Improvements on handling design errors in communication protocols.

With the rapid development of the Internet and distributed systems, communication protocols play a more and more important role. The correctness of the design of these communication protocols becomes crucial especially when critical applications are concerned. Common logical design errors in communication protocols include deadlock states, unspecified receptions, channel overflow, non-executable transitions, etc. Such design errors can be removed via protocol synthesis, or be detected through reachability analysis. The former may introduce more states and transitions than needed and the latter suffers from state space explosion problem. Here we present an improvement on existing technique to transform a protocol design into a deadlock-free one where the number of introduced new states and transitions can be considerably reduced. We also propose a sound reduction technique on a class of protocol designs to significantly reduce their sizes in order to perform reachability analysis.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .D83. Source: Masters Abstracts International, Volume: 44-03, page: 1399. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Testing in context: Efficiency and executability

Testing each software component in isolation is not always feasible. We consider testing a deterministic Implementation Under Test (IUT) together with some other correctly implemented components as its context. One of the essential issues of testing in context is test executability problem, i.e., tests generated solely from the specification of the IUT may not be executable due to the uncontrollable interaction between the IUT and its context. On the other hand, generating a test sequence from the abstract specifications of a stateful IUT and its context often suffers from the well-known state explosion problem. In this dissertation, we solve the problem of generating a minimal-length test sequence from a given specification of a stateful IUT and its embedded context. By adopting model checking techniques, we avoid the state explosion problem during test generation and avoid the test executability problem during testing in context

The Role of IL-33 in Rheumatic Diseases

Interleukin-33 (IL-33), a novel member of IL-1 family, has been recently implicated in several inflammatory and autoimmune diseases. IL-33 can be produced by various types of tissues and cells and induce gene expression of Th2-associated cytokines via binding to the orphan receptor ST2. By promoting Th2 type immune response, IL-33 plays important roles in the allergy, whereas its function in autoimmune diseases attracts more attention. Recent studies reported the correlation of IL-33 with rheumatic diseases, and most of them found that the IL-33 expression levels were consistent with disease activity and development. Furthermore, evidence has indicated that IL-33-related treatment may ameliorate the pathogenic conditions and attenuate disease progression of those rheumatic diseases. Therefore, elucidation of the roles of IL-33 in rheumatic diseases would be beneficial to understand the pathogenesis and therapy of these diseases. In this paper, we will summarize the roles of IL-33 in the rheumatic diseases

VNE solution for network differentiated QoS and security requirements: from the perspective of deep reinforcement learning

The rapid development and deployment of network services has brought a series of challenges to researchers. On the one hand, the needs of Internet end users/applications reflect the characteristics of travel alienation, and they pursue different perspectives of service quality. On the other hand, with the explosive growth of information in the era of big data, a lot of private information is stored in the network. End users/applications naturally start to pay attention to network security. In order to solve the requirements of differentiated quality of service (QoS) and security, this paper proposes a virtual network embedding (VNE) algorithm based on deep reinforcement learning (DRL), aiming at the CPU, bandwidth, delay and security attributes of substrate network. DRL agent is trained in the network environment constructed by the above attributes. The purpose is to deduce the mapping probability of each substrate node and map the virtual node according to this probability. Finally, the breadth first strategy (BFS) is used to map the virtual links. In the experimental stage, the algorithm based on DRL is compared with other representative algorithms in three aspects: long term average revenue, long term revenue consumption ratio and acceptance rate. The results show that the algorithm proposed in this paper has achieved good experimental results, which proves that the algorithm can be effectively applied to solve the end user/application differentiated QoS and security requirements

Theoretical study on structural properties and 4f 5d transitions of locally charge-compensated Ce3+ in CaF2

Reprinted with permission from Ning, L., Wu, C.,Li, L., Lin,L., Duan, C., Zhang, Y. and Luis Seijo. "Theoretical study on structural properties and 4f 5d transitions of locally charge-compensated Ce3+ in CaF2". The Journal of Physical Chemistry C 116.34 (2012): 18419-18426.The structural properties and 4f → 5d transitions of Ce3+ in CaF2, with local charge compensation by an interstitial fluoride (Fi ′) or an oxygen substitution for fluoride (OF′), have been studied using the density functional theory (DFT) within the supercell model and the wave function-based embedded cluster calculations, respectively. The DFT results indicate that the incorporation of locally charge-compensated Ce3+ in CaF2 induces an anisotropic distortion of the structure around the dopant site. On the basis of the DFToptimized structures, the Ce-centered embedded clusters are constructed, on which the wave function-based CASSCF/CASPT2/ RASSI−SO calculations at the spin−orbit level are performed to obtain the Ce3+ 4f1 and 5d1 level energies. The calculated 4f−5d transition energies and relative intensities are in good agreement with available experimental results. From the present calculations, we conclude that the 5d1 level missing in the low-temperature absorption spectrum of the tetragonal Ce center with Fi ′ compensation is the second-lowest one, and the absorption at this level is overshadowed by an adjacent cluster band usually assigned to Ce clusters and thus was not observed in experiments. We also assign the two closely spaced absorption lines around 3118.5 Å observed in experiments to the lowest two quasi-degenerated 4f → 5d transitions of the monoclinic center with Fi ′ compensation rather than those of the trigonal center as proposed earlier. Finally, we analyze the structural and electronic reasons for the large reduction (∼2000 cm−1 ) of the lowest 4f → 5d transition energy from a Fi ′ to a nearest-neighbor OF′ compensation, in terms of the changes in the centroid energy difference and crystal- field splittingThis work was supported by the NSFC (Grants 11174005, 11074315, 90922022, and 10804001) and the Program for Innovative Research Teams in Anhui Normal University of China. L.S. acknowledges support from MEC-Spain (Grant MAT2011-24586

