How to choose the agent construction mode in chinese government investment projects?

The complexity of managing government investment projects arrives, among others, from the fact it involves many stakeholders. Managerial problems in government investment projects resulting in inefficiencies, waste of resources, and delays often appear in China. Government departments used to control all the aspects of a project, including construction, investment, management, and use which result in waste and rent-seeking behaviors. On July 25, 2004, the state council published the document "Decision on Investment System Reform" which clearly put forward the requirements of using construction agents in non-profit government investment projects. Methods of selecting and managing construction agents are different in different regions in China. We adopted qualitative research methods. First, we analyzed the principal-agent relationships and the information asymmetry in construction agent models, and discussed the theory methods to abate information asymmetry and decrease the moral hazard problem. Then we investigated five construction agent modes in five regions of China, and analyzed the project process and management methods. We found that these modes could be split into two types of construction agent models: "market competitive agent" construction model and "administrative agent" construction model. Finally, we analyzed CIXI city’s construction agent model in non - profit government investment project, and found that CIXI also used an “administrative agent" construction model. Therefore, we thought that although market competitive construction agent model is better than administrative construction agent model in theory, the latter might be a contingent way to adapt to the environment in the transition economy period that China is living.A complexidade da gestão de projetos de investimento dos governosé inegável mormente tendo em conta os incontáveis “stakeholders” envolvidos. Na China sempre existiram problemas de gestãonos projetos de investimento do governo que motivaram ineficiências, desperdícios de recursos e demoras na concretização desses projectos. Dado que os departamentos do governo controlavam todos os aspectos relativos aos projetos, incluindo construção, investimento, agenciamento e gestão, o resultado consubstanciou-se em elevados desperdícios e na geração de comportamentos oportunísticos. Em 25 de julho de 2004, o Conselho do Estado da China publicou um documento acerca da gestão de investimentos governamentais - “Decisão sobre a reforma do sistema de gestão de investimentos”. Sob este novo sistema, claramente, o governo apresentou os requisitos de utilização de agentes de construção nos projectos sem fins lucrativos de investimento do governo. Contudo os métodos de seleção e gestão dos referidos agentes são diferentes nas várias regiões da China. Neste trabalho foi utilizado o método qualitativo de pesquisa. Primeiro, analisou-se as relações principal-agente e a assimetria de informação nos modelos de agênciaem construção civil. Além disso, discutiram-se os métodos teóricos para diminuir a assimetria de informação e o problema de risco moral. Segundo, investigou-se os cinco modos deagente naconstrução em cinco regiões da China, e analisou-se o processo de projeto e os métodos de gestão, tendo-se descoberto que estas formas podem ser divididas em dois tipos de modelos de agente na construção: o modelo de construção "market competitive agent" e o modelo de construção "administrative agent", conforme mencionado anteriormente. Finalmente, analisou-se o modelo de agente de construção da cidade de CIXI em projectos sem fins lucrativos de investimento do governo. Ficou evidenciado que o modelo de construção “administrative agent” também foi utilizado nesta cidade. Por isso, conclui-se que, embora em teoria o modelo de construção "market competitive agent" seja melhor do que o de construção "administrative agent ", o último pode ser uma solução contingente e intermédia que se adapta ao período da economia em transição da China

Berberine Improves Glucose Metabolism in Diabetic Rats by Inhibition of Hepatic Gluconeogenesis

Berberine (BBR) is a compound originally identified in a Chinese herbal medicine Huanglian (Coptis chinensis French). It improves glucose metabolism in type 2 diabetic patients. The mechanisms involve in activation of adenosine monophosphate activated protein kinase (AMPK) and improvement of insulin sensitivity. However, it is not clear if BBR reduces blood glucose through other mechanism. In this study, we addressed this issue by examining liver response to BBR in diabetic rats, in which hyperglycemia was induced in Sprague-Dawley rats by high fat diet. We observed that BBR decreased fasting glucose significantly. Gluconeogenic genes, Phosphoenolpyruvate carboxykinase (PEPCK) and Glucose-6-phosphatase (G6Pase), were decreased in liver by BBR. Hepatic steatosis was also reduced by BBR and expression of fatty acid synthase (FAS) was inhibited in liver. Activities of transcription factors including Forkhead transcription factor O1 (FoxO1), sterol regulatory element-binding protein 1c (SREBP1) and carbohydrate responsive element-binding protein (ChREBP) were decreased. Insulin signaling pathway was not altered in the liver. In cultured hepatocytes, BBR inhibited oxygen consumption and reduced intracellular adenosine triphosphate (ATP) level. The data suggest that BBR improves fasting blood glucose by direct inhibition of gluconeogenesis in liver. This activity is not dependent on insulin action. The gluconeogenic inhibition is likely a result of mitochondria inhibition by BBR. The observation supports that BBR improves glucose metabolism through an insulin-independent pathway

