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In this study, a revised scaling law for laboratory test models of strip foundations on cohesionless soils is proposed. The centrifuge model tests were conducted on a strip model foundation at four different gravity levels (1 g, 5 g, 7.5 g, and 10 g), and the test results were used to calibrate numerical simulations. A set of numerical models were created to simulate full-scale tests and laboratory-scale tests. From the numerical simulations, the behavior of a foundation in the centrifuge model test is similar to that of the full-scale test but is different from the behavior in the laboratory-scale test under the 1 g condition. A parametric study was performed by varying the key variables that are internal friction angle, foundation width, and gravitational acceleration. The stress scale ratio is approximate to the geometric scale ratio in the 1 g model test. However, the settlement conversion requires both the geometric scale ratio and the settlement scale ratio newly proposed. The settlement scale ratio increases with increasing the internal friction angle and geometric scale ratio; accordingly, an equation for calculating the settlement scale ratio is proposed.

Purpose Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios. Design/methodology/approach A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale. Findings The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases. Originality/value A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

The newly proposed correlation filter based trackers can achieve appealing performance despite their great simplicity and superior speed. However, this kind of object trackers is not born with scale and aspect ratio adaptability, thus resulting in suboptimal tracking accuracy. To tackle this problem, this paper integrates the class-agnostic detection proposal method, which is widely adopted in object detection area, into a correlation filter tracker. In the tracker part, optimizations such as feature integration, robust model updating and proposal rejection are applied for efficient integration. As for proposal generation, through integrating and comparing four detection proposal generators along with two baseline methods, the quality of detection proposals is found to have considerable influence on tracking accuracy. Therefore, as the most promising proposal generator, EdgeBoxes is chosen and further enhanced with background suppression. Evaluations are mainly performed on a challenging 50-sequence dataset (OTB50) and its two subsets, 28 sequences with significant scale variation and 14 sequences with obvious aspect ratio change. Among the trackers equipped with different proposal generators, state-of-the-art trackers and existing correlation filter variants, our proposed tracker reports the highest accuracy while running efficiently at an average speed of 20.4 frames per second. Additionally, numerical performance analysis in per-sequence manner and experiment results on VOT2014 dataset are also presented to enable deeper insights into our approach.

In this research, amplitude motion and frequency simulation of a thick annular microsystem with graphene nanoplatelets (GPL) reinforcement in the framework of the modified couple stress theory (MCST) is undertaken. For obtaining the effective Poisson ratio, and mass density, the role of mixture is employed. As well as this, the Halpin–Tsai micromechanics model is presented for modeling the effective Young module of the current composite microstructure. The mathematical formulations of the current microstructure, size-dependent governing equations and boundary conditions are obtained by considering the MCST’s terms such as higher-order stress tensors, and symmetric rotation gradient into strain energy of the size-dependent GPL reinforced composite (GPLRC) microstructure. Finally, the generalized differential quadrature method (GDQM) is employed to obtain eigenvalue and eigenvectors of the GPLRC microsystem. Afterward, a parametric study is conducted to present the impacts of the radios ratio, length scale parameter, viscoelastic parameter, radial and circumferential mode number, and GPL’s geometry, on the amplitude motion, and frequency characteristics of the GPLRC annular microsystem. The results demonstrate that in the higher value of the radius ratio and time-dependent parameter, we can ignore the influence of length scale parameter on the amplitude and frequency of the annular microsystem. The useful suggestion of this study is that as the thickness of the GPLs increases, the impact of length scale parameter on the frequency of the annular microsystem decreases.

We present large scale facial model (LSFM)—a 3D Morphable Model (3DMM) automatically constructed from 9663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. To build such a large model we introduce a novel fully automated and robust Morphable Model construction pipeline, informed by an evaluation of state-of-the-art dense correspondence techniques. The dataset that LSFM is trained on includes rich demographic information about each subject, allowing for the construction of not only a global 3DMM model but also models tailored for specific age, gender or ethnicity groups. We utilize the proposed model to perform age classification from 3D shape alone and to reconstruct noisy out-of-sample data in the low-dimensional model space. Furthermore, we perform a systematic analysis of the constructed 3DMM models that showcases their quality and descriptive power. The presented extensive qualitative and quantitative evaluations reveal that the proposed 3DMM achieves state-of-the-art results, outperforming existing models by a large margin. Finally, for the benefit of the research community, we make publicly available the source code of the proposed automatic 3DMM construction pipeline, as well as the constructed global 3DMM and a variety of bespoke models tailored by age, gender and ethnicity.

