Quadratic Transmuted Modified Size-Biased Lehmann Type-II Distribution

In this paper, a two-parameter generalization of Modified Size-Biased Lehmann Type-II distribution is obtained, with the purpose of obtaining a more flexible model relative to the behaviour of hazard rate functions. Various statistical properties of this distribution including the density, hazard rate functions, quantile function, mode, moments, incomplete moments, moment generating functions, Lorenz, Bonferroni and Zenga curves, Rényi entropy and distribution of # order statistics have been derived. The method of maximum likelihood estimation has been used to estimate the parameters of the Quadratic Transmuted-Modified Size-Biased Lehmann Type-II distribution and its performance is discussed by following a simulation study. Real data sets are presented to demonstrate the effectiveness of the new model

Assessment of left ventricular diastolic function in bronchial asthma: can we rely on transmitral inflow velocity patterns?

Background: Left ventricular (LV) diastolic dysfunction has been reported in bronchial asthma (BA), based on the finding of abnormal transmitral inflow velocities on Doppler echocardiography, and attributed to the use of long-term β2-adrenoceptor agonists. However, these indices of LV filling may be affected by other factors. Objectives: We aimed to assess the effect of acute severe asthma in children on Doppler-derived transmitral inflow velocities and determine the factors influencing them. Methods: 23 asthmatic children [14 males, 9 females; age 8.4±4.2 years] and 15 age- and sex-matched, healthy children [10 males, 5 females; age 9.8±4.3 years] were studied clinically, by spirometry and by echocardiography both during and after resolution of acute severe asthma. Pulsed Doppler-derived right ventricular (RV) systolic time intervals [RV pre-ejection period corrected for heart rate (RVEPc), RV ejection time corrected for heart rate (RVETc), acceleration time (AT)], transmitral inflow velocities [peak E velocity, peak A velocity, E/A ratio], and isvolumic relaxation time (IVRT) were measured. Results: During acute exacerbations of BA, patients had significantly shorter RVETc (p < 0.05) and AT (p < 0.05), significantly higher peak A velocity (p < 0.01), significantly lower E/A ratio (p < 0.01), and significantly higher IVRT (<0.05). A highly significant inverse correlation existed between AT and peak A velocity [r= -0.634 (p < 0.01)] during acute asthma exacerbation but disappeared after its resolution. Conclusion: Transmitral inflow velocity patterns during acute severe asthma in children are suggestive of altered LV preload due to an acute transient elevation in pulmonary artery pressure secondary to the altered lung mechanics, and are not reflective of intrinsic LV diastolic dysfunction. Keywords: Bronchial asthma, right ventricular systolic time intervals, left ventricular diastolic function, transmitral inflow velocity; echocardiography, childrenEgypt J Pediatr Allergy Immunol 2006; 4(2): 61-6

Utilization, Receptivity and Reactivity to Interactive Voice Response Daily Monitoring in Risky Drinking Smokers Who Are Motivated to Quit

INTRODUCTION Interactive Voice Response (IVR) technology has become an increasingly popular and valid method for collecting Ecological Momentary Assessment (EMA) data on a variety of health-risk behaviors, including daily alcohol use and cigarette smoking, and for stimulating behavior change. However, very little research has evaluated the parameters of IVR compliance and reactivity in respondents who may have greater problem severity than samples previously examined in published IVR studies. This study examined the prevalence and correlates of use, receptivity and reactivity to IVR monitoring in 77 untreated risky drinking smokers who were motivated to quit within the next 6 months. METHODS Respondents completed twice daily IVR assessments for 28 days and were re-assessed immediately after IVR to measure receptivity and reactivity to daily monitoring and six months post-baseline. RESULTS Mean compliance rate was 70.6%, with a morning rate of 72.4% and an evening compliance rate of 68.9% out of all possible surveys. IVR assessments of drinking and smoking were significantly associated with baseline paper-pencil reports of the same. African-American participants and those who reported more daily stressful events were more compliant. Between the baseline session and the 6-month follow-up, 68% of the sample reported engaging in some form of smoking behavior change (50% reduction in CPD, a quit attempt, past month continuous abstinence). Nearly 80% reported increased awareness of their behavior due to the IVR and 40% reported intentional behavior change from IVR monitoring. The odds of making a quit attempt at the 6-month follow-up were significantly higher among respondents who reported making purposeful changes to their smoking as a result of IVR monitoring (AOR=3.25, p\u3c0.05). CONCLUSIONS Reactivity was associated with behavior change outcomes. IVR may be a useful tool for motivating behavior change in smokers with alcohol-use problems

QuickXsort: Efficient Sorting with n log n - 1.399n +o(n) Comparisons on Average

In this paper we generalize the idea of QuickHeapsort leading to the notion of QuickXsort. Given some external sorting algorithm X, QuickXsort yields an internal sorting algorithm if X satisfies certain natural conditions. With QuickWeakHeapsort and QuickMergesort we present two examples for the QuickXsort-construction. Both are efficient algorithms that incur approximately n log n - 1.26n +o(n) comparisons on the average. A worst case of n log n + O(n) comparisons can be achieved without significantly affecting the average case. Furthermore, we describe an implementation of MergeInsertion for small n. Taking MergeInsertion as a base case for QuickMergesort, we establish a worst-case efficient sorting algorithm calling for n log n - 1.3999n + o(n) comparisons on average. QuickMergesort with constant size base cases shows the best performance on practical inputs: when sorting integers it is slower by only 15% to STL-Introsort

