Steel Surface Defect Classification Based on Small Sample Learning

The classification of steel surface defects plays a very important role in analyzing their causes to improve manufacturing process and eliminate defects. However, defective samples are very scarce in actual production, so using very few samples to construct a good classifier is a challenge to be addressed. If the layer number of the model with proper depth is increased, the model accuracy will decrease (not caused by overfit), and the training error as well as the test error will be very high. This is called the degradation problem. In this paper, we propose to use feature extraction + feature transformation + nearest neighbors to classify steel surface defects. In order to solve the degradation problem caused by network deepening, the three feature extraction networks of Residual Net, Mobile Net and Dense Net are designed and analyzed. Experiment results show that in the case of a small sample number, Dense block can better solve the degradation problem caused by network deepening than Residual block. Moreover, if Dense Net is used as the feature extraction network, and the nearest neighbor classification algorithm based on Euclidean metric is used in the new feature space, the defect classification accuracy can reach 92.33% when only five labeled images of each category are used as the training set. This paper is of some guiding significance for surface defect classification when the sample number is small.

Improving Nonenzymatic Biosensing Performance of Electrospun Carbon Nanofibers Decorated With Ni/Co Particles via Oxidation

Electrochemical nonenzymatic biosensors with no immobilization and degradation problem, have recently attracted growing attention due to stability and reproducibility. Here, a comparative study was conducted to precisely evaluate the nonenzymatic glucose sensing of pure/oxidized Ni, Co, and their bimetal nanostructures grown on electrospun carbon nanofibers (ECNFs). This method provides a low-cost free stand electrode. The prepared nanostructures with superb physiochemical features exhibited sensitivity (from 66.28 to 610.6 μA mM−1 cm−2), linear range of 2-10 mM, limit of detection in the range of 1 mM, and response time (<5 s), besides outstanding selectivity and applicability for glucose detection in the human serum. Regarding Co-C and Ni-C phase diagrams, solid-state diffusion phenomena, and rearrangement of dissolved C atoms after migration from metal particles was discussed. This study undoubtedly provides new prospects on nonenzymatic biosensing performance of mono-metal, bimetal, and oxide compounds of Ni and Co elements, which is useful for the fabrication of biomolecules detecting devices.

An engineered, orthogonal auxin analog/AtTIR1(F79G) pairing improves both specificity and efficacy of the auxin degradation system in Caenorhabditis elegans

The auxin-inducible degradation system in C. elegans allows for spatial and temporal control of protein degradation via heterologous expression of a single Arabidopsis thaliana F-box protein, transport inhibitor response 1 (AtTIR1). In this system, exogenous auxin (Indole-3-acetic acid; IAA) enhances the ability of AtTIR1 to function as a substrate recognition component that adapts engineered degron-tagged proteins to the endogenous C. elegans E3 ubiquitin ligases complex (SKR-1/2-CUL-1-F-box (SCF)), targeting them for degradation by the proteosome. While this system has been employed to dissect the developmental functions of many C. elegans proteins, we have found that several auxin-inducible degron (AID)-tagged proteins are constitutively degraded by AtTIR1 in the absence of auxin, leading to undesired loss-of-function phenotypes. In this manuscript, we adapt an orthogonal auxin-derivative/mutant AtTIR1 pair (C. elegans AID version 2 (C.e.AIDv2)) that transforms the specificity of allosteric regulation of TIR1 from IAA to one that is dependent on an auxin derivative harboring a bulky aryl group (5-Ph-IAA). We find that a mutant AtTIR1(F79G) allele that alters the ligand binding interface of TIR1 dramatically reduces ligand-independent degradation of multiple AID*-tagged proteins. In addition to solving the ectopic degradation problem for some AID targets, addition of 5-Ph-IAA to culture media of animals expressing AtTIR1(F79G) leads to more penetrant loss-of-function phenotypes for AID*-tagged proteins than those elicited by the AtTIR1-IAA pairing at similar auxin analog concentrations. The improved specificity and efficacy afforded by the mutant AtTIR1(F79G) allele expands the utility of the AID system and broadens the number of proteins that can be effectively targeted with it.

Asynchronous Horizons Durable-Strategies Dynamic Games and Tragedy of Cross-Generational Environmental Commons

Different entry and exit times and overlapping generations of players are common in real-life game situations. In addition, durable strategies which have effects over a period of time are no less common than nondurable strategies which have only one-shot effects. This paper develops a new class of dynamic games which contains durable strategies with asynchronous players’ horizons. The optimization techniques for solving asynchronous horizons durable strategies control are derived. Noncooperative game equilibria and cooperative optimal solution are presented. An asynchronous horizons durable strategies dynamic environmental game is provided to analyze the seemingly catastrophe-bound environmental degradation problem. The Price of Anarchy (PoA) in cross-generational exploitation of environmental commons is calibrated. A cooperative solution with a dynamically stable compensatory scheme is presented to alleviate the problem.

