SOFTWARE-AS-A-SERVICE (SAAS) INNOVATION IN THE CONTEXT OF SOFTWARE INDUSTRY: A RESOURCE ORCHESTRATION PERSPECTIVE

Cloud computing brings a paradigm shift in the software industry and changes the business model of software vendors (SV). Software as a service (SaaS), the most popular form of cloud computing, has been recognized as the fundamental change in the delivery, utilization, and management of software. While the transformation to SaaS requires changes within the organization, SVs must actively take action to attract customers to accept the SaaS business model, the so-called pull strategy. Drawing on the resource orchestration view, we propose that the antecedents (i.e., structuring cloud resources, developing service bundling capability, and leveraging cloud ecosystem) are related to the likelihood of an innovative SaaS, which, in turn, is associated with SaaS attractiveness to users. Our proposed research framework provides a guideline for SV to attract and persuade customers to adopt SaaS solutions actively

Autoimmunity-related demyelination in infection by Japanese encephalitis virus

Japanese encephalitis (JE) virus is the most common cause of epidemic viral encephalitis in the world. The virus mainly infects neuronal cells and causes an inflammatory response after invasion of the parenchyma of the brain. The death of neurons is frequently observed, in which demyelinated axons are commonly seen. The mechanism that accounts for the occurrence of demyelination is ambiguous thus far. With a mouse model, the present study showed that myelin-specific antibodies appeared in sera, particularly in those mice with evident symptoms. Meanwhile, specific T cells proliferating in response to stimulation by myelin basic protein (MBP) was also shown in these mice. Taken together, our results suggest that autoimmunity may play an important role in the destruction of components, e.g., MBP, of axon-surrounding myelin, resulting in demyelination in the mouse brain after infection with the JE virus

Inflammatory Marker but Not Adipokine Predicts Mortality among Long-Term Hemodialysis Patients

Aims: chronic inflammation contributes significantly to the morbidity and mortality of chronic hemodialysis patients. A recent research has shown that adipokines were associated with inflammation in these patients. We aim to investigate whether biomarkers of inflammation, adipokines, and clinical features can predict the outcome of hemodialysis patients. Materials and methods: we enrolled 181 hemodialysis patients (men: 97, mean age: 56.3±13.6) and analyzed predictors of long-term outcomes. Results: during the 3-year followup period, 41 patients died; the main causes of death were infection and cardiovascular disease. Elevated serum levels of hsCRP and albumin and advanced age were highly associated with death (all P<.001). Leptin and adiponectin levels were not significantly different between deceased patients and survivors. Cox-regression analysis indicated that age, diabetes, albumin level, and hsCRP were independent factors predicting mortality. Conclusion: the presence of underlying disease, advanced age, and markers of chronic inflammation is strongly related to survival rate in long-term hemodialysis patients

Compact Floor-Planning via Orderly Spanning Trees

Floor-planning is a fundamental step in VLSI chip design. Based upon the concept of orderly spanning trees, we present a simple O(n)-time algorithm to construct a floor-plan for any n-node plane triangulation. In comparison with previous floor-planning algorithms in the literature, our solution is not only simpler in the algorithm itself, but also produces floor-plans which require fewer module types. An equally important aspect of our new algorithm lies in its ability to fit the floor-plan area in a rectangle of size (n-1)x(2n+1)/3. Lower bounds on the worst-case area for floor-planning any plane triangulation are also provided in the paper.Comment: 13 pages, 5 figures, An early version of this work was presented at 9th International Symposium on Graph Drawing (GD 2001), Vienna, Austria, September 2001. Accepted to Journal of Algorithms, 200

Bacteremic pneumonia caused by Nocardia veterana in an HIV-infected patient

SummaryDisseminated Nocardia veterana infection has rarely been reported. We describe the first reported case of N. veterana bacteremic pneumonia in an HIV-infected patient. The isolate was confirmed by 16S rRNA sequencing analysis. The patient initially responded well to trimethoprim–sulfamethoxazole treatment (minimum inhibitory concentration 0.25μg/ml), but died of ventilator-associated pneumonia

Image operator learning coupled with CNN classification and its application to staff line removal

Many image transformations can be modeled by image operators that are characterized by pixel-wise local functions defined on a finite support window. In image operator learning, these functions are estimated from training data using machine learning techniques. Input size is usually a critical issue when using learning algorithms, and it limits the size of practicable windows. We propose the use of convolutional neural networks (CNNs) to overcome this limitation. The problem of removing staff-lines in music score images is chosen to evaluate the effects of window and convolutional mask sizes on the learned image operator performance. Results show that the CNN based solution outperforms previous ones obtained using conventional learning algorithms or heuristic algorithms, indicating the potential of CNNs as base classifiers in image operator learning. The implementations will be made available on the TRIOSlib project site.Comment: To appear in ICDAR 201