Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
5,067
result(s) for
"Xie Zhong"
Sort by:
ثقافة الطعام الصيني
الصين دولة ذات حضارة عريقة وتاريخ طويل، ظلت خلال هذا التاريخ الطويل محتفظة بالكثير من عاداتها وتقاليدها ولغتها حتى ملابس أهلها. يعيش على أرضها ستة وخمسين قومية تتمتع كل قومية منها بعادات وتقاليد وثقافة خاصة. هذا الكتاب رحلة ثقافية شيقة إذ يسلط الضوء على جانب من أهم جوانب الثقافة الصينية ألا وهو \"ثقافة الطعام الصيني. فيلقى الضوء على تاريخ الأطعمة الصينية وثقافتها وتقسيمات المطبخ الصيني وعادات وثقافة الأطعمة الخاصة بالأعياد والمناسبات التقليدية، وثقافة الأطعمة الخاصة بالديانات المختلفة في الصين بما فيها البوذية والطاوية والإسلام والمسيحية وعادات الطعام عند القوميات الصينية، ويهتم بتقديم بعض الجوانب المهمة بثقافة الشاي الصيني وأنواعه وطرق وآداب تناوله هذا الكتاب وجبة دسمة من المعلومات الخاصة بثقافة الأطعمة الصينية التي شهدت خلال السنوات الأخيرة انتشارا واسعا على مستوى العالم بما في ذلك المنطقة العربية.
Book
Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters
Very high resolution (VHR) remote sensing imagery has been used for land cover classification, and it tends to a transition from land-use classification to pixel-level semantic segmentation. Inspired by the recent success of deep learning and the filter method in computer vision, this work provides a segmentation model, which designs an image segmentation neural network based on the deep residual networks and uses a guided filter to extract buildings in remote sensing imagery. Our method includes the following steps: first, the VHR remote sensing imagery is preprocessed and some hand-crafted features are calculated. Second, a designed deep network architecture is trained with the urban district remote sensing image to extract buildings at the pixel level. Third, a guided filter is employed to optimize the classification map produced by deep learning; at the same time, some salt-and-pepper noise is removed. Experimental results based on the Vaihingen and Potsdam datasets demonstrate that our method, which benefits from neural networks and guided filtering, achieves a higher overall accuracy when compared with other machine learning and deep learning methods. The method proposed shows outstanding performance in terms of the building extraction from diversified objects in the urban district.
Journal Article
Road Extraction from High-Resolution Remote Sensing Imagery Using Deep Learning
The road network plays an important role in the modern traffic system; as development occurs, the road structure changes frequently. Owing to the advancements in the field of high-resolution remote sensing, and the success of semantic segmentation success using deep learning in computer version, extracting the road network from high-resolution remote sensing imagery is becoming increasingly popular, and has become a new tool to update the geospatial database. Considering that the training dataset of the deep convolutional neural network will be clipped to a fixed size, which lead to the roads run through each sample, and that different kinds of road types have different widths, this work provides a segmentation model that was designed based on densely connected convolutional networks (DenseNet) and introduces the local and global attention units. The aim of this work is to propose a novel road extraction method that can efficiently extract the road network from remote sensing imagery with local and global information. A dataset from Google Earth was used to validate the method, and experiments showed that the proposed deep convolutional neural network can extract the road network accurately and effectively. This method also achieves a harmonic mean of precision and recall higher than other machine learning and deep learning methods.
Journal Article
Dopamine metabolism by a monoamine oxidase mitochondrial shuttle activates the electron transport chain
Monoamine oxidase (MAO) metabolizes cytosolic dopamine (DA), thereby limiting auto-oxidation, but is also thought to generate cytosolic hydrogen peroxide (H2O2). We show that MAO metabolism of DA does not increase cytosolic H2O2 but leads to mitochondrial electron transport chain (ETC) activity. This is dependent upon MAO anchoring to the outer mitochondrial membrane and shuttling electrons through the intermembrane space to support the bioenergetic demands of phasic DA release.Graves et al. demonstrate that as the neurotransmitter dopamine cycles through the cytosol at release sites, it can be metabolized by a mitochondrial enzyme to help generate the energy necessary to sustain synaptic function.
