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Content analysis of academic movies readily available health through COVID-19 pandemic.
Surprisingly, magnetoquantum oscillations (MQOs) characteristic of a metal with a Fermi surface have been observed in measurements of the topological Kondo insulator SmB6. As these MQO have only been observed in measurements of magnetic torque (dHvA) and not in measurements of magnetoresistance (SdH), a debate has arisen as to whether the MQO are an extrinsic effect arising from rare-earth impurities, defects, and/or aluminum inclusions or an intrinsic effect revealing the existence of charge-neutral excitations. We report here the first observation of MQO in the low-temperature specific heat of SmB6. The observed frequencies and their angular dependence for these flux-grown samples are consistent with previous results based on magnetic torque for SmB6but the inferred effective masses are significantly larger than previously reported. Such oscillations can only be observed if the MQO are of bulk thermodynamic origin; the measured magnetic-field dependent oscillation amplitude and effective mass allow us to rule out suggestions of an extrinsic, aluminum inclusion-based origin for the MQO.Objective. This study aimed to produce a three-dimensional liver elasticity map using the finite element method (FEM) and respiration-induced motion captured by T1-weighted magnetic resonance images (FEM-E-map) and to evaluate whether FEM-E-maps can be an imaging biomarker comparable to magnetic resonance elastography (MRE) for assessing the distribution and severity of liver fibrosis.Approach. We enrolled 14 patients who underwent MRI and MRE. T1-weighted MR images were acquired during shallow inspiration and expiration breath-holding, and the displacement vector field (DVF) between two images was calculated using deformable image registration. FEM-E-maps were constructed using FEM and DVF. First, three Poisson's ratio settings (0.45, 0.49, and 0.499995) were validated and optimized to minimize the difference in liver elasticity between the FEM-E-map and MRE. Then, the whole and regional liver elasticity values estimated using FEM-E-maps were compared with those obtained from MRE using Pearson's correlation ication.Two-dimensional (2D) materials provide tremendous opportunities for next-generation energy storage technologies. We theoretically propose 2D group-IV oxides (α-, β-, andγ-CXO, X = Si/Ge). Among them,α-CXO monolayers, composed of the C-O-X skeleton of silyl (germyl) methyl ether molecules, are the most stable phase.α-CXO possess robust dynamical, mechanical, and thermal stabilities. Remarkably,α-CGeO has an unusual negative Poisson's ratio (NPR). However,α-CSiO displays a bidirectional half-auxeticity, different from all the already known NPR behaviors. The intrinsic moderate direct-band-gap, high carrier mobility, and superior optical absorption ofα-CXO make them attractive for optoelectronics applications. A series ofα-CXO-based excitonic solar cells can achieve high power conversion efficiencies. Besides,α-CXO monolayers are promising anode materials for sodium- and potassium-ion batteries, exhibiting not only the high specific capacity (532-1433 mA h g-1) but also low diffusion barrier and open-circuit voltage. In particular, the specific capacity of K onα-CSiO exhibits one of the highest values ever recorded in 2D materials. The multifunctionality rendersα-CXO promising candidates for nanomechanics, nanoelectronics, and nano-optics.Objective.Transitin vivodosimetry methods monitor that the dose distribution is delivered as planned. However, they have a limited ability to identify and to quantify the cause of a given disagreement, especially those caused by position errors. This paper describes a proof of concept of a simplein vivotechnique to infer a position error from a transit portal image (TPI).Approach.For a given treatment field, the impact of a position error is modeled as a perturbation of the corresponding reference (unperturbed) TPI. The perturbation model determines the patient translation, described by a shift vector, by comparing a givenin vivoTPI to the corresponding reference TPI. Patient rotations can also be determined by applying this formalism to independent regions of interest over the patient. see more Eight treatment plans have been delivered to an anthropomorphic phantom under a large set of couch shifts ( less then 15 mm) and rotations ( less then 10°) to experimentally validate this technique, which we have named Transit-Guided Radiation Therapy (TGRT).Main results.The root mean squared error (RMSE) between the determined and the true shift magnitudes was 1.0/2.4/4.9 mm for true shifts ranging between 0-5/5-10/10-15 mm, respectively. The angular accuracy of the determined shift directions was 12° ± 14°. The RMSE between the determined and the true rotations was 0.5°. The TGRT technique decoupled translations and rotations satisfactorily. In 96% of the cases, the TGRT technique decreased the existing position error. The detection threshold of the TGRT technique was around 1 mm and it was nearly independent of the tumor site, delivery technique, beam energy or patient thickness.Significance.TGRT is a promising technique that not only provides reliable determinations of the position errors without increasing the required equipment, acquisition time or patient dose, but it also adds on-line correction capabilities to existing methods currently using TPIs.Optical fluorescence microscopy plays a pivotal role in the exploration of biological structure and dynamics, especially on live specimens. Progress in the field relies, on the one hand, on technical advances in imaging and data processing and, on the other hand, on progress in fluorescent marker technologies. Among these, genetically encodable fluorescent proteins (FPs) are invaluable tools, as they allow facile labeling of live cells, tissues or organisms, as these produce the FP markers all by themselves after introduction of a suitable gene. Here we cover FP markers from the GFP family of proteins as well as tetrapyrrole-binding