the grid edges. We present a fair and…
Rhyd Lewis
This paper describes the shortest path problem in weighted graphs and examines the differences in efficiency that occur when using Dijkstra's algorithm with a Fibonacci heap, binary heap, and self-balancing binary tree. Using C++ implementations of these algorithm variants, we find that the fastest method is not always…
Yung-Fu Chen, Kenneth Parker, Anish Arora
Routing in wireless meshes must detour around holes. Extant routing protocols often underperform in minimally connected networks where holes are larger and more frequent. Minimal density networks are common in practice due to deployment cost constraints, mobility dynamics, and/or adversarial jamming. Protocols that use…
Josh Neudorf, Shaylyn Kress, Ron Borowsky
The relationship between structural and functional connectivity in the human brain is a core question in network neuroscience, and a topic of paramount importance to our ability to meaningfully describe and predict functional outcomes. Graph theory has been used to produce measures based on the structural connectivity…
Authors not listed
Identifying synthesis routes from knowledge graphs poses challenges beyond retrosynthesis, including path–finding artifacts and data issues. We introduce “SynGPS”, a novel algorithm that overcomes these limitations by identifying viable routes even with common artifacts. SynGPS can resolve nonsensical cycles…
Authors not listed
Delocalized internal irradiation is a promising technique for intensification and scale-up of photochemical processes as it avoids the otherwise inevitable light concentration. In particular, wireless light emitters (WLEs) powered by resonant inductive coupling showed promise in previous studies. However, the achieved…
Anandha Prakash P, Radha R
This research presents a comprehensive electric vehicle (EV) routing framework designed to address the complex interplay of real-world constraints in EV navigation. The proposed system integrates spectral clustering, fuzzy reinforcement learning, and enhanced pathfinding algorithms to compute optimal routes while…