Risk factors for chest infection in acute stroke: a prospective cohort study

<p><b>Background and Purpose:</b> Pneumonia is a major cause of morbidity and mortality after stroke. We aimed to determine key characteristics that would allow prediction of those patients who are at highest risk for poststroke pneumonia.</p> <p><b>Methods:</b> We studied a series of consecutive patients with acute stroke who were admitted to hospital. Detailed evaluation included the modified National Institutes of Health Stroke Scale; the Abbreviated Mental Test; and measures of swallow, respiratory, and oral health status. Pneumonia was diagnosed by set criteria. Patients were followed up at 3 months after stroke.</p> <p><b>Results:</b> We studied 412 patients, 391 (94.9%) with ischemic stroke and 21 (5.1%) with hemorrhagic stroke; 78 (18.9%) met the study criteria for pneumonia. Subjects who developed pneumonia were older (mean±SD age, 75.9±11.4 vs 64.9±13.9 years), had higher modified National Institutes of Health Stroke Scale scores, a history of chronic obstructive pulmonary disease, lower Abbreviated Mental Test scores, and a higher oral cavity score, and a greater proportion tested positive for bacterial cultures from oral swabs. In binary logistic-regression analysis, independent predictors (P<0.05) of pneumonia were age >65 years, dysarthria or no speech due to aphasia, a modified Rankin Scale score ≥4, an Abbreviated Mental Test score <8, and failure on the water swallow test. The presence of 2 or more of these risk factors carried 90.9% sensitivity and 75.6% specificity for the development of pneumonia.</p> <p><b>Conclusions:</b> Pneumonia after stroke is associated with older age, dysarthria/no speech due to aphasia, severity of poststroke disability, cognitive impairment, and an abnormal water swallow test result. Simple assessment of these variables could be used to identify patients at high risk of developing pneumonia after stroke.</p&gt

Environmental monitoring of Mycobacterium bovis in badger feces and badger sett soil by real-time PCR, as confirmed by immunofluorescence, immunocapture, and cultivation

Real-time PCR was used to detect and quantify Mycobacterium bovis cells in naturally infected soil and badger faeces. Immunomagnetic capture, immunofluorescence and selective culture confirmed species identification and cell viability. These techniques will prove useful for monitoring M. bovis in the environment and for elucidating transmission routes between wildlife and cattle

When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy

In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect the privacy of location information. For this purpose, people should know their location privacy preferences, that is, whether or not he/she can release location information at each place and time. However, it is not easy for each user to make such decisions and it is troublesome to set the privacy preference at each time. Therefore, we propose a method to recommend location privacy preferences for decision making. Comparing to existing method, our method can improve the accuracy of recommendation by using matrix factorization and preserve privacy strictly by local differential privacy, whereas the existing method does not achieve formal privacy guarantee. In addition, we found the best granularity of a location privacy preference, that is, how to express the information in location privacy protection. To evaluate and verify the utility of our method, we have integrated two existing datasets to create a rich information in term of user number. From the results of the evaluation using this dataset, we confirmed that our method can predict location privacy preferences accurately and that it provides a suitable method to define the location privacy preference

Gametogenic Cycle in the Non-Native Atlantic Surf Clam, Spisula solidissima (Dillwyn, 1817), Cultured in the Coastal Waters of Georgia

This study describes the gametogenic cycle of the Atlantic surf clam, Spisula solidissima (Dillwyn, 1817), cultured from fall to spring in the coastal waters of Georgia, where it is non-native. Early active stages of gametogenic development began in November, with the majority (83%) of the animals in the early active stage by December. Gonadal indices increased to late active stages by March, with ripe individuals present in April. Spawning commenced in May and continued into June. Sex ratio (0.48 female to 1.00 male) was significantly unequal. Results of this study indicate that clams achieved sexual maturity and spawned when cultured in the coastal waters of Georgia. An aquacultural enterprise in Georgia could obtain broodstock for the production of the following fall\u27s seed crop from the prior year\u27s growout field planted clams before their spring harvest

Gametogenic Cycle in the Non-Native Atlantic Surf Clam, Spisula solidissima (Dillwyn, 1817), Cultured in the Coastal Waters of Georgia

This study describes the gametogenic cycle of the Atlantic surf clam, Spisula solidissima (Dillwyn, 1817), cultured from fall to spring in the coastal waters of Georgia, where it is non-native. Early active stages of gametogenic development began in November, with the majority (83%) of the animals in the early active stage by December. Gonadal indices increased to late active stages by March, with ripe individuals present in April. Spawning commenced in May and continued into June. Sex ratio (0.48 female to 1.00 male) was significantly unequal. Results of this study indicate that clams achieved sexual maturity and spawned when cultured in the coastal waters of Georgia. An aquacultural enterprise in Georgia could obtain broodstock for the production of the following fall\u27s seed crop from the prior year\u27s growout field planted clams before their spring harvest

Performance of an environmental test to detect Mycobacterium bovis infection in badger social groups

A study by Courtenay and others (2006) demonstrated that the probability of detecting Mycobacterium bovis by PCR in soil samples from the spoil heaps of main badger setts correlated with the prevalence of excretion (infectiousness) of captured badgers belonging to the social group. It has been proposed that such a test could be used to target badger culling to setts containing infectious animals (Anon 2007). This short communication discusses the issues surrounding this concept, with the intention of dispelling any misconceptions among relevant stakeholders (farmers, policy makers and conservationists)

Threshold Effect In Mg-doped Lithium Niobate

Optical absorption spectra were obtained after reducing (i.e., vacuum annealing) a series of LiNbO3 crystals grown from melts having various Mg concentrations and Li/Nb ratios. A band peaking at 500 nm, and assigned to oxygen vacancies containing two electrons, was the only absorption present in one set of crystals following reduction. In contrast, two overlapping bands peaking near 1200 and 760 nm were present in the other set of crystals immediately after the reduction. The 1200-nm band is assigned to a previously unreported electron trap and the 760-nm band to oxygen vacancies containing only one electron. These data are interpreted in terms of a threshold level for Mg doping; however, the threshold Mg doping level is not a constant but depends on the ratio of Mg ions to Li vacancies

Security Evaluation of Support Vector Machines in Adversarial Environments

Support Vector Machines (SVMs) are among the most popular classification techniques adopted in security applications like malware detection, intrusion detection, and spam filtering. However, if SVMs are to be incorporated in real-world security systems, they must be able to cope with attack patterns that can either mislead the learning algorithm (poisoning), evade detection (evasion), or gain information about their internal parameters (privacy breaches). The main contributions of this chapter are twofold. First, we introduce a formal general framework for the empirical evaluation of the security of machine-learning systems. Second, according to our framework, we demonstrate the feasibility of evasion, poisoning and privacy attacks against SVMs in real-world security problems. For each attack technique, we evaluate its impact and discuss whether (and how) it can be countered through an adversary-aware design of SVMs. Our experiments are easily reproducible thanks to open-source code that we have made available, together with all the employed datasets, on a public repository.Comment: 47 pages, 9 figures; chapter accepted into book 'Support Vector Machine Applications