582 research outputs found
Tuberculous abdominal abscess in an HIV-infected man: neither infection previously diagnosed
A 38-year-old man had a 1-week history of right lower quadrant abdominal pain; the initial impression was that he had diverticulitis of the ascending colon with an intra-abdominal abscess. Signs of peritonitis mandated an immediate right hemicolectomy. The unusual location of the abscess and the patient’s unusual postoperative course suggested that he might also have a systemic disease. Testing for HIV infection was positive. After 2 weeks in hospital, he was treated as an outpatient for both tuberculosis and HIV with a favourable outcome. In Taiwan a pre-operative HIV test is not performed routinely, and the HIV seroprevalence in surgical patient populations is unknown. Surgeons should keep the possibility of HIV infection in mind in a patient with an unusual clinical course
Comparing two-phase locking and optimistic concurrency control protocols in multiprocessor real-time databases
Previous studies (Haritsa et al., 1990) have shown that optimistic concurrency control (OCC) generally performs better than lock-based protocols in disk-based real-time database systems (RTDBS). We compare the two concurrency control protocols in both disk-based and memory-resident multiprocessor RTDBS. Based on their performance characteristics, a new lock-based protocol, called two phase locking-lock write all (2PL-LW), is proposed. The results of our performance evaluation experiments show that different characteristics of the two environments indeed have great impact on the protocols' performance. We identify such system characteristics and show that our new lock-based protocols, 2PL-LW, is better than OCC in meeting transaction deadlines in both disk-based and memory-resident RTDBS.published_or_final_versio
Methionine aminopeptidase as a novel Target for antibiotic therapy against staphylococcus aureus: a proteomic approach
Key Messages
1. Methionine aminopeptidase (MetAP) is an essential enzyme in Staphylococcus aureus and
a potential target for novel antibiotics.
2. Two-dimensional electrophoresis gel identified more than 100 differences in protein expression between wild type and MetAP-deficient strains of S aureus.
3. Using mass spectroscopic techniques, 63 differentially expressed proteins were identified, of which some were related to purine biosynthesis and methionine metabolism.published_or_final_versio
Maintaining temporal consistency of discrete objects in soft real-time database systems
A real-time database system contains base data items which record and model a physical, real-world environment. For better decision support, base data items are summarized and correlated to derive views. These base data and views are accessed by application transactions to generate the ultimate actions taken by the system. As the environment changes, updates are applied to base data, which subsequently trigger view recomputations. There are thus three types of activities: Base data update, view recomputation, and transaction execution. In a real-time database system, two timing constraints need to be enforced. We require that transactions meet their deadlines (transaction timeliness) and read fresh data (data timeliness). In this paper, we define the concept of absolute and relative temporal consistency from the perspective of transactions for discrete data objects. We address the important issue of transaction scheduling among the three types of activities such that the two timing requirements can be met. We also discuss how a real-time database system should be designed to enforce different levels of temporal consistency.published_or_final_versio
Mining Order-Preserving Submatrices from Data with Repeated Measurements
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Cognitive effects of calligraphy therapy for older people: a randomized controlled trial in Hong Kong
BACKGROUND: This pilot study investigated the effects of calligraphy therapy on cognitive function in older Hong Kong Chinese people with mild cognitive impairment. METHODS: A single-blind, randomized controlled trial was carried out in a sample of 31 adults aged 65 years or older with mild cognitive impairment. They were randomly assigned to receive either intensive calligraphy training led by a trained research assistant for eight weeks (calligraphy group, n = 14) or no calligraphy treatment (control group, n = 17). Participants' cognitive function was assessed by the Chinese version of the Mini-Mental State Examination (CMMSE) before and after calligraphy treatment. Repeated measures analysis of variance and paired samples t-tests were used to analyze the data. RESULTS: A significant interaction effect of time and intervention was detected [F (1, 29) = 9.11, P = 0.005, eta(2) = 0.24]. The calligraphy group was found to have a prominent increase in CMMSE global score, and scores in the cognitive areas of orientation, attention, and calculation after two months (DeltaM = 2.36, P < 0.01), whereas their counterparts in the control group experienced a decline in CMMSE score (DeltaM = -0.41, P < 0.05). CONCLUSION: Calligraphy therapy was effective for enhancing cognitive function in older people with mild cognitive impairment and should be incorporated as part of routine programs in both community and residential care settings. © 2011 Kwok et al, publisher and licensee Dove Medical Press Ltd.published_or_final_versio
A DNA vaccine targeting TcdA and TcdB induces protective immunity against Clostridium difficile
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Decision trees for uncertain data
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/ quantization errors, data staleness, and multiple repeated measurements. With uncertainty, the value of a data item is often represented not by one single value, but by multiple values forming a probability distribution. Rather than abstracting uncertain data by statistical derivatives (such as mean and median), we discover that the accuracy of a decision tree classifier can be much improved if the "complete information" of a data item (taking into account the probability density function (pdf)) is utilized. We extend classical decision tree building algorithms to handle data tuples with uncertain values. Extensive experiments have been conducted which show that the resulting classifiers are more accurate than those using value averages. Since processing pdfs is computationally more costly than processing single values (e.g., averages), decision tree construction on uncertain data is more CPU demanding than that for certain data. To tackle this problem, we propose a series of pruning techniques that can greatly improve construction efficiency. © 2006 IEEE.link_to_subscribed_fulltex
Unraveling the molecular basis of temperature-dependent genetic regulation in Penicillium marneffei
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