Multiscale Interactions Research Articles

Radiative cooling sorbent towards all weather ambient water harvesting

Emerging atmospheric water harvesting (AWH) technologies hold promise for water supply to underdeveloped regions with limited access to liquid water resources. The prevailing AWH systems, including condensation- or sorption-based, mostly rely on a single mechanism limited by working conditions and inferior performance. Here, we synergistically integrate multiple mechanisms, including thermosorption effect, radiative cooling, and multiscale cellulose-water interactions to improve the water harvesting performance with minimal active energy input over a relative humidity (RH) range between 8% to 100%. The proposed system consists of a scalable and sustainable cellulose scaffold impregnated with hygroscopic lithium chloride (LiCl). Cellulose scaffold and LiCl synergistically interact with water at molecular, nanometer, and micrometer scales, achieving a high yield (2.5–16 kg kg−1 at 60–90% RH). The captured water in return facilitates radiative cooling due to its intrinsically high infrared emissivity. An outdoor batch-mode AWH device shows a water uptake up to 6.75 L kg−1 day−1 with a material cost as low as 3.15–5.86 USD kg−1. A theoretical model is also proposed to elucidate the synergistic AWH mechanisms among cellulose-LiCl-water-energy interaction. This AWH strategy provides a potential solution to water scarcity problems in regions with larger seasonal and climate variations, especially arid areas.

Seismic wave propagation analysis in the framework of generalized continuum mechanics theory

For the problems of seismic wave propagation, scale effects will appear while considering the microstructures of medium. Scale effects mean that new components of wave fields appear in the seismograms due to the microstructure interactions in the medium and vary with the change of the characteristic length scale parameters. The generalized continuum mechanics (GCM) theory which introduces the intrinsic length scales of the microstructures is suitable for analyzing the scale effects of seismic wave propagation. We adopt the concept of multi-scale microstructure interactions, that is, the modified couple stress theory, and the one-parameter second strain gradient theory, as two branches of the GCM theory, have the same definition characteristic length scale parameters of medium, to describe the microstructure interactions at different scales. Through the quantitative relationship between the characteristic length scale parameters of the medium and the micropore, the layered model of the characteristic length scale parameters of the micropore is constructed for numerical modeling in a unified framework, and the scale effects of seismic wave propagation is analyzed. More specifically, the asymmetric elastic wave equations under a unified framework are derived, and the physical definition of the characteristic length scale parameters of medium is given. And the influence of the characteristic length scale parameter of the micropore on the seismic wave propagation is focused on. Finally, the scale effects of seismic waves excited by high-speed trains under the viaduct system are analyzed, and some conclusions are drawn.

Graph Learning for Interactive Threat Detection in Heterogeneous Smart Home Rule Data

The interactions among automation configuration rule data have led to undesired and insecure issues in smart homes, which are known as interactive threats. Most existing solutions use program analysis to identify interactive threats among automation rules, which is not suitable for closed-source platforms. Meanwhile, security policy-based solutions suffer from low detection accuracy because the pre-defined security policies in a single platform can hardly cover diverse interactive threat types across heterogeneous platforms. In this paper, we propose Glint, the first graph learning-based system for interactive threat detection in smart homes. We design a multi-scale graph representation learning model, called ITGNN, for both homogeneous and heterogeneous interaction graph pattern learning. To facilitate graph learning, we build large interaction graph training datasets by multi-domain data fusion from five different platforms. Moreover, Glint detects drifting samples with contrastive learning and improves the generalization ability with transfer learning across heterogeneous platforms. Our evaluation shows that Glint achieves 95.5% accuracy in detecting interactive threats across the five platforms. Besides, we examine a set of user-designed blueprints in the Home Assistant platform and reveal four new types of real-world interactive threats, called "action block", "action ablation", "trigger intake", and "condition duplicate", which are cross-platform interactive threats captured by Glint.