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Multiple Feature Hashing Learning for Large-Scale Remote Sensing Image Retrieval

Driven by the urgent demand of remote sensing big data management and knowledge discovery, large-scale remote sensing image retrieval (LSRSIR) has attracted more and more attention. As is well known, hashing learning has played an important role in coping with big data mining problems. In the literature, several hashing learning methods have been proposed to address LSRSIR. Until now, existing LSRSIR methods take only one type of feature descriptor as the input of hashing learning methods and ignore the complementary effects of multiple features, which may represent remote sensing images from different aspects. Different from the existing LSRSIR methods, this paper proposes a flexible multiple-feature hashing learning framework for LSRSIR, which takes multiple complementary features as the input and learns the hybrid feature mapping function, which projects multiple features of the remote sensing image to the low-dimensional binary (i.e., compact) feature representation. Furthermore, the compact feature representations can be directly utilized in LSRSIR with the aid of the hamming distance metric. In order to show the superiority of the proposed multiple feature hashing learning method, we compare the proposed approach with the existing methods on two publicly available large-scale remote sensing image datasets. Extensive experiments demonstrate that the proposed approach can significantly outperform the state-of-the-art approaches

A Framework for Assessing Resilience in Urban Mobility: Incorporating Impact of Ridesharing

To a certain degree, the resilience of the transportation system expresses the safety of the transportation system, because it reflects the ability of the system to maintain its function in the face of disturbance events. In the current research, the assessment of the resilience of urban mobility is attractive and challenging. Apart from this, the concept of green mobility has been popular in recent years. As a representative way of shared mobility, the implementation of ridesharing will affect the level of urban mobility resilience to a certain extent. In this paper, we use a data low-intensity method to evaluate the urban traffic resilience under the circumstance of restricted car use. In addition, we incorporate the impact of ridesharing services. The research in this paper can be regarded as an evaluation framework, which can help policy makers and relevant operators to grasp the overall resilience characteristics of cities in emergencies, identify weak sectors, and formulate the best response plan. This method has been successfully applied to two cities in China, demonstrating its potential for practice. Finally, we also explored the relationship between urban traffic resilience and the pattern of population distribution. The analysis shows that population density has an impact on the level of transportation resilience. And the incorporation of ridesharing will bring an obvious increment in resilience of most areas

A novel head network and group normalisation help track more accurately

Abstract Most existing Siamese Network trackers rely on a predefined anchor box to predict object position. However, they require complicated hyperparameter settings. The authors directly forecast the object boundary by using the fully convolutional network as the head of the tracking network to solve this issue and simplify the application. The end‐to‐end design avoids the setting of hyperparameters and candidate boxes. The authors also discovered that the validation loss decreased less than the training loss throughout Siamese training. The authors changed the normalisation layer from batch normalisation to group normalisation to solve this issue. It solved the problem that the loss function is difficult to decrease and increased training efficiency. Test experiments on the tracking dataset, including VOT2019 and GOT10k, show that the authors’ network outperforms DaSiamRPN and SiamFC regarding precision under the same network size and runs at 24 FPS on an AMD 4800 CPU. It also runs at 306 FPS on a 3090 GPU

Preparation and performance study of sedum multiceps-like biomimetic structure TKX-50 with various particle sizes

Biomimetic structures often endow materials with excellent performance. In order to explore the impact of biomimetic structures on the performance of energetic materials, the sedum multiceps-like bionic structure dihydroxylammonium 5,5′-bistetrazole-1,1′-diolate (TKX-50) was constructed by self-assembly technology, and controllable particle size adjustment was achieved. Moreover, the effects of solvent ratio, solute content, stirring flow field, and temperature on the quality of sedum multiceps-like TKX-50 crystals were explored, and the formation mechanism of sedum multiceps-like TKX-50 crystals was analyzed. Then, the crystal morphology, crystal form and particle size distribution of sedum multiceps-like TKX-50 were characterized, furthermore, the thermal properties and mechanical sensitivity of sedum multiceps-like TKX-50 were emphatically studied. The results showed that the sedum multiceps-like biomimetic structure TKX-50 was assembled from needle shaped or sheet shaped small particle crystals, and the sedum multiceps-like structure did not change the explosive crystal form of TKX-50. What's more, the thermal decomposition activation energy of the prepared sedum multiceps-like TKX-50 crystal was at least 157.30 kJ⋅mol−1 and at most 185.27 kJ⋅mol−1, and the thermal energy was greatly affected by particle size. In addition, the minimum and maximum ultimate impact energy of the sedum multiceps-like TKX-50 crystals are 20 J and 55 J. The ultimate impact energy of the sedum multiceps-like TKX-50 crystal with different particle sizes is higher than that of the raw TKX-50 (15 J). As a consequence, the sedum multiceps-like bionic structure effectively improves the energy release of TKX-50, reduces the impact sensitivity, and improves the uniformity of particle size distribution