proteins, which further complement the FP toolbox in important ways. A broad range of FP variants have been endowed, by using protein engineering, with photophysical properties that are essential for specific fluorescence microscopy techniques, notably those offering nanoscale image resolution. We briefly introduce various advanced imaging methods and show how they utilize the distinct properties of the FP markers in exciting imaging applications, with the aim to guide researchers toward the design of powerful imaging experiments that are optimally suited to address their biological questions.The study of natural cellular materials offers valuable insights into the superior properties and functions underlying their unique structure and benefits the design and fabrication of advanced biomimetic materials. In this study, we present a systematic investigation of the mechanical behavior of fresh and oven-dried pomelo peels. Density measurements revealed the gradient structure of the pomelo peel, which contributed to its mechanical properties. Step-by-step drying revealed two types of water in the peel. Both uniaxial compression and low-strain hysteresis tests were conducted, and the results showed that fresh pomelo peel exhibits soft elastomer-like behavior, while dried pomelo peel behaves more like conventional synthetic polymer foam. Compared to fresh pomelo peel, dried peel samples showed higher compressive modulus and energy loss in 6, 8 and 10% strain hysteresis tests. The rehydration process was studied using hysteresis tests at three different strains. In addition, multilayer gradient EO/EO and LDPE/LDPE film/foams with 16 alternating layers were produced using the microlayer coextrusion technique. The morphology and mechanical properties were examined and indicated great potential for biomimicking the structure and properties of pomelo peel.Objective. Glioma is one of the most fatal cancers in the world which has been divided into low grade glioma (LGG) and high grade glioma (HGG), and its image grading has become a hot topic of contemporary research. Magnetic resonance imaging (MRI) is a vital diagnostic tool for brain tumor detection, analysis, and surgical planning. Accurate and automatic glioma grading is crucial for speeding up diagnosis and treatment planning. Aiming at the problems of (1) large number of parameters, (2) complex calculation, and (3) poor speed of the current glioma grading algorithms based on deep learning, this paper proposes a lightweight 3D UNet deep learning framework, which can improve classification accuracy in comparison with the existing methods.Approach. To improve efficiency while maintaining accuracy, existing 3D UNet has been excluded, and depthwise separable convolution has been applied to 3D convolution to reduce the number of network parameters. The weight of parameters on the basis of space and channel compression & excitation module has been strengthened to improve the model in the feature map, reduce the weight of redundant parameters, and strengthen the performance of the model.Main results. A total of 560 patients with glioma were retrospectively reviewed. All patients underwent MRI before surgery. The experiments were carried out on T1w, T2w, fluid attenuated inversion recovery, and CET1w images. Additionally, a way of marking tumor area by cube bounding box is presented which has no significant difference in model performance with the manually drawn ground truth. Evaluated on test datasets using the proposed model has shown good results (with accuracy of 89.29%).Significance. This work serves to achieve LGG/HGG grading by simple, effective, and non-invasive diagnostic approaches to provide diagnostic suggestions for clinical usage, thereby facilitating hasten treatment decisions.Due to the challenging communication and control systems, few underwater multi-robot coordination systems are currently developed. In nature, weakly electric fish can organize their collective activities using electrocommunication in turbid water. Inspired by this communication mechanism, we developed an artificial electrocommunication system for underwater robots in our previous work. In this study, we coordinate a group of underwater robots using this bio-inspired electrocommunication. We first design a time division multiple access (TDMA) network protocol for electrocommunication to avoid communication conflicts during multi-robot coordination. Then, we revise a distributed controller to coordinate a group of underwater robots. The distributed controller on each robot generates the required controls based on adjacent states obtained through electrocommunication. A central pattern generator (CPG) controller is designed to adjust the speed of individuals according to distributed control law. Simulations and experimental results show that a group of underwater robots is able to achieve coordination with the developed electrocommunication and control systems.
Inflammatory and insulin pathways have been linked to prostate cancer; postdiagnostic behaviors activating these pathways may lead to poor outcomes. The empirical dietary inflammatory pattern (EDIP), empirical dietary index for hyperinsulinemia (EDIH), and empirical dietary index for insulin resistance (EDIR), and associated lifestyle indices (ELIH, ELIR) predict biomarkers of inflammation (EDIP IL6, TNFaR2, CRP) and insulin secretion (EDIH/ELIH c-peptide; EDIR/ELIR TAGHDL) from whole foods and behaviors.

Associations of these indices with time to prostate cancer progression (primary, n = 2,056) and prostate cancer-specific mortality (PCSM; secondary, n = 2,447) were estimated among men diagnosed with nonmetastatic prostate cancer in the Cancer of the Prostate Strategic Urologic Research Endeavor cohort diet and lifestyle sub-study. Because the true (versus clinically documented) date of progression is unobserved, we used parametric (Weibull) survival models to accommodate interval-censoringand estimated adjusted HR and 95% confidence intervals (CI) for prostate cancer progression per 1-SD increase in index.
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