Immunomodulatory effects of food

There is a strong consensus that nutrition plays a role in modulating immune function and that the immune system needs adequate supply of nutrients to function properly. The complexity of the immune system supports this idea because its optimal functioning involves a variety of biological activities including cell division and proliferation, energy metabolism, and production of proteins. The micronutrients most often cited as being important to immune function include vitamins A, C, E, and B6, folate, iron, zinc, and selenium. Other nutrients mentioned as playing a role in immune function include beta-carotene (a precursor to vitamin A), vitamin B12, and vitamin D. On the other hand, over-activation of the immune system can lead to detrimental effects such as chronic inflammation or autoimmune diseases. In persons with allergies, a normally harmless material can be mistaken as an antigen. Some individuals develop an exaggerated immune response to food through developing food allergy which may be IgE mediated, non-IgE mediated, or mixed. This review will highlight the interaction between the immune system and some foods and food components in terms of modulation of immune functions by a variety of mechanisms.Egypt J Pediatr Allergy Immunol 2011;9(1):3-1

Phylogenetic characterization of two echinoid species of the southeastern Mediterranean, off Egypt

AbstractIn this study we investigated the phylogenetics of two sea urchin species, Arbacia lixula and Paracentrotus lividus from the Mediterranean Sea. Specimens were collected from the east coast of Alexandria City, Egypt. Pigmentation examination showed four sympatric color morphotypes (black, purple, reddish brown, and olive green). Mitochondrial DNA was extracted from specimens and mitochondrial cytochrome oxidase subunit I (COI) and 16S ribosomal RNA (16S) were sequenced. The results showed that all black specimens constituted the species A. lixula. All other colors belonged to P. lividus, with no apparent differentiation between color morphotypes. Moreover, P. lividus showed high haplotype diversity (COI; H=0.9500 and 16S; H=0.8580) and low values of nucleotide diversity (COI; π=0.0075 and 16S; π=0.0049), indicating a high degree of polymorphism within this species. This study represents the first attempt at DNA barcoding of echinoid species in the southeast Mediterranean off the Egyptian coast, and will provide a base for future phylogenetic analyses

Deep Learning Algorithms for the Detection of Suspicious Pigmented Skin Lesions in Primary Care Settings: A Systematic Review and Meta- Analysis

Early detection of suspicious pigmented skin lesions is crucial for improving the outcomes and survival rates of skin cancers. However, the accuracy of clinical diagnosis by primary care physicians (PCPs) is suboptimal, leading to unnecessary referrals and biopsies. In recent years, deep learning (DL) algorithms have shown promising results in the automated detection and classification of skin lesions. This systematic review and meta-analysis aimed to evaluate the diagnostic performance of DL algorithms for the detection of suspicious pigmented skin lesions in primary care settings. A comprehensive literature search was conducted using electronic databases, including PubMed, Scopus, IEEE Xplore, Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science. Data from eligible studies were extracted, including study characteristics, sample size, algorithm type, sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and receiver operating characteristic curve analysis. Three studies were included. The results showed that DL algorithms had a high sensitivity (90%, 95% CI: 90-91%) and specificity (85%, 95% CI: 84-86%) for detecting suspicious pigmented skin lesions in primary care settings. Significant heterogeneity was observed in both sensitivity (p = 0.0062, I² = 80.3%) and specificity (p < 0.001, I² = 98.8%). The analysis of DOR and PLR further demonstrated the strong diagnostic performance of DL algorithms. The DOR was 26.39, indicating a strong overall diagnostic performance of DL algorithms. The PLR was 4.30, highlighting the ability of these algorithms to influence diagnostic outcomes positively. The NLR was 0.16, indicating that a negative test result decreased the odds of misdiagnosis. The area under the curve of DL algorithms was 0.95, indicating excellent discriminative ability in distinguishing between benign and malignant pigmented skin lesions. DL algorithms have the potential to significantly improve the detection of suspicious pigmented skin lesions in primary care settings. Our analysis showed that DL exhibited promising performance in the early detection of suspicious pigmented skin lesions. However, further studies are needed

On the complexity of strongly connected components in directed hypergraphs

We study the complexity of some algorithmic problems on directed hypergraphs and their strongly connected components (SCCs). The main contribution is an almost linear time algorithm computing the terminal strongly connected components (i.e. SCCs which do not reach any components but themselves). "Almost linear" here means that the complexity of the algorithm is linear in the size of the hypergraph up to a factor alpha(n), where alpha is the inverse of Ackermann function, and n is the number of vertices. Our motivation to study this problem arises from a recent application of directed hypergraphs to computational tropical geometry. We also discuss the problem of computing all SCCs. We establish a superlinear lower bound on the size of the transitive reduction of the reachability relation in directed hypergraphs, showing that it is combinatorially more complex than in directed graphs. Besides, we prove a linear time reduction from the well-studied problem of finding all minimal sets among a given family to the problem of computing the SCCs. Only subquadratic time algorithms are known for the former problem. These results strongly suggest that the problem of computing the SCCs is harder in directed hypergraphs than in directed graphs.Comment: v1: 32 pages, 7 figures; v2: revised version, 34 pages, 7 figure

Belga B-trees

We revisit self-adjusting external memory tree data structures, which combine the optimal (and practical) worst-case I/O performances of B-trees, while adapting to the online distribution of queries. Our approach is analogous to undergoing efforts in the BST model, where Tango Trees (Demaine et al. 2007) were shown to be $O(\log\log N)$-competitive with the runtime of the best offline binary search tree on every sequence of searches. Here we formalize the B-Tree model as a natural generalization of the BST model. We prove lower bounds for the B-Tree model, and introduce a B-Tree model data structure, the Belga B-tree, that executes any sequence of searches within a $O(\log \log N)$ factor of the best offline B-tree model algorithm, provided $B=\log^{O(1)}N$. We also show how to transform any static BST into a static B-tree which is faster by a $\Theta(\log B)$ factor; the transformation is randomized and we show that randomization is necessary to obtain any significant speedup