Sequential Pattern Mining with Multidimensional Interval Items

In real sequence pattern mining scenarios, the interval information between two item sets is very important. However, although existing algorithms can effectively mine frequent subsequence sets, the interval information is ignored. This paper aims to mine sequential patterns with multidimensional interval items in sequence databases. In order to address this problem, this paper defines and specifies the interval event problem in the sequential pattern mining task. Then, the interval event items framework is proposed to handle the multidimensional interval event items. Moreover, the MII-Prefixspan algorithm is introduced for the sequential pattern with multidimensional interval event items mining tasks. This algorithm adds the processing of interval event items in the mining process. We can get richer and more in line with actual needs information from mined sequence patterns through these methods. This scheme is applied to the actual website behaviour analysis task to obtain more valuable information for web optimization and provide more valuable sequence pattern information for practical problems. This work also opens a new pathway toward more efficient sequential pattern mining tasks

Study on the Modified triphenyl tetrazolium chloride – dehydrogenase activity (TTC-DHA) Method in Determination of bioactivity in the up-flow aerated bio-activated carbon filter

The study applied triphenyl tetrazolium chloride-dehydrogenase activity (TTC-DHA) method to detect the activities of attached biofilm on bio-activated carbon (BAC) samples in the up-flow aerated biological activated carbon filter (UABACF) treating textile secondary effluent. Modification to the conventional TTC-DHA determination method was proposed. In the modification, BAC samples were used directly to measure TTC-DHA without pre-separating the attached biofilm from carbon samples. After modification, the mean values of biofilm TTC-DHA activities for the BAC samples at different heights of the biofilter were 25 to 193 times higher than those measured in conventional way. In addition, the microbial activity distribution related more closely to substrate removal along the height of the reactor after modification. The results indicated that high activity of the bacteria that are firmly fixed on the porous surface of the media would be ignored during pre-separation of the attached biofilm from media surface. The study also indicated the influence of granular activated carbon (GAC) adsorption on the bio-activity of attached biofilm. GAC adsorption was favorable in the improvement of the activities within the biofilter, especially when the attached films were destroyed. The modification of TTC-DHA determination method made this technique more convenient and accurate in activity measurement of biofilm fixed on porous surface structured activated carbon.Keywords: Up-flow, aerated bio-filter, BAC, TTC-DHA, bioactivit

A hidden markov model for haplotype inference for present-absent data of clustered genes using identified haplotypes and haplotype patterns

The majority of killer cell immunoglobin-like receptor (KIR) genes are detected as either present or absent using locus-specific genotyping technology. Ambiguity arises from the presence of a specific KIR gene since the exact copy number (one or two) of that gene is unknown. Therefore, haplotype inference for these genes is becoming more challenging due to such large portion of missing information. Meantime, many haplotypes and partial haplotype patterns have been previously identified due to tight linkage disequilibrium (LD) among these clustered genes thus can be incorporated to facilitate haplotype inference. In this paper, we developed a hidden Markov model (HMM) based method that can incorporate identified haplotypes or partial haplotype patterns for haplotype inference from present-absent data of clustered genes (e.g., KIR genes). We compared its performance with an expectation maximization (EM) based method previously developed in terms of haplotype assignments and haplotype frequency estimation through extensive simulations for KIR genes. The simulation results showed that the new HMM based method outperformed the previous method when some incorrect haplotypes were included as identified haplotypes and/or the standard deviation of haplotype frequencies were small. We also compared the performance of our method with two methods that do not use previously identified haplotypes and haplotype patterns, including an EM based method, HPALORE, and a HMM based method, MaCH. Our simulation results showed that the incorporation of identified haplotypes and partial haplotype patterns can improve accuracy for haplotype inference. The new software package HaploHMM is available and can be downloaded at http://www.soph.uab.edu/ssg/files/People/KZhang/HaploHMM/haplohmm-index.html

Mapping of QTL for Grain Yield Components Based on a DH Population in Maize

The elite maize hybrid Zhengdan 958 (ZD958), which has high and stable yield and extensive adaptability, is widely grown in China. To elucidate the genetic basis of yield and its related traits in this elite hybrid, a set of doubled haploid (DH) lines derived from ZD958 were evaluated in four different environments at two locations over two years, and a total of 49 quantitative trait loci (QTL) and 24 pairs of epistatic interactions related to yield and yield components were detected. Furthermore, 21 QTL for six investigated phenotypic traits were detected across two different sites. Combining the results of these QTL in each environment and across both sites, three main QTL hotspots were found in chromosomal bins 2.02, 2.05–2.06, and 6.05 between the simple sequence repeat (SSR) markers umc1165-bnlg1017, umc1065-umc1637, and nc012-bnlg345, respectively. The existence of three QTL hotspots associated with various traits across multiple environments could be explained by pleiotropic QTL or multiple tightly linked QTL. These genetic regions could provide targets for genetic improvement, fine mapping, and marker-assisted selection in future studies

Thermal and mechanical cracking in bis(triisopropylsilylethnyl)pentacene thin films

No abstract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/60466/1/21518_ftp.pd

Utility of waist-to-height ratio in assessing the status of central obesity and related cardiometabolic risk profile among normal weight and overweight/obese children: The Bogalusa Heart Study

<p>Abstract</p> <p>Background</p> <p>Body Mass Index (BMI) is widely used to assess the impact of obesity on cardiometabolic risk in children but it does not always relate to central obesity and varies with growth and maturation. Waist-to-Height Ratio (WHtR) is a relatively constant anthropometric index of abdominal obesity across different age, sex or racial groups. However, information is scant on the utility of WHtR in assessing the status of abdominal obesity and related cardiometabolic risk profile among normal weight and overweight/obese children, categorized according to the accepted BMI threshold values.</p> <p>Methods</p> <p>Cross-sectional cardiometabolic risk factor variables on 3091 black and white children (56% white, 50% male), 4-18 years of age were used. Based on the age-, race- and sex-specific percentiles of BMI, the children were classified as normal weight (5th - 85th percentiles) and overweight/obese (≥ 85th percentile). The risk profiles of each group based on the WHtR (<0.5, no central obesity versus ≥ 0.5, central obesity) were compared.</p> <p>Results</p> <p>9.2% of the children in the normal weight group were centrally obese (WHtR ≥0.5) and 19.8% among the overweight/obese were not (WHtR < 0.5). On multivariate analysis the normal weight centrally obese children were 1.66, 2.01, 1.47 and 2.05 times more likely to have significant adverse levels of LDL cholesterol, HDL cholesterol, triglycerides and insulin, respectively. In addition to having a higher prevalence of parental history of type 2 diabetes mellitus, the normal weight central obesity group showed a significantly higher prevalence of metabolic syndrome (p < 0.0001). In the overweight/obese group, those without central obesity were 0.53 and 0.27 times less likely to have significant adverse levels of HDL cholesterol and HOMA-IR, respectively (p < 0.05), as compared to those with central obesity. These overweight/obese children without central obesity also showed significantly lower prevalence of parental history of hypertension (p = 0.002), type 2 diabetes mellitus (p = 0.03) and metabolic syndrome (p < 0.0001).</p> <p>Conclusion</p> <p>WHtR not only detects central obesity and related adverse cardiometabolic risk among normal weight children, but also identifies those without such conditions among the overweight/obese children, which has implications for pediatric primary care practice.</p