Geomaterials containing fissures such as some sedimentary rocks often exhibit a bimodal pore size distribution, and they are also inherently anisotropic due to the distinct bedding planes. ...Hydromechanical modeling of solid deformation and fluid flow of such geomaterials remains a significant challenge. In this paper, we have developed a unique anisotropic double porosity elastoplastic framework to describe such processes. Furthermore, for the solid constitutive model, because of the loss of stress tensor coaxiality between the trial state and the final state, we have derived a new implicit return mapping algorithm to obtain the updated effective stress, history parameters and consistent tangent operator for any given strain increment efficiently, followed by a uniaxial strain point simulation to provide benchmark results. Subsequently, 3D stress point simulations are carried out to calibrate the projection and plasticity parameters using triaxial experimental data as well as to illustrate the strain-softening phenomenon. Initial boundary value problem simulations have been conducted to analyze the impacts of fluid flow and solid constitutive model on the resulting geomaterials’ responses. The overarching goal of this paper is to better understand the coupled solid deformation-fluid flow in the transversely isotropic fissured rocks.
Regulating the fluorescent properties of organic small molecules in a controlled and dynamic manner has been a fundamental research goal. Although several strategies have been exploited, realizing ...multi-color molecular emission from a single fluorophore remains challenging. Herein, we demonstrate an emissive system by combining pyrene fluorophore and acylhydrazone units, which can generate multi-color switchable fluorescent emissions at different assembled states. Two kinds of supramolecular tools, amphiphilic self-assembly and γ-cyclodextrin mediated host-guest recognition, are used to manipulate the intermolecular aromatic stacking distances, resulting in the tunable fluorescent emission ranging from blue to yellow, including a pure white-light emission. Moreover, an external chemical signal, amylase, is introduced to control the assembly states of the system on a time scale, generating a distinct dynamic emission system. The dynamic properties of this multi-color fluorescent system can be also enabled in a hydrogel network, exhibiting a promising potential for intelligent fluorescent materials.
Forests in the Tibetan Plateau are thought to be vulnerable to climate extremes, yet they also tend to exhibit resilience contributing to the maintenance of ecosystem services in and beyond the ...plateau. So far the spatiotemporal pattern in tree resilience in the Tibetan Plateau remains largely unquantified and the influence of specific factors on the resilience is poorly understood. Here, we study ring‐width data from 849 trees at 28 sites in the Tibetan Plateau with the aim to quantify tree resilience and determine their diving forces. Three extreme drought events in years 1969, 1979, and 1995 are detected from metrological records. Regional tree resistance to the three extreme droughts shows a decreasing trend with the proportion of trees having high resistance ranging from 71.9%, 55.2%, to 39.7%. Regional tree recovery is increasing with the proportion of trees having high recovery ranging from 28.3%, 52.2%, to 64.2%. The area with high resistance is contracting and that of high recovery is expanding. The spatiotemporal resistance and recovery are associated with moisture availability and diurnal temperature range, respectively. In addition, they are both associated with forest internal factor represented by growth consistence among trees. We conclude that juniper trees in the Tibetan Plateau have increased resilience to extreme droughts in the study period. We highlight pervasive resilience in juniper trees. The results have implications for predicting tree resilience and identifying areas vulnerable to future climate extremes.
Tree resilience is important for maintaining the healthy growth of forests, yet remains largely unquantified. Examination of tree resilience to drought extremes from 28 sites of juniper forests in the Tibetan Plateau reveals a temporal decreasing trend in tree resistance and an increasing trend in recovery, and a spatial contraction in the area of high resistance and expansion in high recovery. The variation of tree resilience is associated with moisture availability, diurnal temperature range, and growth consistence among trees. The results have implications for predicting tree resilience and identifying areas vulnerable to future climate extremes.
Fabrication of soft piezoelectric nanomaterials is essential for the development of wearable and implantable biomedical devices. However, a big challenge in this soft functional material development ...is to achieve a high piezoelectric property with long‐term stability in a biological environment. Here, a one‐step strategy for fabricating core/shell poly(vinylidene difluoride) (PVDF)/dopamine (DA) nanofibers (NFs) with a very high β‐phase content and self‐aligned polarization is reported. The self‐assembled core/shell structure is believed essential for the formation and alignment of β‐phase PVDF, where strong intermolecular interaction between the NH2 groups on DA and the CF2 groups on PVDF is responsible for aligning the PVDF chains and promoting β‐phase nucleation. The as‐received PVDF/DA NFs exhibit significantly enhanced piezoelectric performance and excellent stability and biocompatibility. An all‐fiber‐based soft sensor is fabricated and tested on human skin and in vivo in mice. The devices show a high sensitivity and accuracy for detecting weak physiological mechanical stimulation from diaphragm motions and blood pulsation. This sensing capability offers great diagnostic potential for the early assessment and prevention of cardiovascular diseases and respiratory disorders.