LRBmat: A Novel Gut Microbial Interaction and Individual Heterogeneity Inference Method for Colorectal Cancer

Many diseases are considered to be closely related to the changes in the gut microbial community, including colorectal cancer (CRC), which is one of the most common cancers in the world. The diagnostic classification and etiological analysis of CRC are two critical issues worthy of attention. Many methods adopt gut microbiota to solve it, but few of them simultaneously take into account the complex interactions and individual heterogeneity of gut microbiota, which are two common and important issues in genetics and intestinal microbiology, especially in high-dimensional cases. In this paper, a novel method with a Binary matrix based on Logistic Regression (LRBmat) is proposed to deal with the above problem. The binary matrix can directly weakened or avoided the influence of heterogeneity, and also contain the information about gut microbial interactions with any order. Moreover, LRBmat has a powerful generalization, it can combine with any machine learning method and enhance them. The real data analysis on CRC validates the proposed method, which has the best classification performance compared with the state-of-the-art. Furthermore, the association rules extracted from the binary matrix of the real data align well with the biological properties and existing literatures, which are helpful for the etiological analysis of CRC. The source codes for LRBmat are available at https://github.com/tsnm1/LRBmat

Electronic properties and 4f→ 5d transitions in Ce-doped Lu2SiO5: a theoretical investigation

This is an electronic version of an article published in Journal of Materials Chemistry. Ning, L., Lin, L., Li, L., Wu, C., Duan, C., Zhang, Y. and Luis Seijo. "Electronic properties and 4f 5d transitions in Ce-doped Lu2SiO5: a theoretical investigation". Journal of Materials Chemistry 22 (2012): 13723-1373

Peptide-fluorescent bacteria complex as luminescent reagents for cancer diagnosis

Currently in clinic, people use hematoxylin and eosin stain (H&E stain) and immunohistochemistry methods to identify the generation and genre of cancers for human pathological samples. Since these methods are inaccurate and time consuming, developing a rapid and accurate method to detect cancer is urgently demanded. In our study, binding peptides for lung cancer cell line A549 were identified using bacteria surface display method. With those binding peptides for A549 cells on the surface, the fluorescent bacteria (Escherichia coli with stably expressed green fluorescent protein) were served as specific detecting reagents for the diagnosis of cancers. The binding activity of peptide-fluorescent bacteria complex was confirmed by detached cancer cells, attached cancer cells and mice tumor xenograft samples. A unique fixation method was developed for peptide-bacteria complex in order to make this complex more feasible for the clinic use. This peptide-fluorescent bacteria complex has great potential to become a new diagnostic tool for clinical application

Alpha2B-Adrenergic Receptor Regulates Neutrophil Recruitment in MSU-Induced Peritoneal Inflammation

Gout is one of the most common metabolic disorders in human. Previous studies have shown that the disease activity is closely associated with sympathetic nervous system (SNS). α2B-adrenergic receptor (α2BAR), a subtype of α2 adrenergic receptor, plays a critical role in many diseases. However, the role of α2BAR in the pathogenesis of gout remains unclear. Here, we assessed the role of α2BAR in the monosodium urate (MSU) crystals-induced peritonitis that mimics human gout by using the α2BAR-overexpressing mice (α2BAR-Tg). We found that the number of recruited neutrophils was significantly increased in the α2BAR-Tg mice after MSU treatment, when compared with wild type mice. In contrast, the number of macrophages was not changed. Importantly, there is no difference in the IL-1β levels and caspase-1 activity between wild type and α2BAR-Tg mice in the gout animal model. Notably, the enhanced neutrophil migration in α2BAR-Tg mice was dependent on the α2BAR overexpression in neutrophils, but not resulted from other tissues or cells with α2BAR overexpression. In conclusion, our data provide a direct evidence that α2BAR plays a critical role in neutrophil migration and MSU-induced inflammation

C1ql4 regulates breast cancer cell stemness and epithelial-mesenchymal transition through PI3K/AKT/NF-κB signaling pathway

BackgroundThe stemness characteristic of breast cancer (BC) is a crucial factor underlying cancer recurrence and metastasis after operative therapy and chemoradiotherapy. Understanding the potential mechanism of breast cancer stem cells (BCSCs) may ameliorate the prognosis of patients.MethodsWe collected clinical specimens of BC patients for staining and statistical analysis to verify the expression status and clinical significance of complement C1q-like 4 (C1ql4). Western blot and qRT-PCR were employed to detect the expression of molecules. Flow cytometry was used to examine cell cycle, cell apoptosis and the portion of BCSCs. Wound healing and Transwell assays were used to detect cell metastasis. The effect of C1ql4 on breast cancer progression in vivo was examined in a nude mouse tumor bearing model.ResultsOur clinical analysis showed that C1ql4 was highly expressed in BC tissues and cell lines, and the high expression of C1ql4 was significantly corelated with the malignancy of BC patients. Moreover, we also found that C1ql4 was overexpressed in BCSCs. C1ql4 knockdown suppressed the BCSC and EMT properties, promoted cell cycle progression, enhanced BC cell apoptosis, and inhibited cell migration and invasion, whereas the C1ql4 overexpression exhibited the opposite effects. Mechanistically, C1ql4 promoted the activation and nuclear location of NF-κB and the expression of downstream factors TNF-α and IL-1β. Moreover, inhibition of PI3K/AKT signaling suppressed the C1ql4-induced stemness and EMT.ConclusionsOur findings suggest that C1ql4 promotes the BC cell stemness and EMT via modulating the PI3K/AKT/NF-κB signaling, and provides a promising target for BC treatment