Recent initiatives such as The Cancer Genome Atlas have mapped the genome-wide effect of individual genes on tumor growth. By unraveling genomic alterations in tumors, molecular subtypes of cancers have been identified, which is improving patient diagnostics and treatment. Uhlen et al. developed a computer-based modeling approach to examine different cancer types in nearly 8000 patients. They provide an open-access resource for exploring how the expression of specific genes influences patient survival in 17 different types of cancer. More than 900,000 patient survival profiles are available, including for tumors of colon, prostate, lung, and breast origin. This interactive data set can also be used to generate personalized patient models to predict how metabolic changes can influence tumor growth. Science , this issue p. eaan2507 A systems biology approach should allow genome-wide exploration of the effect of individual proteins on cancer clinical outcomes. Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database ( www.proteinatlas.org/pathology ) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

In visual object tracking, robust scale estimation is always a challenging problem. Because of the fast movement of the target, the background, the relative distance and relative azimuth angle between the target and the background usually change greatly. However, traditional correlation filtering tracking method cannot track the target accurately or even lose the target when the target scale and aspect ratio change. To address these problems, this paper adds two independent filters for the length and width scale estimation to complete the adaptive tracking on the basis of the translation filter. The experimental results in the public data set show that: compared with the original trackers, our method improves the tracking accuracy significantly, and meets the needs of real-time target tracking.

Energy generation by wind and solar farms could reduce carbon emissions and thus mitigate anthropogenic climate change. But is this its only benefit? Li et al. conducted experiments using a climate model to show that the installation of large-scale wind and solar power generation facilities in the Sahara could cause more local rainfall, particularly in the neighboring Sahel region. This effect, caused by a combination of increased surface drag and reduced albedo, could increase coverage by vegetation, creating a positive feedback that would further increase rainfall. Science , this issue p. 1019 Large wind and solar farms could increase local rainfall and vegetation cover in the Sahara. Wind and solar farms offer a major pathway to clean, renewable energies. However, these farms would significantly change land surface properties, and, if sufficiently large, the farms may lead to unintended climate consequences. In this study, we used a climate model with dynamic vegetation to show that large-scale installations of wind and solar farms covering the Sahara lead to a local temperature increase and more than a twofold precipitation increase, especially in the Sahel, through increased surface friction and reduced albedo. The resulting increase in vegetation further enhances precipitation, creating a positive albedo–precipitation–vegetation feedback that contributes ~80% of the precipitation increase for wind farms. This local enhancement is scale dependent and is particular to the Sahara, with small impacts in other deserts.

A bstract We present a practical three-step procedure of using the Standard Model effective field theory (SM EFT) to connect ultraviolet (UV) models of new physics with weak scale precision observables. With this procedure, one can interpret precision measurements as constraints on a given UV model. We give a detailed explanation for calculating the effective action up to one-loop order in a manifestly gauge covariant fashion. This covariant derivative expansion method dramatically simplifies the process of matching a UV model with the SM EFT, and also makes available a universal formalism that is easy to use for a variety of UV models. A few general aspects of RG running effects and choosing operator bases are discussed. Finally, we provide mapping results between the bosonic sector of the SM EFT and a complete set of precision electroweak and Higgs observables to which present and near future experiments are sensitive. Many results and tools which should prove useful to those wishing to use the SM EFT are detailed in several appendices.

We investigate the effect of using convection-permitting models (CPMs) spanning a pan-European domain on the representation of precipitation distribution at a climatic scale. In particular we compare two 2.2 km models with two 12 km models run by ETH Zürich (ETH-12 km and ETH-2.2 km) and the Met-Office (UKMO-12 km and UKMO-2.2 km). The two CPMs yield qualitatively similar differences to the precipitation climatology compared to the 12 km models, despite using different dynamical cores and different parameterization packages. A quantitative analysis confirms that the CPMs give the largest differences compared to 12 km models in the hourly precipitation distribution in regions and seasons where convection is a key process: in summer across the whole of Europe and in autumn over the Mediterranean Sea and coasts. Mean precipitation is increased over high orography, with an increased amplitude of the diurnal cycle. We highlight that both CPMs show an increased number of moderate to intense short-lasting events and a decreased number of longer-lasting low-intensity events everywhere, correcting (and often over-correcting) biases in the 12 km models. The overall hourly distribution and the intensity of the most intense events is improved in Switzerland and to a lesser extent in the UK but deteriorates in Germany. The timing of the peak in the diurnal cycle of precipitation is improved. At the daily time-scale, differences in the precipitation distribution are less clear but the greater Alpine region stands out with the largest differences. Also, Mediterranean autumnal intense events are better represented at the daily time-scale in both 2.2 km models, due to improved representation of mesoscale processes.