Multiscale Structural Mechanics of Rotary Shaft Seals: Numerical Studies and Visual Experiments

Although rotary shaft seals have been used successfully in many industrial applications for decades, their tribological behavior is still not completely understood. In-depth knowledge of the structural mechanics is essential for the design and optimization of such sealing systems. High complexity results from the multiscale interactions in the tribological system rotary shaft seal. Large macroscopic deformations occur due to the hyperelastic material behavior of elastomers coupled with microscopic tangential distortions of the sealing edge surface in the contact area. This paper includes both numerical and experimental studies on the tribological behavior of rotary shaft seals. A multiscale finite element model provides the simulation of the macroscopic deformations and the microscopic displacements. A test rig equipped with a hollow glass shaft enables in situ visual contact analyses, qualitative determinations of pressure distributions and quantitative measurements of elastomer surface distortions. The optical phenomenon of frustrated total internal reflection enables qualitative evaluations of the pressure distribution. Particle image velocimetry (PIV) is employed to quantify the tangential distortions. The test rig enables the measurement of the friction torque with the same configuration. The results of the numerical and experimental investigations for the radial load, friction torque and tangential distortions are compared and discussed. This serves to validate the simulation methods and the correlation of the measured parameters. This finally results in a solid and validated basis for further tribological investigations of rotary shaft seals.

Multi-Scale Interactions Between Augmented Reality and Virtual Reality Users in Mixed Reality Environment

Multi-scale interaction in Mixed Reality (MR) allows the avatars to shrink down themselves into a small size or enlarge into giant size. Multi-scale in MR is important in some situations that required precise avatar’s measurements to interact and manipulate with the content. However, the correct or appropriate scaling for multi-scale still remain unsolved in MR, very less people work in Augmented Reality (AR). It is critical to align precisely the way humans perceive the virtual world with the ways perceiving the real world. Therefore, this paper aims to produce a correct multi-scale technique for VR and AR users in MR environment. This paper presents a preliminary study on the previous works multi-scale techniques for MR remote collaboration. Then it explains the development of a multi-scale interaction between VR and AR users for the MR environment. Finally, this paper shows the results and implement the technique into an application. The results used to measure how multi-scale interaction can be leveraged with MR technology. The remote MR application involves AR and VR users with different interaction techniques.

Multiscale Interfacial Interactions in Carbon Nanotube–Asphalt Nanocomposites: Implications for Asphalt Pavement Materials

Carbon nanotube (CNT)–asphalt nanocomposites are considered to be the next generation of pavement materials; however, the interaction between CNT and asphalt at the interface and the mechanisms of property enhancement are not well understood, which limits the application of CNT–asphalt nanocomposites. In this study, CNT is used as a representative of one-dimensional nanomaterials, and the interfacial multiscale interaction mechanism between CNT and asphalt molecules is investigated by density functional theory (DFT), molecular dynamics simulation, atomic force microscopy (AFM), gelation permeation chromatography (GPC), Fourier transform infrared spectroscopy (FTIR), and performance evaluation. It has been shown that CNT and asphalt substrates are very compatible at the atomic scale, mainly due to π–π stacking, mechanical entanglement, and van der Waals forces. The interfacial energy barrier is −2.63 (kcal/mol)/Å2 and the shear barriers are 52.70 MPa, with asphaltene and aromatic making the greatest contribution to interfacial stress transfer. This research provides a theoretical basis for the targeted tuning of properties and establishes the basis for CNT–asphalt nanocomposites for highway applications.

A Simple Approach for Disentangling Vortical and Wavy Motions of Oceanic Flows

Abstract A long-standing challenge in dynamical oceanography is to distinguish nonlinearly intermingled dynamical regimes of oceanic flows. Conventional approaches focus on time-scale or space-scale decomposition. Here, we pursue a dynamics-based decomposition, where a mean flow is introduced to extend the classic theory of wavy and vortical modes. Mainly based on relative magnitudes of the relative vorticity and the modified horizontal divergence in spectral space, the full flow is decomposed into wavy and vortical motions. The proposed approach proves simple and efficient and can be used particularly for online disentangling vortical and wavy motions of the simulated flows by ever-popular tide-resolving high-resolution numerical models. This dynamical approach, combined with conventional time-scale- or space-scale-based approaches, paves the way for online mixing parameterizations using model simulated vortical (for isopycnal mixing) and wavy (for diapycnal mixing) motions and for understanding of multiregime and multiscale interactions of oceanic flows.

