Strain engineering is widely used to manipulate the electronic and magnetic properties of complex materials. For example, the piezomagnetic effect provides an attractive route to control magnetism ...with strain. In this effect, the staggered spin structure of an antiferromagnet is decompensated by breaking the crystal field symmetry, which induces a ferrimagnetic polarization. Piezomagnetism is especially appealing because, unlike magnetostriction, it couples strain and magnetization at linear order, and allows for bi-directional control suitable for memory and spintronics applications. However, its use in functional devices has so far been hindered by the slow speed and large uniaxial strains required. Here we show that the essential features of piezomagnetism can be reproduced with optical phonons alone, which can be driven by light to large amplitudes without changing the volume and hence beyond the elastic limits of the material. We exploit nonlinear, three-phonon mixing to induce the desired crystal field distortions in the antiferromagnet CoF2. Through this effect, we generate a ferrimagnetic moment of 0.2 μB per unit cell, nearly three orders of magnitude larger than achieved with mechanical strain.This paper shows how lattice distortions induced by a laser pulse can create a ferrimagnetic moment in an antiferromagnet. This mechanism gives a magnetic response that is orders of magnitude larger than using mechanical strain.
Light fields at terahertz and mid-infrared frequencies allow for the direct excitation of collective modes in condensed matter, which can be driven to large amplitudes. For example, excitation of the ...crystal lattice has been shown to stimulate insulator-metal transitions, melt magnetic order or enhance superconductivity. Here, we generalize these ideas and explore the simultaneous excitation of more than one lattice mode, which are driven with controlled relative phases.
Parametric amplification of optical phonons Cartella, A.; Nova, T. F.; Fechner, M. ...
Proceedings of the National Academy of Sciences - PNAS,
11/2018, Letnik:
115, Številka:
48
Journal Article
Recenzirano
Odprti dostop
We use coherent midinfrared optical pulses to resonantly excite large-amplitude oscillations of the Si–C stretching mode in silicon carbide. When probing the sample with a second pulse, we observe ...parametric optical gain at all wavelengths throughout the reststrahlen band. This effect reflects the amplification of light by phonon-mediated four-wave mixing and, by extension, of optical-phonon fluctuations. Density functional theory calculations clarify aspects of the microscopic mechanism for this phenomenon. The high-frequency dielectric permittivity and the phonon oscillator strength depend quadratically on the lattice coordinate; they oscillate at twice the frequency of the optical field and provide a parametric drive for the lattice mode. Parametric gain in phononic four-wave mixing is a generic mechanism that can be extended to all polar modes of solids, as a means to control the kinetics of phase transitions, to amplify many-body interactions or to control phonon-polariton waves.
Nudges are increasingly used to encourage sustainable and often meat-free diets. Interventions to reduce people’s meat consumption are motivated by concerns about health, animal welfare, and the ...environment. However, dietary choices are of personal and cultural significance, and not everybody wants to be nudged towards a plant-based diet. Nudging has been criticised for being paternalistic, manipulative, and a violation of personal autonomy, amongst other points. It is important to ask whether it is ethical to nudge people towards plant-based diets or whether it is unethical not to do so. Using the FORGOOD ethics framework, this paper organises diverse ethical arguments both in favour and against nudging people towards plant-based diets into seven dimensions: fairness, openness, respect, goals, opinions, options, and delegation. We propose that policymakers, researchers, retailers, restaurant managers, and others who design food menus, set food defaults, decide about which labels to use, and design food choice architectures in other ways should use the presented arguments to reflect on whether nudging people towards plant-based diets is ethical.
Abstract
Motivation
Cancer heterogeneity is observed at multiple biological levels. To improve our understanding of these differences and their relevance in medicine, approaches to link organ- and ...tissue-level information from diagnostic images and cellular-level information from genomics are needed. However, these ‘radiogenomic’ studies often use linear or shallow models, depend on feature selection, or consider one gene at a time to map images to genes. Moreover, no study has systematically attempted to understand the molecular basis of imaging traits based on the interpretation of what the neural network has learned. These studies are thus limited in their ability to understand the transcriptomic drivers of imaging traits, which could provide additional context for determining clinical outcomes.
Results
We present a neural network-based approach that takes high-dimensional gene expression data as input and performs non-linear mapping to an imaging trait. To interpret the models, we propose gene masking and gene saliency to extract learned relationships from radiogenomic neural networks. In glioblastoma patients, our models outperformed comparable classifiers (>0.10 AUC) and our interpretation methods were validated using a similar model to identify known relationships between genes and molecular subtypes. We found that tumor imaging traits had specific transcription patterns, e.g. edema and genes related to cellular invasion, and 10 radiogenomic traits were significantly predictive of survival. We demonstrate that neural networks can model transcriptomic heterogeneity to reflect differences in imaging and can be used to derive radiogenomic traits with clinical value.
Availability and implementation
https://github.com/novasmedley/deepRadiogenomics.
Contact
whsu@mednet.ucla.edu
Supplementary information
Supplementary data are available at Bioinformatics online.
SUMMARY
We present new absolute archaeointensity data from six archaeological sites situated in the Okayama Prefecture, Japan. The materials studied are well-dated fragments from pottery, ceramic ...coffins and haniwa artefacts. Their ages range from 160 AD to 675 AD, covering the Late Yayoi and Kofun periods. Rock magnetic experiments suggest the presence of magnetite and/or Ti-magnetite as the main carrier of the remanence, with a possible minor contribution of higher coercivity minerals. After thermal demagnetization experiments, the most magnetically stable samples were selected for archaeointensity analysis performed following the double-heating method proposed by Thellier and modified by Coe. Partial thermoremanent magnetization (pTRM) checks and pTRM tail-checks were performed for monitoring possible chemical alterations during heating. All measurements were corrected for both anisotropy and cooling-rate effects. Successful archaeointensity determinations, following rigorous selection criteria, were obtained for samples from all the investigated archaeological sites. Compared with literature data from Japan, the new high-quality data show significantly lower intensity values. They also reveal possible fast secular variation changes during the Late Yayoi period and very weak geomagnetic intensity field around 630 AD. Such values offer evidence of a possible recurrence of weak intensity field in East Asia, suggesting an ancient recurrence of the West Pacific Anomaly. The new data might change the archaeomagnetic field models interpretations in the area, even though more data are still necessary to better understand the secular variation in Japan and the temporal evolution of the geomagnetic field's behaviour in East Asia.
