USING SOCIAL NETWORK ANALYSIS AS A STRATEGY FOR E-COMMERCE RECOMMENDATION

Recommender agents are being widely used by E-commerce business to help customers make decisions from a large amount of choices. To improve the performance of recommendation agents, three main approaches (content-based approaches, collaborative approaches and hybrid approaches) have been proposed to address recommendation problem whose basic idea is to discover similarity of items and users and predicate users’ preference toward a set of items. This provides potential for using social network analysis to make recommendations since social network analysis can be used to investigate the relationships of customers. In this research, we illustrate the concepts of social network analysis and how it can be employed to make better recommendations in E-commerce context. Application and research opportunities are presented

Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network.

Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet) approach, a novel network integration pipeline for herb-target prediction mainly relying on the symptom related associations. HTINet focuses on capturing the low-dimensional feature vectors for both herbs and proteins by network embedding, which incorporate the topological properties of nodes across multi-layered heterogeneous network, and then performs supervised learning based on these low-dimensional feature representations. HTINet obtains performance improvement over a well-established random walk based herb-target prediction method. Furthermore, we have manually validated several predicted herb-target interactions from independent literatures. These results indicate that HTINet can be used to integrate heterogeneous information to predict novel herb-target interactions

Characteristics of CD8+ T cell subsets in Chinese patients with chronic HIV infection during initial ART

<p>Abstract</p> <p>Background</p> <p>CD8+ T cells may play an important role in protecting against HIV. However, the changes of CD8+ T cell subsets during early period of ART have not been fully studied.</p> <p>Methods</p> <p>Twenty-one asymptomatic treatment-naive HIV-infected patients with CD4 T+ cells less than 350 cells/μl were enrolled in the study. Naïve, central memory(CM), effective memory(EM) and terminally differentiated effector (EMRA) CD8+ cell subsets and their activation and proliferation subsets were evaluated in blood samples collected at base line, and week 2, 4, 8 and 12 of ART.</p> <p>Results</p> <p>The total CD8+ T cells declined and the Naïve and CM subsets had a tendency of increase. Activation levels of all CD8+ T cell subsets except EMRA subset decreased after ART. However, proliferation levels of total CD8+ T cells, EMRA, EM and CM subsets increased at the first 4 weeks of ART, then decreased. Proliferation level of the naïve cells decreased after ART.</p> <p>Conclusion</p> <p>The changes of CD8+ T cell subsets during initial ART are complex. Our results display a complete phenotypical picture of CD8+ cell subsets during initial ART and provide insights for understanding of immune status during ART.</p

A novel WebVR-Based lightweight framework for virtual visualization of blood vasculum

With the arrival of the Web 2.0 era and the rapid development of virtual reality (VR) technology in recent years, WebVR technology has emerged as the combination of Web 2.0 and VR. Moreover, the concept of “WebVR + medical science”is also proposed to advance medical applications. However, due to the limited storage space and low computing capability of Web browsers, it is difficult to achieve real-time rendering of large-scale medical vascular models on the Web, let alone large-scale vascular animation simulations. The framework proposed in this paper can achieve virtual display of the medical blood vasculum, including lightweight processing of the vasculum and virtual realization of blood flow. This innovative framework presents a simulation algorithm for the virtual blood path based on the Catmull-Rom spline. The mechanisms of progressive compression and online recovery of the lightweight vascular structure are further proposed. The experimental results show that our framework has a shorter browser-side response time than existing methods and achieves efficient real-time simulation

A new framework for the integrative analytics of intravascular ultrasound and optical coherence tomography images

Abstract:The integrative analysis of multimodal medical images plays an important role in the diagnosis of coronary artery disease by providing additional comprehensive information that cannot be found in an individual source image. Intravascular ultrasound (IVUS) and optical coherence tomography (IV-OCT) are two imaging modalities that have been widely used in the medical practice for the assessment of arterial health and the detection of vascular lumen lesions. IV-OCT has a high resolution and poor penetration, while IVUS has a low resolution and high detection depth. This paper proposes a new approach for the fusion of intravascular ultrasound and optical coherence tomography pullbacks to significantly improve the use of those two types of medical images. It also presents a new two-phase multimodal fusion framework using a coarse-to-fine registration and a wavelet fusion method. In the coarse-registration process, we define a set of new feature points to match the IVUS image and IV-OCT image. Then, the improved quality image is obtained based on the integration of the mutual information of two types of images. Finally, the matched registered images are fused with an approach based on the new proposed wavelet algorithm. The experimental results demonstrate the performance of the proposed new approach for significantly enhancing both the precision and computational stability. The proposed approach is shown to be promising for providing additional information to enhance the diagnosis and enable a deeper understanding of atherosclerosis

