E1E_1-degeneration and d′d′′d'd''-lemma

For a double complex $(A, d', d'')$, we show that if it satisfies the $d'd''$-lemma and the spectral sequence $\{E^{p, q}_r\}$ induced by $A$ does not degenerate at $E_0$, then it degenerates at $E_1$. We apply this result to prove the degeneration at $E_1$ of a Hodge-de Rham spectral sequence on compact bi-generalized Hermitian manifolds that satisfy a version of $d'd''$-lemma

A design of Personal Information Push-Delivery System on the Internet

The Internet provides a powerful disseminative ability for users to acquire information more efficiently and quickly. However, an increasingly large scale of data induces certain problems as users face a more serious information overload situation. By using an information retrieval technique, information push-delivery provides a good solution for users to acquire rich information from the Internet. In fact, providing personal service for users is one of the mo st important issues in an electronic commerce (EC) environment. In order to increase interaction between themselves and customers, many enterprises provide personal services to improve management performance and competitiveness. However, since the customers have different preferences for information received from the Internet, it seems necessary to design a personal information system to guarantee that the customers can receive the desired information. In this study, the fuzzy retrieval and similarity measurement techniques are applied to design a personal information push-delivery system. The data resulting from testing a group of students at Da-Yeh University, Changhua, Taiwan, shows that the satisfaction degree for the received information for all participants was 70%. These results indicate that the proposed system can effectively provide correct and interesting information to users

FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation

Over the past few years, we have witnessed the success of deep learning in image recognition thanks to the availability of large-scale human-annotated datasets such as PASCAL VOC, ImageNet, and COCO. Although these datasets have covered a wide range of object categories, there are still a significant number of objects that are not included. Can we perform the same task without a lot of human annotations? In this paper, we are interested in few-shot object segmentation where the number of annotated training examples are limited to 5 only. To evaluate and validate the performance of our approach, we have built a few-shot segmentation dataset, FSS-1000, which consists of 1000 object classes with pixelwise annotation of ground-truth segmentation. Unique in FSS-1000, our dataset contains significant number of objects that have never been seen or annotated in previous datasets, such as tiny daily objects, merchandise, cartoon characters, logos, etc. We build our baseline model using standard backbone networks such as VGG-16, ResNet-101, and Inception. To our surprise, we found that training our model from scratch using FSS-1000 achieves comparable and even better results than training with weights pre-trained by ImageNet which is more than 100 times larger than FSS-1000. Both our approach and dataset are simple, effective, and easily extensible to learn segmentation of new object classes given very few annotated training examples. Dataset is available at https://github.com/HKUSTCV/FSS-1000

Acute aortic dissection mimicking as ureteral calculus

AbstractAcute aortic dissection is an uncommon but life-threatening emergency, which is often missed in up to 38% of patients on initial evaluation, and in up to 28% of patients the diagnosis is made at autopsy. Painless aortic dissection has been reported, but is relatively uncommon. The mortality rates are estimated at 50% by 48 hours and increase by 1% per hour if undiagnosed. We report a case of atypical aortic dissection who presented to ER with subtle unspecific renal colicky like pain as a primary symptom, which had made the prompt diagnosis very challenging and difficult

Polysaccharides obtained from mycelia of Cordyceps militaris attenuated doxorubicin-induced cytotoxic effects in chemotherapy

Objectives: Fungus Cordyceps militaris has been used as a herbal tonic in traditional Chinese medicine, which could be surface liquid-cultured for mycelia production. To evaluate the potential of polysaccharides obtained from mycelia of Cordyceps militaris (PS-MCM) for attenuation of side-effects of chemotherapy.Methods: Doxorubicin was used to induce cytotoxicity in THP-1 monocytes and EL-4 T cells, and the effects of PS-MCM on cell viability and cytokine production were detected on doxorubicin-treated THP-1 and EL-4 cells.Results: PS-MCM reduced doxorubicin-induced cell death and promoted cell proliferation in THP-1 and EL-4 cells. Moreover, PS-MCM elevated the level of cytokines associated with immune-modulation of THP-1 and EL-4 cells.Conclusion: These findings indicate that PS-MCM has potential for development as a functional food to counteract side effects of chemotherapy.Keywords: Cordyceps militaris, traditional Chinese medicine, doxorubicin, chemotherapy, immunotherapy

A user preference perception model using data mining on a Web-based Environment

In a competitive environment, how to provide the information and products to meet the requirements of customers and improve the customer satisfaction will be the key criteria to measure a company’s competitiveness. Customer Relationship Management (CRM) becomes an important issue in any business market gradually. Using information technology, businesses can achieve their requirements for one to one marketing more efficiently with lower cost, labor and time. In this paper, we proposed a user preference perception model by using data mining technology on a web-based environment. First, the users’ web browse records are aggregated. Second, fuzzy set theory and most sequential pattern mining algorithm are used to infer the users’ preference changes in a period. After the test had processed, we use the on-line questionnaire to investigate the customer satisfaction degree from all participators. The results show that the degree of satisfaction was up to 72% for receiving the new information of participants whose preferences had been changed. It indicates that the proposed system can effectively perceive the change of preference for users on a web environment

Prescription Patterns of Chinese Herbal Products for Osteoporosis in Taiwan: A Population-Based Study

Background. Traditional Chinese medicine (TCM) includes Chinese herbal products (CHPs), acupuncture, and traumatology manipulative therapies. TCM physicians often prescribe CHP to treat patients with osteoporosis; however, the drugs used and their patterns of prescriptions have yet to be characterized. This study, therefore, aimed to evaluate the CHP used for the treatment of osteoporosis in Taiwan and their prescription patterns. Methods. A cohort of one million randomly sampled cases from the National Health Insurance Research Database (NHIRD) was analyzed to evaluate the frequencies and percentages of herbal formula and single herb prescriptions for osteoporosis. Association rules were then applied to evaluate the CHP coprescription patterns and the prevalence of osteoporosis. Results. The osteoporosis cohort included 16 544 patients, of whom more than 70% had used TCM on one or more occasion. Of these patients, 4 292 (25.9%) had been hospitalized at least once because of fracture. Du-Huo-Ji-Sheng-Tang and Du Zhong (Cortex Eucommiae) were the most frequently prescribed herbal formula and single herb, respectively, for the treatment of osteoporosis. Conclusion. This study identified patterns of CHP use for the treatment of osteoporosis. However, further research is required to fully elucidate the efficacy and safety of these CHP