The growing amount of longitudinal data for a large population of patients has necessitated the application of algorithms that can discover patterns to inform patient management. This study ...demonstrates how temporal patterns generated from a combination of clinical and imaging measurements improve residual survival prediction in glioblastoma patients. Temporal patterns were identified with sequential pattern mining using data from 304 patients. Along with patient covariates, the patterns were incorporated as features in logistic regression models to predict 2-, 6-, or 9-month residual survival at each visit. The modeling approach that included temporal patterns achieved test performances of 0.820, 0.785, and 0.783 area under the receiver operating characteristic curve for predicting 2-, 6-, and 9-month residual survival, respectively. This approach significantly outperformed models that used tumor volume alone (p < 0.001) or tumor volume combined with patient covariates (p < 0.001) in training. Temporal patterns involving an increase in tumor volume above 122 mm
/day, a decrease in KPS across multiple visits, moderate neurologic symptoms, and worsening overall neurologic function suggested lower residual survival. These patterns are readily interpretable and found to be consistent with known prognostic indicators, suggesting they can provide early indicators to clinicians of changes in patient state and inform management decisions.
The crystal structure of a solid largely dictates its electronic, optical and mechanical properties. Indeed, much of the exploration of quantum materials in recent years including the discovery of ...new phases and phenomena in correlated, topological and two-dimensional materials—has been based on the ability to rationally control crystal structures through materials synthesis, strain engineering or heterostructuring of van der Waals bonded materials. These static approaches, while enormously powerful, are limited by thermodynamic and elastic constraints. An emerging avenue of study has focused on extending such structural control to the dynamical regime by using resonant laser pulses to drive vibrational modes in a crystal. This paradigm of ‘nonlinear phononics’ provides a basis for rationally designing the structure and symmetry of crystals with light, allowing for the manipulation of functional properties at high speed and, in many instances, beyond what may be possible in equilibrium. Here we provide an overview of the developments in this field, discussing the theory, applications and future prospects of optical crystal structure engineering.The interaction between light and the crystal lattice of a quantum material can modify its properties. Utilizing nonlinear interactions allows this to be done in a controlled way to design specific non-equilibrium functionalities.
Using deep neural networks for radiogenomic analysis Smedley, Nova F.; Hsu, William
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018),
04/2018, Letnik:
2018
Conference Proceeding, Journal Article
Odprti dostop
Radiogenomic studies have suggested that biological heterogeneity of tumors is reflected radiographically through visible features on magnetic resonance (MR) images. We apply deep learning techniques ...to map between tumor gene expression profiles and tumor morphology in pre-operative MR studies of glioblastoma patients. A deep autoencoder was trained on 528 patients, each with 12,042 gene expressions. Then, the autoencoder's weights were used to initialize a supervised deep neural network. The supervised model was trained using a subset of 109 patients with both gene and MR data. For each patient, 20 morphological image features were extracted from contrast-enhancing and peritumoral edema regions. We found that neural network pre-trained with an autoencoder and dropout had lower errors than linear regression in predicting tumor morphology features by an average of 16.98% mean absolute percent error and 0.0114 mean absolute error, where several features were significantly different (adjusted p-value < 0.05). These results indicate neural networks, which can incorporate nonlinear, hierarchical relationships between gene expressions, may have the representational power to find more predictive radiogenomic associations than pairwise or linear methods.
Staphylococcus aureus is a facultative intracellular pathogen of human macrophages, which facilitates chronic infection. The genotypes, pathways, and mutations influencing that phenotype remain ...incompletely explored. Here, we used two distinct strategies to ascertain S. aureus gene mutations affecting pathogenesis in macrophages. First, we analyzed isolates collected serially from chronic cystic fibrosis (CF) respiratory infections. We found that S. aureus strains evolved greater macrophage invasion capacity during chronic human infection. Bacterial genome-wide association studies (GWAS) identified 127 candidate genes for which mutation was significantly associated with macrophage pathogenesis in vivo. In parallel, we passaged laboratory S. aureus strains in vitro to select for increased infection of human THP-1 derived macrophages, which identified 15 candidate genes by whole-genome sequencing. Functional validation of candidate genes using isogenic transposon mutant knockouts and CRISPR interference (CRISPRi) knockdowns confirmed virulence contributions from 37 of 39 tested genes (95%) implicated by in vivo studies and 7 of 10 genes (70%) ascertained from in vitro selection, with one gene in common to the two strategies. Validated genes included 17 known virulence factors (39%) and 27 newly identified by our study (61%), some encoding functions not previously associated with macrophage pathogenesis. Most genes (80%) positively impacted macrophage invasion when disrupted, consistent with the phenotype readily arising from loss-of-function mutations in vivo. This work reveals genes and mechanisms that contribute to S. aureus infection of macrophages, highlights differences in mutations underlying convergent phenotypes arising from in vivo and in vitro systems, and supports the relevance of S. aureus macrophage pathogenesis during chronic respiratory infection in CF. Additional studies will be needed to illuminate the exact mechanisms by which implicated mutations affect their phenotypes.
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