Multi-symmetry high-entropy relaxor ferroelectric with giant capacitive energy storage

Relaxor ferroelectric ceramics with remarkable energy storage performance, which is dominantly determined by polarization and breakdown strength, are one of the bottlenecks for next generation high/pulsed power dielectric capacitors. Herein, we report that high-entropy composition Li2CO3-densified Bi0.2Na0.2Ba0.2Sr0.2Ca0.2TiO3 achieves a giant recoverable energy density (Wrec) of 10.7 J/cm3 and an ultrahigh efficiency (η) of 89 %. To understand the mechanism, the influence of the high-entropy effect on atomic-scale polarization configuration and macroscale electrical properties has been investigated systematically. Randomly distributed A-site ions and B-site ions form complex interactions, which lead to coexisted atomic-scale low crystallographic symmetries, and thus, high-dynamic polar nanoregions as well as “intermediate polarization”, such multiple symmetry polarization configuration ensures fast and strong polarization response. On the other hand, the high-entropy system exhibits a wide band gap, helping to reduce conductivity and delay breakdown. Moreover, stable high-entropy structure brings great advantages for enhancing the thermal/frequency stability of energy storage performance. This work not only provides a material candidate with outstanding comprehensive energy storage performance but also affirms high-entropy approach is a shortcut to optimizing functional property by multi-scale interactions between polarization, microstructure and crystal structure.

The heterarchical life and spatial analyses of the historical Buddhist temples in the Chiang Saen Basin, Northern Thailand

Social hierarchy is the most prominent framework scholars use to examine settlement structure and development in Southeast Asia's pre- and post-state eras. The concept of social heterarchy, an unfixed ranked and diversified form of social structure, is an alternative approach to examining the sociopolitical organization of early settlements in the region. However, applications of heterarchy are limited in archaeological research on the sociopolitical organization and social landscape in Southeast Asian state societies. This paper incorporates space syntax and GIS angular and viewshed analyses to understand how sociopolitical interactions were arranged through the spatial configurations of the historical Buddhist temples in Chiang Saen, Thailand. This paper explores the complex interactions between various historical Chiang Saen social and religious groups through their temple spaces across time. Temple spatial characteristics indicate heterarchical forms of organization—evidenced by the hybrid and nonhierarchical temple spatial patterns characterized by open accessibility and integrated and symmetrical organization of spaces—co-existed with hierarchical relationships from the 13th to 17th century. The approach discussed here provides a better understanding of the multiscale relationships and interactions among sociopolitical groups in the historical communities in Chiang Saen, enabling a broader view that can embrace the co-occurrence of hierarchical and heterarchical forms of governance.

Towards a Transnational Approach to Transboundary Haze Pollution: Governing Traditional Farming in Fire-Prone Regions of Indonesia

AbstractIn Indonesia, swidden practices have been part of traditional rice farming for centuries. Swidden agriculture is a fundamental part of all remaining large tropical forests and provides a critical form of biodiversity-friendly agriculture. Meanwhile, peatland degradation and land conversion for oil palm plantation and agriculture have created an annual transboundary environmental disaster in Southeast Asia. This article adopts a transnational lens to highlight the complex multi-scale interactions that perpetuate recurring transboundary air pollution in the region. Having examined the traditional practices of swidden agriculture in Central Kalimantan and South Sumatra (Indonesia), the article reveals that swidden agriculture has been misunderstood generally, and in particular in international and national law and policy. It argues that existing laws fail to identify the important role that swidden agriculture plays in sustainable ecosystem management and cultural expression. Nuanced understandings of fire use, alongside transnational multi-stakeholder and multi-scale approaches, are required.