Optimization of Transport Performance and Strength of the Filling Slurry in Tailings Reservoir Waste by Adding Air Entraining Agent

At present, many mines adopt the filling method. It is particularly important to solve the problem of the long-distance transportation of slurry during the filling process. Based on the high-density filling material of Sanning mine, the experiments were designed to add sodium abietate (SA), triterpene saponin (SJ) and sodium dodecyl sulfonate (K12) with concentrations of 0.0%, 0.2%, 0.4% and 0.6%, respectively, which were used as air entraining agents (AEA). The filling body with the curing age of 7 and 28 days was prepared for various tests, including nuclear magnetic resonance (NMR), and alternating current (AC) impedance tests. The effects of the air entraining agent and curing time on the physical properties, pore structure and AC impedance properties of the filling were obtained. The results show that: (1) within the frequency range of 10−1–105 Hz, the variation trend of AC impedance of the filling body cannot be changed by adding the air entraining agent, and the filling body with the same ratio had a similar topological structure. (2) The filling body with different AEA and curing times can be represented by the same equivalent circuit model, while the maximum chi-square coefficient was 0.46%. (3) Under the condition of a high frequency of 105 Hz, the porosity and uniaxial compressive strength of the filling body with 7 day curing age were linearly correlated with the AC impedance. However, the porosity and uniaxial compressive strengths of the filling body with 28 days curing time were affected by the type of AEA at a high frequency of 105 Hz

Effects of Dietary Koumine on Growth Performance, Intestinal Morphology, Microbiota, and Intestinal Transcriptional Responses of <i>Cyprinus carpio</i>

Gelsemium elegans Benth. (GEB) is a traditional medicinal plant in China, and acts as a growth promoter in pigs and goats. Koumine (KM) is the most abundant alkaloid in GEB and produces analgesic, anti-cancer, and immunomodulatory effects. KM can be used as an aquatic immune stimulant, but its growth-promoting effects and transcriptional mechanisms have not been investigated. Diets containing KM at 0, 0.2, 2, and 20 mg/kg were fed to Cyprinus carpio for 71 days to investigate its effects on growth performance, intestinal morphology, microflora, biochemical indicators, and transcriptional mechanisms. Cyprinus carpio fed with KM as the growth promoter, and the number of intestinal crypts and intestinal microbial populations were influenced by KM concentration. KM increased the abundance of colonies of Afipia, Phyllobacterium, Mesorhizobium, and Labrys, which were associated with compound decomposition and proliferation, and decreased the abundance of colonies of pathogenic bacteria Methylobacterium-Methylorubrum. A total of 376 differentially-expressed genes (DEGs) among the four experimental groups were enriched for transforming growth factor-β1 and small mother against decapentaplegic (TGF-β1/Smad), mitogen-activated protein kinase (MAPK), and janus kinases and signal transducers and activators of transcription (Jak/Stat) signaling pathways. In particular, tgfbr1, acvr1l, rreb-1, stat5b, smad4, cbp, and c-fos were up-regulated and positively correlated with KM dose. KM had a growth-promoting effect that was related to cell proliferation driven by the TGF-β1/Smad, MAPK, and Jak/Stat signaling pathways. KM at 0.2 mg/kg optimized the growth performance of C. carpio, while higher concentrations of KM (2 and 20 mg/kg) may induce apoptosis without significantly damaging the fish intestinal structure. Therefore, KM at low concentration has great potential for development as an aquatic growth promotion additive

Noncovalent Interactions and Crystal Structure Prediction of Energetic Materials

The crystal and molecular structures, intermolecular interactions, and energy of CL-20, HATO, and FOX-7 were comparatively predicted based on molecular dynamic (MD) simulations. By comparison, the 2D fingerprint plot, Hirshfeld surface, reduced density gradient isosurface, and electrostatic potential surface were studied to detect the intermolecular interactions. Meanwhile, the effects of vacuum and different solvents on the crystal habit of CL-20, HATO, and FOX-7 were studied by AE and MAE model, respectively. The energy calculation was also analysed based on the equilibrium structures of these crystal models by MD simulations. Our results would provide fundamental insights for the crystal engineering of energetic materials