In this paper, a stochastic traffic assignment model for networks is proposed for the study of discrete dynamic Bayesian algorithms. In this paper, we study a feasible method and theoretical system ...for implementing traffic engineering in networks based on Bayesian algorithm theory. We study the implementation of traffic assignment engineering in conjunction with the network stochastic model: first, we study the Bayesian algorithm theoretical model of control layer stripping in the network based on the discrete dynamic Bayesian algorithm theory and analyze the resource-sharing mechanism in different queuing rules; second, we study the extraction and evaluation theory of traffic assignment for the global view obtained by the control layer of the network and establish the Bayesian algorithm analysis model based on the traffic assignment; subsequently, the routing of bandwidth guarantee and delay guarantee in the network is studied based on Bayesian algorithm model and Bayesian algorithm network random traffic allocation theory. In this paper, a Bayesian algorithm estimation model based on Bayesian algorithm theory is constructed based on network random observed traffic assignment as input data. The model assumes that the roadway traffic distribution follows the network random principle, and based on this assumption, the likelihood function of the roadway online traffic under the network random condition is derived; the prior distribution of the roadway traffic is derived based on the maximum entropy principle; the posterior distribution of the roadway traffic is solved by combining the likelihood function and the prior distribution. The corresponding algorithm is designed for the model with roadway traffic as input, and the reliability of the algorithm is verified in the arithmetic example.
As a highly appealing technology for hydrogen generation, water electrolysis including oxygen evolution reaction (OER) at the anode and hydrogen evolution reaction (HER) at the cathode largely ...depends on the availability of efficient electrocatalysts. Accordingly, over the past years, much effort has been made to develop various electrocatalysts with superior performance and reduced cost. Among them, ruthenium (Ru)-based materials for OER and HER are very promising because of their prominent catalytic activity, pH-universal application, the cheapest price among the precious metal family, and so on. Herein, recent advances in this hot research field are comprehensively reviewed. A general description about water splitting is presented to understand the reaction mechanism and proposed scaling relations toward activities, and key stability issues for Ru-based materials are further given. Subsequently, various Ru-involving electrocatalysts are introduced and classified into different groups for improving or optimizing electrocatalytic properties, with a special focus on several significant bifunctional electrocatalysts along with a simulated water electrolyzer. Finally, a perspective on the existing challenges and future progress of Ru-based catalysts toward OER and HER is provided. The main aim here is to shed some light on the design and construction of emerging catalysts for energy storage and conversion technologies.
Scene text detection is an important step in the scene text reading system. The main challenges lie in significantly varied sizes and aspect ratios, arbitrary orientations, and shapes. Driven by the ...recent progress in deep learning, impressive performances have been achieved for multi-oriented text detection. Yet, the performance drops dramatically in detecting the curved texts due to the limited text representation (e.g., horizontal bounding boxes, rotated rectangles, or quadrilaterals). It is of great interest to detect the curved texts, which are actually very common in natural scenes. In this paper, we present a novel text detector named TextField for detecting irregular scene texts. Specifically, we learn a direction field pointing away from the nearest text boundary to each text point. This direction field is represented by an image of 2D vectors and learned via a fully convolutional neural network. It encodes both binary text mask and direction information used to separate adjacent text instances, which is challenging for the classical segmentation-based approaches. Based on the learned direction field, we apply a simple yet effective morphological-based post-processing to achieve the final detection. The experimental results show that the proposed TextField outperforms the state-of-the-art methods by a large margin (28% and 8%) on two curved text datasets: Total-Text and SCUT-CTW1500, respectively; TextField also achieves very competitive performance on multi-oriented datasets: ICDAR 2015 and MSRA-TD500. Furthermore, TextField is robust in generalizing unseen datasets.
The current advances in the development of technologies for solar light utilization are largely due to the environmental and energy crisis caused by the rapid consumption of fossil fuels, and ...consequently, various applications have been implemented in domestic heating devices, the field of spaceflight, vehicles with clean energy, self-cleaning devices, the bio-pharmaceutical field, etc ...
