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"Song, Rui"
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Business trends in the digital era : evolution of theories and applications
This book introduces 10 mega business trends, ranging from big data to the O2O model. By mining and analyzing mountains of data, the author identifies these 10 emerging trends and goes to great lengths to explain and support his views with up-to-date cases. By incorporating the latest developments, this book allows readers to keep abreast of rapidly advancing digital technologies and business models. In this time of mass entrepreneurship and innovation, acquiring deep insights into business trends and grasping opportunities for innovation give readers (business executives in particular) and their companies a competitive advantage and the potential to become the next success story. The Chinese version of the book has become a hit, with some business schools using it as a textbook for their S & T Innovation and Business Trends programs. It also provides business executives with a practical guide for their investment and operation decisions.
Book
SURE INDEPENDENCE SCREENING IN GENERALIZED LINEAR MODELS WITH NP-DIMENSIONALITY
Ultrahigh-dimensional variable selection plays an increasingly important role in contemporary scientific discoveries and statistical research. Among others, Fan and Lv [J. R. Stat. Soc. Ser. B Stat. Methodol. 70 (2008) 849—911] propose an independent screening framework by ranking the marginal correlations. They showed that the correlation ranking procedure possesses a sure independence screening property within the context of the linear model with Gaussian covariates and responses. In this paper, we propose a more general version of the independent learning with ranking the maximum marginal likelihood estimates or the maximum marginal likelihood itself in generalized linear models. We show that the proposed methods, with Fan and Lv [J. R. Stat. Soc. Ser. B Stat. Methodol. 70 (2008) 849—911] as a very special case, also possess the sure screening property with vanishing false selection rate. The conditions under which the independence learning possesses a sure screening is surprisingly simple. This justifies the applicability of such a simple method in a wide spectrum. We quantify explicitly the extent to which the dimensionality can be reduced by independence screening, which depends on the interactions of the covariance matrix of covariates and true parameters. Simulation studies are used to illustrate the utility of the proposed approaches. In addition, we establish an exponential inequality for the quasi-maximum likelihood estimator which is useful for high-dimensional statistical learning.
Journal Article
Enhancing two-stage object detection models via data-driven anchor box optimization in UAV-based maritime SAR
The high-altitude imaging capabilities of Unmanned Aerial Vehicles (UAVs) offer an effective solution for maritime Search and Rescue (SAR) operations. In such missions, the accurate identification of boats, personnel, and objects within images is crucial. While object detection models trained on general image datasets can be directly applied to these tasks, their effectiveness is limited due to the unique challenges posed by the specific characteristics of maritime SAR scenarios. Addressing this challenge, our study leverages the large-scale benchmark dataset SeaDronesSee, specific to UAV-based maritime SAR, to analyze and explore the unique attributes of image data in this scenario. We identify the need for optimization in detecting specific categories of difficult-to-detect objects within this context. Building on this, an anchor box optimization strategy is proposed based on clustering analysis, aimed at enhancing the performance of the renowned two-stage object detection models in this specialized task. Experiments were conducted to validate the proposed anchor box optimization method and to explore the underlying reasons for its effectiveness. The experimental results show our optimization method achieved a 45.8% and a 10% increase in average precision over the default anchor box configurations of torchvision and the SeaDronesSee official sample code configuration respectively. This enhancement was particularly evident in the model’s significantly improved ability to detect swimmers, floaters, and life jackets on boats within the SeaDronesSee dataset’s SAR scenarios. The methods and findings of this study are anticipated to provide the UAV-based maritime SAR research community with valuable insights into data characteristics and model optimization, offering a meaningful reference for future research.
Journal Article
S100A8/A9 in Inflammation
S100A8 and S100A9 (also known as MRP8 and MRP14, respectively) are Ca
binding proteins belonging to the S100 family. They often exist in the form of heterodimer, while homodimer exists very little because of the stability. S100A8/A9 is constitutively expressed in neutrophils and monocytes as a Ca
sensor, participating in cytoskeleton rearrangement and arachidonic acid metabolism. During inflammation, S100A8/A9 is released actively and exerts a critical role in modulating the inflammatory response by stimulating leukocyte recruitment and inducing cytokine secretion. S100A8/A9 serves as a candidate biomarker for diagnosis and follow-up as well as a predictive indicator of therapeutic responses to inflammation-associated diseases. As blockade of S100A8/A9 activity using small-molecule inhibitors or antibodies improves pathological conditions in murine models, the heterodimer has potential as a therapeutic target. In this review, we provide a comprehensive and detailed overview of the distribution and biological functions of S100A8/A9 and highlight its application as a diagnostic and therapeutic target in inflammation-associated diseases.
Journal Article
Cardiac ECM: Its Epigenetic Regulation and Role in Heart Development and Repair
The extracellular matrix (ECM) is the non-cellular component in the cardiac microenvironment, and serves essential structural and regulatory roles in establishing and maintaining tissue architecture and cellular function. The patterns of molecular and biochemical ECM alterations in developing and adult hearts depend on the underlying injury type. In addition to exploring how the ECM regulates heart structure and function in heart development and repair, this review conducts an inclusive discussion of recent developments in the role, function, and epigenetic guidelines of the ECM. Moreover, it contributes to the development of new therapeutics for cardiovascular disease.
