Numerical Simulation of Nano Scanning in Intermittent-Contact Mode AFM under Q control

We investigate nano scanning in tapping mode atomic force microscopy (AFM) under quality (Q) control via numerical simulations performed in SIMULINK. We focus on the simulation of whole scan process rather than the simulation of cantilever dynamics and the force interactions between the probe tip and the surface alone, as in most of the earlier numerical studies. This enables us to quantify the scan performance under Q control for different scan settings. Using the numerical simulations, we first investigate the effect of elastic modulus of sample (relative to the substrate surface) and probe stiffness on the scan results. Our numerical simulations show that scanning in attractive regime using soft cantilevers with high Qeff results in a better image quality. We, then demonstrate the trade-off in setting the effective Q factor (Qeff) of the probe in Q control: low values of Qeff cause an increase in tapping forces while higher ones limit the maximum achievable scan speed due to the slow response of the cantilever to the rapid changes in surface profile. Finally, we show that it is possible to achieve higher scan speeds without causing an increase in the tapping forces using adaptive Q control (AQC), in which the Q factor of the probe is changed instantaneously depending on the magnitude of the error signal in oscillation amplitude. The scan performance of AQC is quantitatively compared to that of standard Q control using iso-error curves obtained from numerical simulations first and then the results are validated through scan experiments performed using a physical set-up

Locomotion strategy selection for a legged wheeled hybrid quadruped using depth images

Three fundamental locomotion configurations recognized commonly are legged, wheeled, and articulated mechanisms using which a mobile robot can navigate terrains. Hybrid configurations enable execution of different locomotion types separately and in combinations. Such advantage usually implies complexity and necessity in a robust supervisory controller capable of terrain recognition and locomotion strategy selection. We developed the Nazarbayev University (NU) Hybrid Quadruped (Fig. 1) - mobile robot with four legs and wheels. Project's major novelty is the implementation of the supervisory controller which selects a locomotion mode associated with particular terrain types based on its terrain recognizer input data

Asynchronous Interaction Aggregation for Action Detection

Understanding interaction is an essential part of video action detection. We propose the Asynchronous Interaction Aggregation network (AIA) that leverages different interactions to boost action detection. There are two key designs in it: one is the Interaction Aggregation structure (IA) adopting a uniform paradigm to model and integrate multiple types of interaction; the other is the Asynchronous Memory Update algorithm (AMU) that enables us to achieve better performance by modeling very long-term interaction dynamically without huge computation cost. We provide empirical evidence to show that our network can gain notable accuracy from the integrative interactions and is easy to train end-to-end. Our method reports the new state-of-the-art performance on AVA dataset, with 3.7 mAP gain (12.6% relative improvement) on validation split comparing to our strong baseline. The results on dataset UCF101-24 and EPIC-Kitchens further illustrate the effectiveness of our approach. Source code will be made public at: https://github.com/MVIG-SJTU/AlphAction

The effect of racemic gossypol and AT-101 on angiogenic profile of OVCAR-3 cells: a preliminary molecular framework for gossypol enantiomers

To compare the effect of racemic gossypol with its (–)/(–) enantiomer (AT-101) on expression profiles of angiogenic molecules by mRNA levels in human ovarian cancer cell line OVCAR-3. Methods: Cell viability assay (2,3-bis (2-methoxy-4-nitro-5- sulfophenyl)-5-[(phenylamino) carbonyl]-2H-tetrazolium hydroxide) was used to detect cytotoxicity of gossypol enantiomers. DNA fragmentation by an enzyme-linked immunosorbent (ELISA) assay was used to evaluate the rate of apoptosis. The mRNA expression levels of angiogenic molecules were investigated by Human Angiogenesis RT2 ProfilerTM PCR Array (SuperArray, Frederick, MD). Results: Both racemic form and AT-101 resulted in a significant cytotoxicity and induced apoptosis. This effect was observed in a dose- and time dependent manner. However, AT-101 was much more potent. In addition, the treatment of 10 μM of racemic gossypol alone and 3 μM of AT-101 alone resulted in significant down-regulation (≥ 3 fold) in mRNA levels of some pivotal angiogenic molecules in OVCAR-3, but altered gene profiles were different by the treatment of each enantiomer. Conclusion: The efficacy of two gossypol enantiomers in OVCAR-3 cells showed distinction. AT-101 was much more potent than racemic gossypol, not only by means of cell death and apoptosis, but also by modulation of angiogenic molecules released from OVCAR-3 cells. Further studies with endothelial cells should be done to verify the anti-angiogenic effect of gossypol enantiomers in cancer treatment