Wind and Turbulence Effects on Raindrop Fall Speed

Abstract Wind and turbulence effects on raindrop fall speeds were elucidated using field observations over a 2-yr time period. Motivations for this study include the recent observations of raindrop fall speed deviations from the terminal fall speed predictions (Vt) based upon laboratory studies and the utilizations of these predictions in various important meteorological and hydrological applications. Fall speed (Vf) and other characteristics of raindrops were observed using a high-speed optical disdrometer (HOD), and various rainfall and wind characteristics were observed using a 3D ultrasonic anemometer, a laser-type disdrometer, and rain gauges. A total of 26 951 raindrops were observed during 17 different rainfall events, and of these observed raindrops, 18.5% had a subterminal fall speed (i.e., 0.85Vt ≥ Vf) and 9.5% had a superterminal fall speed (i.e., 1.15Vt ≤ Vf). Our observations showed that distributions of sub- and superterminal raindrops in the raindrop size spectrum are distinct, and different physical processes are responsible for the occurrence of each. Vertical wind speed, wind shear, and turbulence were identified as the important factors, the latter two being the dominant ones, for the observed fall speed deviations. Turbulence and wind shear had competing effects on raindrop fall. Raindrops of different sizes showed different responses to turbulence, indicating multiscale interactions between raindrop fall and turbulence. With increasing turbulence levels, while the raindrops in the smaller end of the size spectrum showed fall speed enhancements, those in the larger end of the size spectrum showed fall speed reductions. The effect of wind shear was to enhance the raindrop fall speed toward a superterminal fall.

Distinct Influences of Two Boreal Summer Intraseasonal Oscillation Modes on Synoptic-Scale Eddies over the Western North Pacific

Abstract The boreal summer intraseasonal oscillation (BSISO), which consists of a 10–30-day component and a 30–90-day component, is vigorous over the East Asian and the western North Pacific (WNP) monsoon regions where synoptic-scale eddies are also active. In this study, we systematically compare and diagnose the modulating effects of the 10–30- and 30–90-day BSISO modes on the development and maintenance of the WNP synoptic-scale eddies in terms of eddy energetics. During the developing phase of the synoptic eddies, the eddies tend to grow faster under the background conditions associated with the 10–30-day BSISO mode, compared with that associated with the 30–90-day mode, indicating the importance of the 10–30-day mode in eddy development. In contrast, the 30–90-day BSISO mode shows a larger contribution to the maintenance of the synoptic eddy intensity after the eddies reach their maximum amplitude. On the basis of the diagnoses of the eddy kinetic energy (EKE) budget equation, we find that the positive EKE advection induced by the 10–30-day flow is the leading process resulting in the increased EKE for eddy development. However, the 30–90-day circulation anomalies provide long-lasting favorable conditions (relative to those of the 10–30-day anomalies) to maintain the eddy intensity by generating a positive barotropic energy conversion from 30- to 90-day kinetic energy to EKE. These results not only advance our understanding of multiscale interactions over the WNP but also help toward better monitoring and prediction of synoptic-scale eddies, including tropical cyclones, using the background BSISO information. Significance Statement The western North Pacific is a region with active but complex multiscale interactions among synoptic-scale disturbances, intraseasonal oscillation, and low-frequency background monsoonal activity. The relative effects of 10–30- and 30–90-day intraseasonal variability on the synoptic-scale disturbances were quantitatively examined based on the eddy kinetic energy budget analysis. The results show that the 10–30-day (30–90-day) mode of intraseasonal oscillations plays a key role in the growth (maintenance) of synoptic-scale disturbances through the advection (barotropic energy conversion) process. The results suggest the implication of monitoring and predicting the activity of synoptic-scale disturbances using the information of two different intraseasonal modes.

AsiaPEX: Challenges and Prospects in Asian Precipitation Research

Abstract The Asian Precipitation Experiment (AsiaPEX) was initiated in 2019 to understand terrestrial precipitation over diverse hydroclimatological conditions for improved predictions, disaster reduction, and sustainable development across Asia under the framework of the Global Hydroclimatology Panel (GHP)/Global Energy and Water Exchanges (GEWEX). AsiaPEX is the successor to GEWEX Asian Monsoon Experiment (GAME; 1995–2005) and Monsoon Asian Hydro-Atmosphere Scientific Research and Prediction Initiative (MAHASRI; 2006–16). While retaining the key objectives of the aforementioned projects, the scientific targets of AsiaPEX focus on land–atmosphere coupling and improvements to the predictability of the Asian hydroclimatological system. AsiaPEX was designed for both fine-scale hydroclimatological processes occurring at the land surface and the integrated Asian hydroclimatological system characterized by multiscale interactions. We adopt six approaches including observation, process studies, scale interactions, high-resolution hydrological modeling, field campaigns, and climate projection, which bridge gaps in research activities conducted in different regions. Collaboration with mesoscale and global modeling researchers is one of the core methods in AsiaPEX. We review these strategies based on the literature and our initial outcomes. These include the estimation and validation of high-resolution satellite precipitation, investigations of extreme rainfall mechanisms, field campaigns over the Maritime Continent and Tibetan Plateau, areas of significant impact on the entire AsiaPEX region, process studies on diurnal- to interdecadal-scale interactions, and evaluation of the predictabilities of climate models for long-term variabilities. We will conduct integrated observational and modeling initiative, the Asian Monsoon Year (AMY)-II around 2025–28, whose strategies are the subregional observation platforms and integrated global analysis.