Biofilm formation and antibiotic sensitivity in Elizabethkingia anophelis

Elizabethkingia anophelis has recently gained global attention and is emerging as a cause of life-threatening nosocomial infections. The present study aimed to investigate the association between antimicrobial resistance and the ability to form biofilm among E. anophelis isolated from hospitalized patients in China. Over 10 years, a total of 197 non-duplicate E. anophelis strains were collected. Antibiotic susceptibility was determined by the standard agar dilution method as a reference assay according to the Clinical and Laboratory Standards Institute. The biofilm formation ability was assessed using a culture microtiter plate method, which was determined using a crystal violet assay. Culture plate results were cross-checked by scanning electron microscopy imaging analysis. Among the 197 isolates, all were multidrug-resistant, and 20 were extensively drug-resistant. Clinical E. anophelis showed high resistance to current antibiotics, and 99% of the isolates were resistant to at least seven antibiotics. The resistance rate for aztreonam, ceftazidime, imipenem, meropenem, trimethoprim-sulfamethoxazole, cefepime, and tetracycline was high as 100%, 99%, 99%, 99%, 99%, 95%, and 90%, respectively. However, the isolates exhibited the highest susceptibility to minocycline (100%), doxycycline (96%), and rifampin (94%). The biofilm formation results revealed that all strains could form biofilm. Among them, the proportions of strong, medium, and weak biofilm-forming strains were 41%, 42%, and 17%, respectively. Furthermore, the strains forming strong or moderate biofilm presented a statistically significant higher resistance than the weak formers (p &lt; 0.05), especially for piperacillin, piperacillin-tazobactam, cefepime, amikacin, and ciprofloxacin. Although E. anophelis was notoriously resistant to large antibiotics, minocycline, doxycycline, and rifampin showed potent activity against this pathogen. The data in the present report revealed a positive association between biofilm formation and antibiotic resistance, which will provide a foundation for improved therapeutic strategies against E. anophelis infections in the future

HIV associated cell death: Peptide-induced apoptosis restricts viral transmission.

The human immunodeficiency virus (HIV) is still a global pandemic and despite the successful use of anti-retroviral therapy, a well-established cure remains to be identified. Viral modulation of cell death has a significant role in HIV pathogenesis. Here we sought to understand the major mechanisms of HIV- induced death of lymphocytes and the effects on viral transmission. Flow cytometry analysis of lymphocytes from five latent HIV-infected patients, and HIV IIIB-infected MT2 cells demonstrated both necrosis and apoptosis to be the major mechanisms of cell death in CD4+ and CD4-/CD8- lymphocytes. Significantly, pro-apoptotic tumor necrosis factor (TNF) peptide (P13) was found to inhibit HIV-related cell death and reduced viral transmission. Whereas pro-necrotic TNF peptide (P16) had little effect on HIV-related cell death and viral transmission. Understanding mechanisms by which cell death can be manipulated may provide additional drug targets to reduce the loss of CD4+ cells and the formation of a viral reservoir in HIV infection

Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography

Hydraulic tomography (HT) has emerged as a potentially viable method for mapping fractures in geologic media as demonstrated by recent studies. However, most of the studies adopted equivalent porous media (EPM) models to generate and invert hydraulic interference test data for HT. While these models assign significant different hydraulic properties to fractures and matrix, they may not fully capture the discrete nature of the fractures in the rocks. As a result, HT performance may have been overrated. To explore this issue, this study employed a discrete fracture network (DFN) model to simulate hydraulic interference tests. HT with the EPM model was then applied to estimate the distributions of hydraulic conductivity (K) and specific storage (S-s) of the DFN. Afterward, the estimated fields were used to predict the observed heads from DFN models, not used in the HT analysis (i.e., validation). Additionally, this study defined the spatial representative elementary volume (REV) of the fracture connectivity probability for the entire DFN dominant. The study showed that if this spatial REV exists, the DFN is deemed equivalent to EPM and vice versa. The hydraulic properties estimated by HT with an EPM model can then predict head fields satisfactorily over the entire DFN domain with limited monitoring wells. For a sparse DFN without this spatial REV, a dense observation network is needed. Nevertheless, HT is able to capture the dominant fractures.National Science and Technology Major Project of China [2017ZX05008-003-021]; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB10030601]; Youth Innovation Promotion Association of the Chinese Academy of Sciences [2016063]; US Civilain Research and Development Foundation (CRDF) under the award: Hydraulic tomography in shallow alluvial sediments: Nile River Valley, Egypt [DAA2-15-61224-1]; Global Expert award through Tianjin Normal University from the Thousand Talents Plan of Tianjin City6 month embargo; published online: 23 April 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]