Competing Ultrafast Energy Relaxation Pathways in Photoexcited Graphene

For most optoelectronic applications of graphene a thorough understanding of the processes that govern energy relaxation of photoexcited carriers is essential. The ultrafast energy relaxation in graphene occurs through two competing pathways: carrier-carrier scattering -- creating an elevated carrier temperature -- and optical phonon emission. At present, it is not clear what determines the dominating relaxation pathway. Here we reach a unifying picture of the ultrafast energy relaxation by investigating the terahertz photoconductivity, while varying the Fermi energy, photon energy, and fluence over a wide range. We find that sufficiently low fluence ($\lesssim$ 4 $\mu$J/cm$^2$) in conjunction with sufficiently high Fermi energy ($\gtrsim$ 0.1 eV) gives rise to energy relaxation that is dominated by carrier-carrier scattering, which leads to efficient carrier heating. Upon increasing the fluence or decreasing the Fermi energy, the carrier heating efficiency decreases, presumably due to energy relaxation that becomes increasingly dominated by phonon emission. Carrier heating through carrier-carrier scattering accounts for the negative photoconductivity for doped graphene observed at terahertz frequencies. We present a simple model that reproduces the data for a wide range of Fermi levels and excitation energies, and allows us to qualitatively assess how the branching ratio between the two distinct relaxation pathways depends on excitation fluence and Fermi energy.Comment: Nano Letters 201

Nanoparticle amount, and not size, determines chain alignment and nonlinear hardening in polymer nanocomposites

Polymer nanocomposites-materials in which a polymer matrix is blended with nanoparticles (or fillers)-strengthen under sufficiently large strains. Such strain hardening is critical to their function, especially for materials that bear large cyclic loads such as car tires or bearing sealants. Although the reinforcement (i.e., the increase in the linear elasticity) by the addition of filler particles is phenomenologically understood, considerably less is known about strain hardening (the nonlinear elasticity). Here, we elucidate the molecular origin of strain hardening using uniaxial tensile loading, microspectroscopy of polymer chain alignment, and theory. The strain-hardening behavior and chain alignment are found to depend on the volume fraction, but not on the size of nanofillers. This contrasts with reinforcement, which depends on both volume fraction and size of nanofillers, potentially allowing linear and nonlinear elasticity of nanocomposites to be tuned independently.This work is part of the research programme “Understanding the viscoelasticity of elastomer based nanocomposites” of the Stichting voor Fundamenteel Onderzoek der Materie, which is financially supported by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression

Importance: Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological mechanisms and support precision and individualized medicine. Objective: To cross-sectionally and longitudinally delineate disease-related heterogeneity in LLD associated with neuroanatomy, cognitive functioning, clinical symptoms, and genetic profiles. Design, Setting, and Participants: The Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) study is an international multicenter consortium investigating brain aging in pooled and harmonized data from 13 studies with more than 35 000 participants, including a subset of individuals with major depressive disorder. Multimodal data from a multicenter sample (N = 996), including neuroimaging, neurocognitive assessments, and genetics, were analyzed in this study. A semisupervised clustering method (heterogeneity through discriminative analysis) was applied to regional gray matter (GM) brain volumes to derive dimensional representations. Data were collected from July 2017 to July 2020 and analyzed from July 2020 to December 2021. Main Outcomes and Measures: Two dimensions were identified to delineate LLD-associated heterogeneity in voxelwise GM maps, white matter (WM) fractional anisotropy, neurocognitive functioning, clinical phenotype, and genetics. Results: A total of 501 participants with LLD (mean [SD] age, 67.39 [5.56] years; 332 women) and 495 healthy control individuals (mean [SD] age, 66.53 [5.16] years; 333 women) were included. Patients in dimension 1 demonstrated relatively preserved brain anatomy without WM disruptions relative to healthy control individuals. In contrast, patients in dimension 2 showed widespread brain atrophy and WM integrity disruptions, along with cognitive impairment and higher depression severity. Moreover, 1 de novo independent genetic variant (rs13120336; chromosome: 4, 186387714; minor allele, G) was significantly associated with dimension 1 (odds ratio, 2.35; SE, 0.15; P = 3.14 ×10⁸) but not with dimension 2. The 2 dimensions demonstrated significant single-nucleotide variant–based heritability of 18% to 27% within the general population (N = 12 518 in UK Biobank). In a subset of individuals having longitudinal measurements, those in dimension 2 experienced a more rapid longitudinal change in GM and brain age (Cohen ƒ² = 0.03; P = .02) and were more likely to progress to Alzheimer disease (Cohen ƒ² = 0.03; P = .03) compared with those in dimension 1 (N = 1431 participants and 7224 scans from the Alzheimer’s Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], and Biomarkers for Older Controls at Risk for Dementia [BIOCARD] data sets). Conclusions and Relevance: This study characterized heterogeneity in LLD into 2 dimensions with distinct neuroanatomical, cognitive, clinical, and genetic profiles. This dimensional approach provides a potential mechanism for investigating the heterogeneity of LLD and the relevance of the latent dimensions to possible disease mechanisms, clinical outcomes, and responses to interventions