Multi-Scale Human-Object Interaction Detector

Transformers are transforming the landscape of computer vision, especially for image-level recognition and instance-level detection tasks. Human-object interaction detection transformer (HOI-TR) is the first transformer-based end-to-end learning system for human-object interaction (HOI) detection; vision transformers build a simple multi-stage structure for multi-scale representation with single-scale patch and are the first patch-based transformer architecture for image-level recognition and instance-level detection. In this paper, we build a transformer-based multi-scale human-object interaction detector (MHOI), a novel method to integrate Vision and HOI detection Transformer, instead of directly incorporating two types of transformers, since the vision transformer lacks hierarchical architecture to handle the large variations in the scale of visual entities due to the single-scale patch partitioning. Specifically, MHOI embeds features of the same size (i.e., sequence length) with patches of variable scales simultaneously by utilizing overlapping convolutional patch embedding, then introduces an efficient transformer decoder that designs the query based on anchor points and essential auxiliary techniques to boost the HOI detection performance. Numerically, extensive experiments on several benchmarks demonstrate that our proposed framework outperforms prior existing methods coherently and achieves the impressive performance of 29.67 mAP on HICO-DET and 58.7 mAP on V-COCO, respectively.

MFBGR: Multi-scale feature boundary graph reasoning network for polyp segmentation

At present, adding Transformer to CNN has promoted the rapid development of colorectal polyp image processing. However, from the perspective of multi-scale feature interaction and boundary coherence, there are mainly some limitations: (1) ignore the local and global correlation within the scale feature, which may cause the missed detection of tiny polyps, (2) lack of multi-scale features to explore the target region, which hinders the learning of multi-variant polyps, and (3) the semantic connection between the target area and the boundary is ignored, cause incoherent segmentation boundaries. In this regard, we design a multi-scale feature boundary graph inference network for polyp segmentation, namely MFBGR. First, the Transformer block captures local–global cues inside the multi-scale information learned by the CNN branches. Second, for the multi-scale global information generated by the Transformer block, we design a cross-scale feature fusion module (CSFM). CSFM performs scale-variation interaction and cascaded fusion to capture the correlation between features across scales and solve the scale-variation problem of segmented objects. Finally, the traditional boundary refinement or enhancement idea is generalized to the graph convolutional reasoning layer (BGRM). BGRM receives CNN’s low-level feature information and CSFM’s fusion features, or intermediate prediction results, and propagates cross-domain feature information between graph vertices, explores information between target regions and boundary regions, and achieves more accurate boundary segmentation. On the CVC-300, CVC-ClinicDB, CVC-ColonDB, Kvasir-SEG, ETIS datasets, MFBGR and mainstream polyp segmentation networks were compared and tested. MFBGR achieved good results, and Dice, IOU, BAcc, and Haudo were the best. The values reached 94.16%, 89.35% and 97.42%, 3.7442, and the segmentation accuracy of colorectal polyp images has been improved to a certain extent.

Toward Earth system modeling with resolved clouds and ocean submesoscales on heterogeneous many-core HPCs.