Discoveries of novel functional materials have played very important roles to the development of science and technologies and thus to benefit our daily life. Among the diverse materials, ...metal–organic framework (MOF) materials are rapidly emerging as a unique type of porous and organic/inorganic hybrid materials which can be simply self-assembled from their corresponding inorganic metal ions/clusters with organic linkers, and can be straightforwardly characterized by various analytical methods. In terms of porosity, they are superior to other well-known porous materials such as zeolites and carbon materials; exhibiting extremely high porosity with surface area up to 7000 m2/g, tunable pore sizes, and metrics through the interplay of both organic and inorganic components with the pore sizes ranging from 3 to 100 Å, and lowest framework density down to 0.13 g/cm3. Such unique features have enabled metal–organic frameworks to exhibit great potentials for a broad range of applications in gas storage, gas separations, enantioselective separations, heterogeneous catalysis, chemical sensing and drug delivery. On the other hand, metal–organic frameworks can be also considered as organic/inorganic self-assembled hybrid materials, we can take advantages of the physical and chemical properties of both organic and inorganic components to develop their functional optical, photonic, and magnetic materials. Furthermore, the pores within MOFs can also be utilized to encapsulate a large number of different species of diverse functions, so a variety of functional MOF/composite materials can be readily synthesized. In this Account, we describe our recent research progress on pore and function engineering to develop functional MOF materials. We have been able to tune and optimize pore spaces, immobilize specific functional groups, and introduce chiral pore environments to target MOF materials for methane storage, light hydrocarbon separations, enantioselective recognitions, carbon dioxide capture, and separations. The intrinsic optical and photonic properties of metal ions and organic ligands, and guest molecules and/or ions can be collaboratively assembled and/or encapsulated into their frameworks, so we have realized a series of novel MOF materials as ratiometric luminescent thermometers, O2 sensors, white-light-emitting materials, nonlinear optical materials, two-photon pumped lasing materials, and two-photon responsive materials for 3D patterning and data storage. Thanks to the interplay of the dual functionalities of metal–organic frameworks (the inherent porosity, and the intrinsic physical and chemical properties of inorganic and organic building blocks and encapsulated guest species), our research efforts have led to the development of functional MOF materials beyond our initial imaginations.
There are great challenges in developing efficient adsorbents to replace the currently used and energy-intensive cryogenic distillation processes for olefin/paraffin separation, owing to the similar ...physical properties of the two molecules. Here we report an ultramicroporous metal-organic framework Ca(C
O
)(H
O), synthesized from calcium nitrate and squaric acid, that possesses rigid one-dimensional channels. These apertures are of a similar size to ethylene molecules, but owing to the size, shape and rigidity of the pores, act as molecular sieves to prevent the transport of ethane. The efficiency of this molecular sieve for the separation of ethylene/ethane mixtures is validated by breakthrough experiments with high ethylene productivity under ambient conditions. This material can be easily synthesized at the kilogram scale using an environmentally friendly method and is water-stable, which is important for potential industrial implementation. The strategy of using highly rigid metal-organic frameworks with well defined and rigid pores could also be extended to other porous materials for chemical separation processes.
Understanding the effects of external organic and inorganic components on soil fertility and quality is essential for improving low-yielding soils. We conducted a field study over two consecutive ...rice growing seasons to investigate the effect of applying chemical fertilizer (NPK), NPK plus green manure (NPKG), NPK plus pig manure (NPKM), and NPK plus straw (NPKS) on the soil nutrient status, enzyme activities involved in C, N, P, and S cycling, microbial community and rice yields of yellow clayey soil. Results showed that the fertilized treatments significantly improved rice yields over the first three experimental seasons. Compared with the NPK treatment, organic amendments produced more favorable effects on soil productivity. Notably, the NPKM treatment exhibited the highest levels of nutrient availability, microbial biomass carbon (MBC), activities of most enzymes and the microbial community. This resulted in the highest soil quality index (SQI) and rice yield, indicating better soil fertility and quality. Significant differences in enzyme activities and the microbial community were observed among the treatments, and redundancy analysis showed that MBC and available N were the key determinants affecting the soil enzyme activities and microbial community. The SQI score of the non-fertilized control (0.72) was comparable to that of the NPK (0.77), NPKG (0.81) and NPKS (0.79) treatments but significantly lower compared with NPKM (0.85). The significant correlation between rice yield and SQI suggests that SQI can be a useful to quantify soil quality changes caused by different agricultural management practices. The results indicate that application of NPK plus pig manure is the preferred option to enhance SOC accumulation, improve soil fertility and quality, and increase rice yield in yellow clayey soil.
