国产十种乌头的染色体研究

本文描述了我国产毛茛科乌头属的10个种的染色体数目和形态。  根据该属染色体基 数为8(x＝8)，可将这些种归为二倍体、四倍体、六倍体和八倍体种。  10种乌头的染色体在数目、大小、结构上表现出相关性。其中具根状茎而多年生的种多为二倍体，染色体形态较大，第3-7号多为近端着丝点(st)染色体, 具块茎而二年生的种多为多倍体，染色体形态较小，第3-7号多为近中着丝点(sm)染色体。染色体演化方向可能是二倍体→多倍体、大→ 小、st→sm。这进一步证明根状茎种较块茎种原始。根据染色体数目和形态，又可将这些种的染色体分为两类。这进一步支持了目前分类学上的牛扁亚属和乌头亚属的划分。本文还讨论了这些种的有关分类问题。     

Unsupervised word sense disambiguation for Korean through the acyclic weighted digraph using corpus and dictionary

Word sense disambiguation (WSD) is meant to assign the most appropriate sense to a polysemous word according to its context. We present a method for automatic WSD using only two resources: a raw text corpus and a machine-readable dictionary (MRD). The system learns the similarity matrix between word pairs from the unlabeled corpus, and it uses the vector representations of sense definitions from MRD, which are derived based on the similarity matrix. In order to disambiguate all occurrences of polysemous words in a sentence, the system separately constructs the acyclic weighted digraph (AWD) for every occurrence of polysemous words in a sentence. The AWD is structured based on consideration of the senses of context words which occur with a target word in a sentence. After building the AWD per each polysemous word, we can search the optimal path of the AWD using the Viterbi algorithm. We assign the most appropriate sense to the target word in sentences with the sense on the optimal path in the AWD. By experiments, our system shows 76.4% accuracy for the semantically ambiguous Korean words.     

Optimization of some factors affecting the performance of query expansion

This paper examines the factors affecting the performance of global query expansion based on term co-occurrence data and suggests a way to maximize the retrieval effectiveness. Major parameters to be optimized through experiments are term similarity measure and the weighting scheme of additional terms. The evaluation of four similarity measures tested in query expansion reveal that mutual information and Yule's Y, which emphasize low frequency terms, achieve better performance than cosine and Jaccard coefficients that have the reverse tendency. In the evaluation of three weighting schemes, similarity weight performs well only with short queries, whereas fixed weights of approximately 0.5 and similarity rank weights were effective with queries of any length. Furthermore, the optimal similarity rank weight achieving the best overall performance seems to be the least affected by test collections and the number of additional terms. For the efficiency of retrieval, the number of additional terms needs not exceed 70 in our test collections, but the optimal number may vary according to the characteristics of the similarity measure employed.     

Association of Elevated Serum Lipoprotein(a), Inflammation,Oxidative Stress and Chronic Kidney Disease with Hypertension in Non-diabetes Hypertensive Patients

Hypertension is the most common cardiovascular risk factor. Lipoprotein(a) [Lp(a)], inflammation, oxidative stress and chronic kidney disease (CKD) exacerbate the response to tissue injury and acts as markers of the vascular disease, especially in glomerulosclerosis. We compared the clinical characteristics of 138 non-diabetes hypertensive women (ndHT) patients with 417 non-diabetes normotensive subjects and tested the association of hypertension with Lp(a), inflammation, CKD and oxidative stress by using multiple logistic regression. BP, BMI, waist circumference, creatinine, Lp(a), inflammation and malondialdehyde levels were significantly higher and CKD state in the ndHT patients (p < 0.05). Multiple logistic regression showed hypertension associated with increased Lp(a), inflammation, ORs and 95 % CIs were 2.52 (1.33, 4.80), 2.75 (1.44, 5.27) after adjusting for their covariates. Elevated serum Lp(a) and inflammation levels concomitants with increased oxidative stress and CKD were the major risk factors associated with hypertension and implications for the increased risk of HT and vascular disease.     

The effect of extremely high glucose concentrations on 21 routine chemistry and thyroid Abbott assays: interference study

Introduction

Extremely high glucose concentrations have been shown to interfere with creatinine assays especially with Jaffe method in peritoneal dialysate. Because diabetes is the fastest growing chronic disease in the world, laboratories study with varying glucose concentrations. We investigated whether different levels of glucose spiked in serum interfere with 21 routine chemistry and thyroid assays at glucose concentrations between 17-51 mmol/L.