Journal Article
Continuous approximation and GIS-enhanced design optimization of feeder bus networks along rail corridors
As urbanization accelerates, urban public transportation systems are tasked with meeting the growing demand for travel. According to statistics, the regional rail transit network currently handles 60% of the passenger volume for trips originating from around the stations, and this is projected to increase by over 20% within the next decade. However, the current feeder bus services suffer from insufficient coverage, leading to inconvenience for passengers and impacting the overall efficiency of the transportation system. To enhance the public transit service coverage along a rail transit corridor, this study designs feeder bus services to connect the rail stations. A theoretical trunk-feeder transit design problem is firstly solved to furnish the initial feeder bus line designs. The objective is to minimize total generalized system cost with respect to the density of feeder bus routes and their service frequencies. The idealized design of the optimal bus route density function is then discretized into specific locations and fine-tuned with Geographic Information System (GIS) tool. Considering local conditions like road network and demographic information, a four-step adjustment strategy is proposed to furnish the implementation-ready design of feeder bus services. Numerical results show the final design renders at least 3.5% saving in total system cost. This study illustrates how the state-of-the-art theories of transit design can be applied into practice and highlights the connection between theoretical studies and practical application.
Journal Article
Porcine milk-derived exosomes promote proliferation of intestinal epithelial cells
Milk-derived exosomes were identified as a novel mechanism of mother-to-child transmission of regulatory molecules, but their functions in intestinal tissues of neonates are not well-studied. Here, we characterized potential roles of porcine milk-derived exosomes in the intestinal tract.
In vitro
, treatment with milk-derived exosomes (27 ± 3 ng and 55 ± 5 ng total RNA) significantly promoted IPEC-J2 cell proliferation by MTT, CCK8, EdU fluorescence and EdU flow cytometry assays. The qRT-PCR and Western blot analyses indicated milk-derived exosomes (0.27 ± 0.03 μg total RNA) significantly promoted expression of CDX2, IGF-1R and PCNA and inhibited p53 gene expression involved in intestinal proliferation. Additionally, six detected miRNAs were significantly increased in IPEC-J2 cell, while
FAS
and
SERPINE
were significantly down-regulated relative to that in control.
In vivo
, treated groups (0.125 μg and 0.25 μg total RNA) significantly raised mice’ villus height, crypt depth and ratio of villus length to crypt depth of intestinal tissues, significantly increased CDX2, PCNA and IGF-1R’ expression and significantly inhibited p53′ expression. Our study demonstrated that milk-derived exosomes can facilitate intestinal cell proliferation and intestinal tract development, thus giving a new insight for milk nutrition and newborn development and health.
Journal Article
The effect of rice storage on the eating quality
This study investigated the impact of different storage temperatures on the quality of rice during an 11-month storage period. Rice is a crucial staple food, and maintaining its quality during storage is essential for food security. The research focused on moisture content and fatty acid value as key indicators of rice quality. Results showed that low-temperature storage, specifically at 0°C and 10°C, contributed to slower moisture loss and reduced lipid degradation compared to room temperature storage (25°C). This study underscores the significance of low-temperature storage in preserving the quality of rice over time.
Journal Article
Facial Expression Recognition with Fusion Features Extracted from Salient Facial Areas
In the pattern recognition domain, deep architectures are currently widely used and they have achieved fine results. However, these deep architectures make particular demands, especially in terms of their requirement for big datasets and GPU. Aiming to gain better results without deep networks, we propose a simplified algorithm framework using fusion features extracted from the salient areas of faces. Furthermore, the proposed algorithm has achieved a better result than some deep architectures. For extracting more effective features, this paper firstly defines the salient areas on the faces. This paper normalizes the salient areas of the same location in the faces to the same size; therefore, it can extracts more similar features from different subjects. LBP and HOG features are extracted from the salient areas, fusion features’ dimensions are reduced by Principal Component Analysis (PCA) and we apply several classifiers to classify the six basic expressions at once. This paper proposes a salient areas definitude method which uses peak expressions frames compared with neutral faces. This paper also proposes and applies the idea of normalizing the salient areas to align the specific areas which express the different expressions. As a result, the salient areas found from different subjects are the same size. In addition, the gamma correction method is firstly applied on LBP features in our algorithm framework which improves our recognition rates significantly. By applying this algorithm framework, our research has gained state-of-the-art performances on CK+ database and JAFFE database.
Journal Article
Rainstorm waterlogging risk assessment in central urban area of Shanghai based on multiple scenario simulation
With the acceleration of the urbanization process, waterlogging problems in coastal cities are becoming more and more serious due to climate change. However, up until now, the common procedures and programs for rainstorm waterlogging risk assessment in coastal cities still have not formed. Considering a series of impact factors of rainstorm waterlogging in coastal city, the present study established a paradigm for rainstorm waterlogging risk assessment through the combination of hydrological modeling and GIS spatial analysis, and took the residence in central urban area of Shanghai as an example. First, the simplified urban waterlogging model was applied to simulate the depth and extent of rainstorm waterlogging under six hypothetic scenarios. Second, the residence exposed to rainstorm waterlogging was extracted and analyzed supported by spatial analysis module of ArcGIS. Then, stage-damage curves were applied to analyze the loss rate of structure and contents of residential building. Finally, the waterlogging loss maps of residence in different scenarios, the annual average loss, and the risk curve were taken as the expression of waterlogging risk. The results show that the inundated water depth, vulnerability, and losses of residence all increase as the intensity of rainstorm increases. The old-style residence is most vulnerable to rainstorm waterlogging, followed by the new-style residence, and villa is less vulnerable to rainstorm waterlogging. The annual average loss of residence in Shanghai central urban area was about CNY 22.25 million. The results also indicate high risk in Yangpu and Putuo districts, Xuhui, Hongkou, Changning and Zhabei districts come under medium-risk zone, and Jing’an, Luwan and Huangpu districts come under low-risk zone. These results provide important information for the local government, and the methodology can be applied in other cities to provide guidance on waterlogging risk governance.
Journal Article