Understanding the roles of splicing factors and splicing events during tumorigenesis would open new avenues for targeted therapies. Here we identify an oncofetal splicing factor, MBNL3, which ...promotes tumorigenesis and indicates poor prognosis of hepatocellular carcinoma patients. MBNL3 knockdown almost completely abolishes hepatocellular carcinoma tumorigenesis. Transcriptomic analysis revealed that MBNL3 induces lncRNA-PXN-AS1 exon 4 inclusion. The transcript lacking exon 4 binds to coding sequences of PXN mRNA, causes dissociation of translation elongation factors from PXN mRNA, and thereby inhibits PXN mRNA translation. In contrast, the transcript containing exon 4 preferentially binds to the 3' untranslated region of PXN mRNA, protects PXN mRNA from microRNA-24-AGO2 complex-induced degradation, and thereby increases PXN expression. Through inducing exon 4 inclusion, MBNL3 upregulates PXN, which mediates the pro-tumorigenic roles of MBNL3. Collectively, these data demonstrate detailed mechanistic links between an oncofetal splicing factor, a splicing event and tumorigenesis, and establish splicing factors and splicing events as potential therapeutic targets.
Although numerous studies on the impacts of climate change on biodiversity have been published, only a handful are focused on the intraspecific level or consider population‐level models (separate ...models per population). We endeavored to fill this knowledge gap relative to the Qinghai‐Tibetan plateau (QTP) by combining species distribution modeling (SDMs) with population genetics (i.e., population‐level models) and phylogenetic methods (i.e., phylogenetic tree reconstruction and phylogenetic diversity analyses). We applied our models to 11 endemic and widely distributed herpetofauna species inhabiting high elevations in the QTP. We aimed to determine the influence of environmental heterogeneity on species’ responses to climate change, the magnitude of climate‐change impacts on intraspecific diversity, and the relationship between species range loss and intraspecific diversity losses under 2 shared socioeconomic pathways (SSP245 and SSP585) and 3 future periods (2050s, 2070s, and 2090s). The effects of global climatic change were more pronounced at the intraspecific level (22% of haplotypes lost and 36% of populations lost) than the morphospecies level in the SSP585 climate change scenario. Maintenance of genetic diversity was in general determined by a combination of factors including range changes, species genetic structure, and the part of the range predicted to be lost. This is owing to the fact that the loss and survival of populations were observed in species irrespective of the predicted range changes (contraction or expansion). In the southeast (mountainous regions), climate change had less of an effect on range size (>100% in 3 species) than in central and northern QTP plateau regions (range size <100% in all species). This may be attributed to environmental heterogeneity, which provided pockets of suitable climate in the southeast, whereas ecosystems in the north and central regions were homogeneous. Generally, our results imply that mountainous regions with high environmental heterogeneity and high genetic diversity may buffer the adverse impacts of climate change on species distribution and intraspecific diversity. Therefore, genetic structure and characteristics of the ecosystem may be crucial for conservation under climate change.
Impactos del cambio climático sobre la diversidad de herpetofauna en la meseta Qinghai‐Tíbet
Región
Aunque se han publicado numerosos estudios sobre los impactos del cambio climática en la biodiversidad, son muy pocos los que se enfocan en el nivel intraespecífico o que consideran modelos a nivel poblacional (modelos separados por población). Intentamos cerrar este vacío de conocimiento en relación con la meseta Qinghai‐Tíbet (MQT) con la combinación entre modelos de distribución de especies (MDE) y genética poblacional (modelos a nivel poblacional) y métodos filogenéticos (reconstrucción de árboles filogenéticos y análisis de diversidad filogenética). Aplicamos nuestros modelos a once especies endémicas de herpetofauna con distribución amplia en las elevaciones más altas de la MQT. Nos planteamos determinar la influencia de la heterogeneidad de las especies sobre la respuesta de las especies al cambio climático, la magnitud de los impactos del cambio climático sobre la diversidad intraespecífica y la relación entre la pérdida de distribución de la especie y las pérdidas de diversidad intraespecífica bajo dos vías socioeconómicas (SSP245 y SSP585) y tres periodos del futuro (2050s, 2070s y 2090s). Los efectos del cambio climático global fueron más pronunciados a nivel intraespecífico (22% de pérdida en los haplotipos y 36% en las poblaciones) que al nivel morfoespecie en el escenario de cambio climático SSP585. El mantenimiento de la diversidad genética casi siempre estuvo determinado por una combinación de factores que incluyen cambios en la distribución, estructura genética de las especies y la parte de la distribución que se pronosticó se perdería. Esto se debe a que observamos la pérdida y supervivencia de las poblaciones sin importar los cambios pronosticados en la distribución (contracción o expansión). En las regiones montañosas del sureste, el cambio climático tuvo un efecto menor sobre la distribución (>100% en tres especies) comparado con las regiones de la meseta central y del norte de la MQT (distribución <100% en todas las especies). Esto puede atribuirse a la heterogeneidad ambiental, la cual proporciona recovecos de clima adecuado en el sureste, mientras que los ecosistemas en las regiones central y norte fueron homogéneos. De manera general, nuestros resultados implican que las regiones montañosas con una elevada heterogeneidad ambiental y una gran diversidad genética podrían reducir los impactos adversos del cambio climático sobre la distribución de las especies y la diversidad intraespecífica. Por lo tanto, la estructura genética y las características del ecosistema pueden ser cruciales para conservar bajo el cambio climático.