High‐performance poly(vinylidene difluoride)/dopamine core/shell piezoelectric nanofibers with excellent stability are successfully fabricated by one‐step electrospinning in large scale and quantity, offering an extraordinary building block for developing self‐powered sensor devices to detect weak absolute pressure change from soft tissues in vivo. This sensing capability offers great diagnostic potential for the early assessment and prevention of cardiovascular diseases and respiratory disorders.
This paper presents a new technique for artificial neural network (ANN) inverse modeling and applications to microwave filters. In inverse modeling of a microwave component, the inputs to the model ...are electrical parameters such as <inline-formula> <tex-math notation="LaTeX">S </tex-math></inline-formula>-parameters, and the outputs of the model are geometrical or physical parameters. Since the analytical formula of the inverse input-output relationship does not exist, the ANN becomes a logical choice, because it can be trained to learn from the data in inverse modeling. The main challenge of inverse modeling is the nonuniqueness problem. This problem in the ANN inverse modeling is that different training samples with the same or very similar input values have quite different (contradictory) output values (multivalued solutions). In this paper, we propose a multivalued neural network inverse modeling technique to associate a single set of electrical parameters with multiple sets of geometrical or physical parameters. One set of geometrical or physical parameters is called one value of our proposed inverse model. Our proposed multivalued neural network is structured to accommodate multiple values for the model output. We also propose a new training error function to focus on matching each training sample using only one value of our proposed inverse model, while other values are free and can be trained to match other contradictory samples. In this way, our proposed multivalued neural network can learn all the training data by automatically redirecting contradictory information into different values of the proposed inverse model. Therefore, our proposed technique can solve the nonuniqueness problem in a simpler and more automated way compared with the existing ANN inverse modeling techniques. This technique is illustrated by inverse modeling and parameter extraction of four microwave filter examples.
Image classification plays an important role in computer vision. The existing convolutional neural network methods have some problems during image classification process, such as low accuracy of ...tumor classification and poor ability of feature expression and feature extraction. Therefore, we propose a novel ResNet101 model based on dense dilated convolution for medical liver tumors classification. The multi-scale feature extraction module is used to extract multi-scale features of images, and the receptive field of the network is increased. The depth feature extraction module is used to reduce background noise information and focus on effective features of the focal region. To obtain broader and deeper semantic information, a dense dilated convolution module is deployed in the network. This module combines the advantages of Inception, residual structure, and multi-scale dilated convolution to obtain a deeper level of feature information without causing gradient explosion and gradient disappearance. To solve the common feature loss problems in the classification network, the up- down-sampling module in the network is improved, and multiple convolution kernels with different scales are cascaded to widen the network, which can effectively avoid feature loss. Finally, experiments are carried out on the proposed method. Compared with the existing mainstream classification networks, the proposed method can improve the classification performance, and finally achieve accurate classification of liver tumors. The effectiveness of the proposed method is further verified by ablation experiments.
Highlights
The multi-scale feature extraction module is introduced to extract multi-scale features of images, it can extract deep context information of the lesion region and surrounding tissues to enhance the feature extraction ability of the network.
The depth feature extraction module is used to focus on the local features of the lesion region from both channel and space, weaken the influence of irrelevant information, and strengthen the recognition ability of the lesion region.
The feature extraction module is enhanced by the parallel structure of dense dilated convolution, and the deeper feature information is obtained without losing the image feature information to improve the classification accuracy.
The long‐segment peripheral nerve injury (PNI) represents a global medical challenge, leading to incomplete nerve tissue recovery and unsatisfactory functional reconstruction. However, the current ...electrical stimulation (ES) apparatuses fail perfect nerve repair due to their inability of the variable synchronous self‐regulated function with physiological states. It is urgent to develop an implantable ES platform with physiologically adaptive function to provide instantaneous and nerve‐preferred ES. Here, a physiologically self‐regulated electrical signal is generated by integrating a novel tribo/piezoelectric hybrid nanogenerator with a nanoporous nerve guide conduit to construct a fully implantable neural electrical stimulation (FI‐NES) system. The optimal neural ES parameters completely originate from the body itself and are highly self‐responsive to different physiological states. The morphological evaluation, representative protein expression level, and functional reconstruction of the regenerated nerves are conducted to assess the PNI recovery process. Evidence shows that the recovery effect of 15 mm length nerve defects under the guidance of the FI‐NES system is significantly close to the autograft. The designed FI‐NES system provides an effective method for long‐term accelerating the recovery of PNI in vivo and is also appropriate for other tissue injury or neurodegenerative diseases.