Journal Article
Hydrogen Sulfide and Cellular Redox Homeostasis
Intracellular redox imbalance is mainly caused by overproduction of reactive oxygen species (ROS) or weakness of the natural antioxidant defense system. It is involved in the pathophysiology of a wide array of human diseases. Hydrogen sulfide (H2S) is now recognized as the third “gasotransmitters” and proved to exert a wide range of physiological and cytoprotective functions in the biological systems. Among these functions, the role of H2S in oxidative stress has been one of the main focuses over years. However, the underlying mechanisms for the antioxidant effect of H2S are still poorly comprehended. This review presents an overview of the current understanding of H2S specially focusing on the new understanding and mechanisms of the antioxidant effects of H2S based on recent reports. Both inhibition of ROS generation and stimulation of antioxidants are discussed. H2S-induced S-sulfhydration of key proteins (e.g., p66Shc and Keap1) is also one of the focuses of this review.
Journal Article
Engineering a PAM-flexible SpdCas9 variant as a universal gene repressor
The RNA-guided CRISPR-associated Cas9 proteins have been widely applied in programmable genome recombination, base editing or gene regulation in both prokaryotes and eukaryotes. SpCas9 from
Streptococcus pyogenes
is the most extensively engineered Cas9 with robust and manifold functionalities. However, one inherent limitation of SpCas9 is its stringent 5′-NGG-3′ PAM requirement that significantly restricts its DNA target range. Here, to repurpose SpCas9 as a universal gene repressor, we generate and screen variants of the deactivated SpCas9 (SpdCas9) with relaxed 5′-CAT-3′ PAM compatibility that can bind to the start codon ATG of almost any gene. Stepwise structure-guided mutations of the PAM-interacting residues and auxiliary PAM-proximal residues of the SpdNG (5′-NG-3′ PAM) create a PAM-flexible variant SpdNG-LWQT that preferentially accommodates 5′-NRN-3′ PAMs. SpdNG-LWQT is demonstrated to be effective in gene repression with the advantage of customizable sgRNA design in both
Escherichia coli
and
Saccharomyces cerevisiae
. This work validates the feasibility of purposeful PAM expansion of Cas9 towards signature PAMs and establishes a universal SpdCas9-based gene repressor.
SpCas9 has a NGG PAM requirement that limits its DNA target range. Here the authors present a PAM-expanded SpdCas9 variant SpdNG-LWQT to target NRN PAMs.
Journal Article
TE-SAGAN: An Improved Generative Adversarial Network for Remote Sensing Super-Resolution Images
Resolution is a comprehensive reflection and evaluation index for the visual quality of remote sensing images. Super-resolution processing has been widely applied for extracting information from remote sensing images. Recently, deep learning methods have found increasing application in the super-resolution processing of remote sensing images. However, issues such as blurry object edges and existing artifacts persist. To overcome these issues, this study proposes an improved generative adversarial network with self-attention and texture enhancement (TE-SAGAN) for remote sensing super-resolution images. We first designed an improved generator based on the residual dense block with a self-attention mechanism and weight normalization. The generator gains the feature extraction capability and enhances the training model stability to improve edge contour and texture. Subsequently, a joint loss, which is a combination of L1-norm, perceptual, and texture losses, is designed to optimize the training process and remove artifacts. The L1-norm loss is designed to ensure the consistency of low-frequency pixels; perceptual loss is used to entrench medium- and high-frequency details; and texture loss provides the local features for the super-resolution process. The results of experiments using a publicly available dataset (UC Merced Land Use dataset) and our dataset show that the proposed TE-SAGAN yields clear edges and textures in the super-resolution reconstruction of remote sensing images.