【摘要】
尽管已有大量有关气候变化对生物多样性影响的研究发表, 但只有少数研究考虑种下或种群水平的模型。我们将物种分布模型(SDMs)与种群遗传学和系统发生学方法相结合, 填补青藏高原地区(QTP)在这一方面的研究空白。我们对11种栖息在青藏高原特有且分布广泛的两栖爬行动物进行了模型分析, 探究环境异质性对物种响应气候变化的影响、气候变化对种内多样性的影响程度、以及在SSP245和SSP585两种情景下, 未来(2050年、2070年和2090年)物种分布范围丧失与种内多样性丧失之间的关系。结果显示, 在SSP585气候变化情景中, 在种下有22%的单倍型和36%的种群将会丢失, 全球气候变化对种内多样性的影响比种间更为明显。遗传多样性是否能够维持一般由多种因素共同决定, 包括分布区的变化、物种遗传结构以及预测丢失的分布区。在青藏高原东南部山区, 气候变化对物种分布范围大小的影响(有3个物种的分布范围扩张)小于青藏高原北部和中部地区(所有物种的分布范围均缩小), 主要原因可能是东南部环境异质性更高, 物种可以选择较为合适的生境, 而北部和中部地区环境则趋于同质化。本研究结果表明, 环境异质性高、遗传多样性高的山区可以缓冲气候变化对物种分布和种内多样性的不利影响。因此, 生态系统的遗传结构和特征对于气候变化下的多样性保护至关重要。
Many protein‐coding oncofetal genes are highly expressed in murine and human fetal liver and silenced in adult liver. The protein products of these hepatic oncofetal genes have been used as clinical ...markers for the recurrence of hepatocellular carcinoma (HCC) and as therapeutic targets for HCC. Herein we examined the expression profiles of long noncoding RNAs (lncRNAs) found in fetal and adult liver in mice. Many fetal hepatic lncRNAs were identified; one of these, lncRNA‐mPvt1, is an oncofetal RNA that was found to promote cell proliferation, cell cycling, and the expression of stem cell‐like properties of murine cells. Interestingly, we found that human lncRNA‐hPVT1 was up‐regulated in HCC tissues and that patients with higher lncRNA‐hPVT1 expression had a poor clinical prognosis. The protumorigenic effects of lncRNA‐hPVT1 on cell proliferation, cell cycling, and stem cell‐like properties of HCC cells were confirmed both in vitro and in vivo by gain‐of‐function and loss‐of‐function experiments. Moreover, mRNA expression profile data showed that lncRNA‐hPVT1 up‐regulated a series of cell cycle genes in SMMC‐7721 cells. By RNA pulldown and mass spectrum experiments, we identified NOP2 as an RNA‐binding protein that binds to lncRNA‐hPVT1. We confirmed that lncRNA‐hPVT1 up‐regulated NOP2 by enhancing the stability of NOP2 proteins and that lncRNA‐hPVT1 function depends on the presence of NOP2. Conclusion: Our study demonstrates that the expression of many lncRNAs is up‐regulated in early liver development and that the fetal liver can be used to search for new diagnostic markers for HCC. LncRNA‐hPVT1 promotes cell proliferation, cell cycling, and the acquisition of stem cell‐like properties in HCC cells by stabilizing NOP2 protein. Regulation of the lncRNA‐hPVT1/NOP2 pathway may have beneficial effects on the treatment of HCC. (Hepatology 2014;60:1278–1290)
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