Restoring Degraded Lands

Land degradation continues to be an enormous challenge to human societies, reducing food security, emitting greenhouse gases and aerosols, driving the loss of biodiversity, polluting water, and undermining a wide range of ecosystem services beyond food supply and water and climate regulation. Climate change will exacerbate several degradation processes. Investment in diverse restoration efforts, including sustainable agricultural and forest land management, as well as land set aside for conservation wherever possible, will generate co-benefits for climate change mitigation and adaptation and more broadly for human and societal well-being and the economy. This review highlights the magnitude of the degradation problem and some of the key challenges for ecological restoration. There are biophysical as well as societal limits to restoration. Better integrating policies to jointly address poverty, land degradation, and greenhouse gas emissions and removals is fundamental to reducing many existing barriers and contributing to climate-resilient sustainable development. Expected final online publication date for the Annual Review of Environment and Resources, Volume 46 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

An engineered, orthogonal auxin analog/AtTIR1(F79G) pairing improves both specificity and efficacy of the auxin degradation system in Caenorhabditis elegans

The auxin-inducible degradation system in C. elegans allows for spatial and temporal control of protein degradation via heterologous expression of a single Arabidopsis thaliana F-box protein, transport inhibitor response 1 (AtTIR1). In this system, exogenous auxin (Indole-3-acetic acid; IAA) enhances the ability of AtTIR1 to function as a substrate recognition component that adapts engineered degron-tagged proteins to the endogenous C. elegans E3 ubiquitin ligases complex (SKR-1/2-CUL-1-F-box (SCF)), targeting them for degradation by the proteosome. While this system has been employed to dissect the developmental functions of many C. elegans proteins, we have found that several auxin-inducible degron (AID)-tagged proteins are constitutively degraded by AtTIR1 in the absence of auxin, leading to undesired loss-of-function phenotypes. In this manuscript, we adapt an orthogonal auxin-derivative/mutant AtTIR1 pair (C. elegans AID version 2 (C.e.AIDv2)) that transforms the specificity of allosteric regulation of TIR1 from IAA to one that is dependent on an auxin derivative harboring a bulky aryl group (5-Ph-IAA). We find that a mutant AtTIR1(F79G) allele that alters the ligand binding interface of TIR1 dramatically reduces ligand-independent degradation of multiple AID*-tagged proteins. In addition to solving the ectopic degradation problem for some AID targets, addition of 5-Ph-IAA to culture media of animals expressing AtTIR1(F79G) leads to more penetrant loss-of-function phenotypes for AID*-tagged proteins than those elicited by the AtTIR1-IAA pairing at similar auxin analog concentrations. The improved specificity and efficacy afforded by the mutant AtTIR1(F79G) allele expands the utility of the AID system and broadens the number of proteins that can be effectively targeted with it.

An Indoor Localization System Using Residual Learning with Channel State Information

With the increasing demand of location-based services, neural network (NN)-based intelligent indoor localization has attracted great interest due to its high localization accuracy. However, deep NNs are usually affected by degradation and gradient vanishing. To fill this gap, we propose a novel indoor localization system, including denoising NN and residual network (ResNet), to predict the location of moving object by the channel state information (CSI). In the ResNet, to prevent overfitting, we replace all the residual blocks by the stochastic residual blocks. Specially, we explore the long-range stochastic shortcut connection (LRSSC) to solve the degradation problem and gradient vanishing. To obtain a large receptive field without losing information, we leverage the dilated convolution at the rear of the ResNet. Experimental results are presented to confirm that our system outperforms state-of-the-art methods in a representative indoor environment.

Terahertz Image Enhancing Based on the Physical Model and Multiscale Retinex Algorithm

To settle the THz image degradation problem, we propose an effective enhancement method based on the physical model and multiscale retinex (MSR) algorithm. The overall enhancing process involves two parts: reconstruction and enhancement. Firstly, the original THz images are reconstructed by a mathematical model, which is built and considered the THz absorption variate and Gaussian distribution of the beam. Then, the original images are processed by the proposed algorithm, which is combined the atmospheric scattering model and optimized MSR algorithm. The proposed algorithm not only recover the image scene radiance and remove haze, but also can make a compromise of the dynamic range of grayscale and edge enhancement of image. Results on a variety of THz images demonstrate our method can effectively improve the quality of THz images and retain sufficient image details.

Silvopastoralism, local ecological knowledge and forest trajectories in a Category V- type management area

Preserving landscape heritage elements and indigenous and local knowledge is an increasingly popular approach in conservation. We focus on a globally very contentious practice, silvopastoral livestock raising, which along with other peasant practices, is slated for elimination according to projected Chilean conservation policy. We used ecological surveys to ask how central Chilean semi-arid woodlands in the locality of Alhué have responded to past human livelihoods practices, including silvopastoralism. Using interviews, we examined local ecological knowledge and uses of forest plants. We also conducted surveys on current agricultural practices. Many residents maintain a diversified, smallholder subsistence agricultural strategy. Residents identified 113 plants with 73 uses. They also demonstrated a good knowledge of woodland regulations. We found that woodlands recover well from historical disturbances over 50-100 year time scales. In fact, the presence of cattle year-round in the woodlands was associated with greater tree regeneration. We find that despite the conservation discourse, there is no evidence of a degradation problem, and we hypothesize based on our findings that eradicating peasants’ silvopastoralism and other practices could increase degradation. We recommend that the Conservation Landscape programme be used to save key traditional practices, which should be studied further to determine optimal management. We show how conflicts and misalignments within and between ILK, data, and environmental discourse can signal complex socio-ecological issues where a closer look at how the evidence fits together is necessary.