Journal Article
Greater Biofilm Formation and Increased Biodegradation of Polyethylene Film by a Microbial Consortium of Arthrobacter sp. and Streptomyces sp
The widespread use of polyethylene (PE) mulch films has led to a significant accumulation of plastic waste in agricultural soils. The biodegradation of plastic waste by microorganisms promises to provide a cost-effective and environmentally-friendly alternative for mitigating soil plastic pollution. A large number of microorganisms capable of degrading PE have been reported, but degradation may be further enhanced by the cooperative activity of multiple microbial species. Here, two novel strains of Arthrobacter sp. and Streptomyces sp. were isolated from agricultural soils and shown to grow with PE film as a sole carbon source. Arthrobacter sp. mainly grew in the suspension phase of the culture, and Streptomyces sp. formed substantial biofilms on the surface of the PE film, indicating that these strains were of different metabolic types and occupied different microenvironments with contrasting nutritional access. Individual strains were able to degrade the PE film to some extent in a 90-day inoculation experiment, as indicated by decreased hydrophobicity, increased carbonyl index and CO2 evolution, and the formation of biofilms on the film surface. However, a consortium of both strains had a much greater effect on these degradation properties. Together, these results provide new insights into the mechanisms of PE biodegradation by a microbial consortium composed of different types of microbes with possible metabolic complementarities.
Journal Article
Dopamine neurons derived from human ES cells efficiently engraft in animal models of Parkinson’s disease
A new strategy for derivation of human midbrain dopamine neurons from pluripotent cells was developed; transplantation of the neurons in mice, rats and parkinsonian monkeys show they are a promising source of cells for applications in regenerative medicine.
Repairing parkinsonian tissue
Lorenz Studer and colleagues have developed a new strategy for the efficient derivation of human midbrain dopamine (DA) neurons from pluripotent stem cells. The DA neurons showed functionality
in vivo
and achieved long-term engraftment in three Parkinson's disease model systems (6-OHDA-lesioned mice and rats, and transplantation into parkinsonian monkeys). The DA neurons are a promising source of cells for applications in regenerative medicine.
Human pluripotent stem cells (PSCs) are a promising source of cells for applications in regenerative medicine. Directed differentiation of PSCs into specialized cells such as spinal motoneurons
1
or midbrain dopamine (DA) neurons
2
has been achieved. However, the effective use of PSCs for cell therapy has lagged behind. Whereas mouse PSC-derived DA neurons have shown efficacy in models of Parkinson’s disease
3
,
4
, DA neurons from human PSCs generally show poor
in vivo
performance
5
. There are also considerable safety concerns for PSCs related to their potential for teratoma formation or neural overgrowth
6
,
7
. Here we present a novel floor-plate-based strategy for the derivation of human DA neurons that efficiently engraft
in vivo
, suggesting that past failures were due to incomplete specification rather than a specific vulnerability of the cells. Midbrain floor-plate precursors are derived from PSCs 11 days after exposure to small molecule activators of sonic hedgehog (SHH) and canonical WNT signalling. Engraftable midbrain DA neurons are obtained by day 25 and can be maintained
in vitro
for several months. Extensive molecular profiling, biochemical and electrophysiological data define developmental progression and confirm identity of PSC-derived midbrain DA neurons.
In vivo
survival and function is demonstrated in Parkinson’s disease models using three host species. Long-term engraftment in 6-hydroxy-dopamine-lesioned mice and rats demonstrates robust survival of midbrain DA neurons derived from human embryonic stem (ES) cells, complete restoration of amphetamine-induced rotation behaviour and improvements in tests of forelimb use and akinesia. Finally, scalability is demonstrated by transplantation into parkinsonian monkeys. Excellent DA neuron survival, function and lack of neural overgrowth in the three animal models indicate promise for the development of cell-based therapies in Parkinson’s disease.
Journal Article