Materials and methods

Baseline (group I) serum pool with glucose concentration of 5.55 (5.44-5.61) mmol/L was prepared from patient sera. Spiking with 20% dextrose solution, sample groups were obtained with glucose concentrations: 17.09, 34.52, and 50.95 mmol/L (group II, III, IV, respectively). Total of 21 biochemistry analytes and thyroid tests were studied on Abbott c8000 and i2000sr with commercial reagents. Bias from baseline value was checked statistically and clinically.

Results

Creatinine increased significantly by 8.74%, 31.66%, 55.31% at groups II, III, IV, respectively with P values of < 0.001. At the median glucose concentration of 50.95 mmol/L, calcium, albumin, chloride and FT4 biased significantly clinically (-0.85%, 1.63%, 0.65%, 7.4% with P values 0.138, 0.214, 0.004, < 0.001, respectively). Remaining assays were free of interference.

Conclusion

Among the numerous biochemical parameters studied, only a few parameters are affected by dramatically increased glucose concentration. The creatinine measurements obtained in human sera with the Jaffe alkaline method at high glucose concentrations should be interpreted with caution. Other tests that were affected with extremely high glucose concentrations were calcium, albumin, chloride and FT4, hence results should be taken into consideration in patients with poor diabetic control.Key words: assay interference, glucose interference, preanalytical phase, creatinine, Jaffe kinetic assay, thyroid function tests     

Parsimonious translation models for information retrieval

In the KL divergence framework, the extended language modeling approach has a critical problem of estimating a query model, which is the probabilistic model that encodes the user’s information need. For query expansion in initial retrieval, the translation model had been proposed to involve term co-occurrence statistics. However, the translation model was difficult to apply, because the term co-occurrence statistics must be constructed in the offline time. Especially in a large collection, constructing such a large matrix of term co-occurrences statistics prohibitively increases time and space complexity. In addition, reliable retrieval performance cannot be guaranteed because the translation model may comprise noisy non-topical terms in documents. To resolve these problems, this paper investigates an effective method to construct co-occurrence statistics and eliminate noisy terms by employing a parsimonious translation model. The parsimonious translation model is a compact version of a translation model that can reduce the number of terms containing non-zero probabilities by eliminating non-topical terms in documents. Through experimentation on seven different test collections, we show that the query model estimated from the parsimonious translation model significantly outperforms not only the baseline language modeling, but also the non-parsimonious models.     

An empirical study of query expansion and cluster-based retrieval in language modeling approach

The term mismatch problem in information retrieval is a critical problem, and several techniques have been developed, such as query expansion, cluster-based retrieval and dimensionality reduction to resolve this issue. Of these techniques, this paper performs an empirical study on query expansion and cluster-based retrieval. We examine the effect of using parsimony in query expansion and the effect of clustering algorithms in cluster-based retrieval. In addition, query expansion and cluster-based retrieval are compared, and their combinations are evaluated in terms of retrieval performance by performing experimentations on seven test collections of NTCIR and TREC.     

Critical factors influencing secondary school pupil’s decisions to study computing in tertiary education: Gender differences

This paper aims to determine the factors affecting the decisions of both male and female secondary school pupils whether or not to pursue undergraduate studies in Computing. It is based on research conducted in Greece, on a sample of 248 pupils, 135 of whom were female. All were aged 17 and about to decide on their future undergraduate studies. Questionnaires were used, addressing issues in the following four main categories: a) the reasons pupils chose/rejected Computing, b) how family and friends, the media and the school environment contribute to their decision, c) how pupils perceived their future after studying Computing and d) how pupils perceived the profile of a computer professional in terms of gender.

Religious Development in African American Adolescents: Growth Patterns That Offer Protection

Although religiosity promotes resilient outcomes in African American (AA) adolescents, there is a lack of research that examines the protective role of religious development in the context of stressful life events (SLEs). In 1,595 AA adolescents, a cohort-sequential design was used from ages 12 to 18 to examine subtypes of religiosity, as well as distinct developmental patterns within subtypes. The protective role of religious development was also examined in the context of SLEs. The study findings indicated two subtypes of religiosity—extrinsic and intrinsic religiosity—as well as low and high developmental patterns in the identified subtypes. Furthermore, the protective influence of extrinsic and intrinsic religiosity gradually diminished from age 12 to 18 in the context of SLEs.