With the aid of the newly developed 'Sunway' heterogeneous-architecture supercomputer, which has world-leading HPC (high-performance computer) capability, a series of high-resolution coupled Earth system models (SW-HRESMs) with up to 5km of atmosphere and 3km of ocean have been developed. These models can meet the needs of multiscale interaction studies with different computational costs. Here we describe the progress of SW-HRESMs development, with an overview of the major advancements made by the international Earth science community in HR-ESMs. We also show the preliminary results of SW-HRESMs with regard to capturing major weather-climate extremes in the atmosphere and ocean, stressing the importance of permitted clouds and ocean submesoscale eddies in modeling tropical cyclones and eddy-mean flow interactions, and paving the way for further model development to resolve finer scales with even higher resolution and more realistic physics. Finally, in addition to increasing model resolution, the development procedure for a non-hydrostatic cloud and ocean submesoscale resolved ESM is discussed, laying out the major scientific directions of such a huge modeling advancement.

Sensitivity analysis of kinetic theory of granular flow (KTGF) and mixture models in terms of involved elemental parameters for two-phase gas-solid flow

Probing into the multiscale essence and nonlinear interactions of gas-solid flows whether in natural or industrial scale have continuously been evoking challenges in flow physics and modeling approaches. Although there are capabilities within the test bench experiments and empirical formulas to define or predict the flow characteristics in two-phase systems, the flow pattern would be still unknown, and here is where the numerical approaches thrive. Since, the corresponding non-linear equation system developed to predict the behavior of two-phase flows is intrinsically complex and makes the numerical solutions time-consuming, in this article, the sensitivity analysis of two well-known models based on the Euler-Euler approach, namely KTGF and Mixture models, is conducted in terms of continuous/dispersed shear stress and solid pressure on the accuracy, stability, and duration of solution. In the KTGF model, granular viscosity is particularly most influential term; while in the Mixture model, the numerical solution profoundly depends on the continuous phase viscosity. Moreover, it is perceived that the existence of solid pressure as a diffusive source term is consequential for the stability in the modeling process, and in high values of dispersed volume fraction, its impact on the flow behavior is distinguishable.

Water Vapor Budget Features and Its Precipitation Effects over the Key Area of Sichuan-Tibet Railway in Summer

In this study, we investigate the variation of characteristics of summer precipitation with different magnitudes and the water vapor budget in different key areas of the Sichuan-Tibet Railway by using the daily precipitation data from meteorological stations and the monthly mean ERA-Interim reanalysis data from 1979 to 2018. The results show that the summer heavy precipitation anomaly in the Brahmaputra valley and mountain (BVM) area is generated by the multi-scale interactions between the unique topography and different water vapor transports at low latitudes. When an intense anticyclonic circulation occurs over the western Pacific and the South China Sea, there is also an anomalous anticyclonic circulation extending from the northern Indian Peninsula to the Bay of Bengal. This circulation pattern is conductive to the increase of the water vapor inflow from the southern boundary and the net water vapor budget in the BVM area. The strong southwesterly wind and water vapor convergence over this area thus leading to heavy precipitation in the summer. The summer heavy precipitation amount, frequency and intensity in the western parts of the steep terrain (ST) area on the east slope of the plateau are positively correlated with the water vapor inflow from its western boundary. However, the correlations of the water vapor budget to the summer heavy precipitation amount and frequency are opposite in the eastern parts of the ST area. The unique terrain and circulation patterns lead to the localization and diversity of heavy precipitation in the ST area.

User-defined mid-air gestures for multiscale GIS interface interaction

ABSTRACT Multisize geographic information system (GIS) has widely used in social life, and the introduction of natural interactive methods such as gesture interaction further broadens the applications of GIS. Gestures, as a natural means of expression, bring a convenient experience to the use of GIS. The user-elicitation method can determine the user’s original operational intention and take advantage of the natural and convenient gesture interaction. However, current research on elicitation methods mainly focuses on defining the function factors of operation commands and rarely considers the influence of environmental factors such as spatial sizes. This paper takes GIS as the object, which is closely related to multisize space. This paper reports a research project on user-defined gestures for interacting with two-dimensional maps in a virtual reality environment, including three types of GIS operation commands and six sizes of maps. The results showed that the user-defined gestures for the same GIS operation commands varied across map sizes. The increase in map size increased the amount of gestural movement. Drawing on our research, we developed a set of gestures for multisize GIS interface interaction. We hope that this research can provide a guiding foundation for mid-air gesture design for all multisize interfaces.

Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease.

From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.