A physiologically self‐regulated, fully implantable, battery‐free neural electrical stimulation system is successfully constructed to produce physiologically electrical signals for the acceleration of regeneration and functional recovery of peripheral nerve injury.
Thermomagnetic curves of magnetic susceptibility (κ) are key to characterizing magnetic properties. We report hump‐shaped κ‐T curves of magnetite‐bearing basalt during heating‐cooling cycles to ...∼340°C, with a large thermal hysteresis and similar starting and ending values, even in multiple repeated cycles, ruling out changes in magnetic mineralogy. Based on FORC diagrams and published results of engineered materials, we propose that thermal hysteresis arises from configurations of magnetic moments in clusters of single‐domain particles due to dipolar coupling, with different collective behavior during heating and cooling. This effect modifies the hump‐shaped thermal relaxation behavior of the individual nanoparticles. FORC and κ‐T results indicate an increase in effective particle sizes after 700°C‐heating. Our results are a warning against premature interpretation of a decreasing trend in κ‐T curves by maghemite inversion. Instead, fine particle behavior should be considered when a hump‐shaped κ‐T behavior is detected.
Plain Language Summary
Thermomagnetic curves of magnetic susceptibility (κ) are key to characterizing magnetic properties. A marked drop in κ‐T curves at ∼300–400°C is often considered to indicate the inversion of maghemite to hematite. Such a drop is often preceded by an increase in κ, creating a hump shape that is rarely noted in discussions. We report hump‐shaped κ‐T curves in magnetite‐bearing basalt. When heating up to ∼340°C and cooled subsequently, a large thermal hysteresis was observed. This hump shape and the thermal hysteresis behavior occur in a very similar way in repeated κ‐T cycles, ruling out changes in magnetic mineralogy. We hypothesize that the thermal hysteresis arises from configurations of coupled magnetic moments in clusters of fine particles, which is partly irreversible upon cooling. This effect modifies the hump‐shaped thermal relaxation behavior of the individual particle moments. When heated to 700°C, grain boundaries may weld and internal stress effects are reduced, increasing the effective particle sizes and shifting the hump‐peak to a higher temperature. Our results indicate that fine particle behavior should be considered for all types of natural materials when a hump‐shaped κ‐T curve is observed rather than interpreting the drop in κ as maghemite inversion.
Key Points
We observed reversible thermal hysteresis behavior in hump‐shaped partial magnetic susceptibility cycles of magnetite‐bearing basalts
The thermal hysteresis may be caused by blocked states of coupled nanoparticle moments modulating thermal activation
Descending susceptibility in hump‐shaped curves is often due to single‐domain thermal relaxation rather than maghemite inversion
The formation of lateral branches has an important and fundamental contribution to the remarkable developmental plasticity of plants, which allows plants to alter their architecture to adapt to the ...challenging environment conditions. The Gibberellin (GA) phytohormones have been known to regulate the outgrowth of axillary meristems (AMs), but the specific molecular mechanisms remain unclear. Here we show that DELLA proteins regulate axillary bud formation by interacting and regulating the DNA‐binding ability of SQUAMOSA‐PROMOTER BINDING PROTEIN LIKE 9 (SPL9), a microRNA156‐targeted squamosa promoter binding protein‐like transcription factor. SPL9 participates in the initial regulation of axillary buds by repressing the expression of LATERAL SUPPRESSOR (LAS), a key regulator in the initiation of AMs, and LAS contributes to the specific expression pattern of the GA deactivation enzyme GA2ox4, which is specifically expressed in the axils of leaves to form a low‐GA cell niche in this anatomical region. Nevertheless, increasing GA levels in leaf axils by ectopically expressing the GA‐biosynthesis enzyme GA20ox2 significantly impaired axillary meristem initiation. Our study demonstrates that DELLA‐SPL9‐LAS‐GA2ox4 defines a core feedback regulatory module that spatially pattern GA content in the leaf axil and precisely control the axillary bud formation in different spatial and temporal.
As an important agronomic trait, lateral branches closely related to crop yield. In this study, we demonstrated that phytohormone gibberellin represses the axillary bud formation through enhancing the activity of transcription factor SPL9 to repress the expression of LAS that is a key regulator in the initiation of axillary buds.
Since the LHCb collaboration announced the observation of the doubly charmed baryon
Ξ
cc
+
+
, a series of studies of doubly heavy baryons have been presented. In this work, I analyse the ...non-leptonic weak decays of doubly heavy baryons
Ξ
bc
and
Ω
bc
under the flavor
SU
(3) symmetry. I mainly focus on the
W
-exchange diagrams, which will contribute to the decay channels with final states are light meson and light baryon. These channels would be helpful for searching for
Ξ
bc
and
Ω
bc
at LHC. And these channels and relations of corresponding decay widths could be examined by the future experimental facilities such as LHC, Belle II and CEPC.
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