Moudud Alam

A Novel Generalized Ridge Regression Method for Quantitative Genetics

As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithm for situations in which the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number of observations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm. Using such an approach, a heteroscedastic effects model (HEM) was also developed, implemented, and tested. The efficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis data set including 84 inbred lines and 216,130 SNPs. The computation of all the SNP effects required <10 sec using a single 2.7-GHz core. The advantage in run time makes permutation test feasible for such a whole-genome model, so that a genome-wide significance threshold can be obtained. HEM was found to be more robust than ordinary RR (a.k.a. SNP-best linear unbiased prediction) in terms of QTL mapping, because SNP-specific shrinkage was applied instead of a common shrinkage. The proposed algorithm was also assessed for genomic evaluation and was shown to give better predictions than ordinary RR.

Road Barrier Repair Costs and Influencing Factors

This paper presents a study that examines repair costs for different road barrier types and factors that influence these costs. The analyses focused on w-beam and cable barriers used as median barriers. To some extent, pipe barriers, Kohlswa-beam barriers, and concrete barriers were also studied. The influencing factors included in this study were road type, speed limit, barrier type, and seasonal effects. A case study was conducted in four regions of the Swedish Road Administration. Data were collected from 1,625 barrier repairs carried out during 2005 and 2006. The results show that the number of barrier repairs and the average repair cost per vehicle kilometer are higher along collision-free roads than along motorways and 4-lane roads. The results also show that the number of barrier repairs and the average repair cost per vehicle kilometer are higher for cable barrier than for other barrier types. No conclusion can be drawn regarding influence of speed limits on barrier repairs and associated costs as the result from the regions are divergent and not statistically significant.

Computationally feasible estimation of the covariance structure in generalized linear mixed models

In this paper, we discuss how a regression model, with a non-continuous response variable, which allows for dependency between observations, should be estimated when observations are clustered and measurements on the subjects are repeated. The cluster sizes are assumed to be large. We find that the conventional estimation technique suggested by the literature on generalized linear mixed models (GLMM) is slow and sometimes fails due to non-convergence and lack of memory on standard PCs. We suggest to estimate the random effects as fixed effects by generalized linear model and to derive the covariance matrix from these estimates. A simulation study shows that our proposal is feasible in terms of mean-square error and computation time. We recommend that our proposal be implemented in the software of GLMM techniques so that the estimation procedure can switch between the conventional technique and our proposal, depending on the size of the clusters.

Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation

Abstract Worldwide there is a rush toward wind power development and its associated infrastructure. In Fennoscandia, large‐scale wind farms comprising several hundred windmills are currently built in important grazing ranges used for Sámi reindeer husbandry. In this study, reindeer habitat use was assessed using reindeer fecal pellet group counts in relation to two relatively small wind farms, with 8 and 10 turbines, respectively. In 2009, 1,315 15‐m2 plots were established and pellet groups were counted and cleaned from the plots. This was repeated once a year in May, during preconstruction, construction, and operation of the wind farms, covering 6 years (2009–2014) of reindeer habitat use in the area. We modeled the presence/absence of any pellets in a plot at both the local (wind farm site) and regional (reindeer calving to autumn range) scale with a hierarchical logistic regression, where spatial correlation was accounted for via random effects, using vegetation type, and the interaction between distance to wind turbine and time period as predictor variables. Our results revealed an absolute reduction in pellet groups by 66% and 86% around each wind farm, respectively, at local scale and by 61% at regional scale during the operation phase compared to the preconstruction phase. At the regional, scale habitat use declined close to the turbines in the same comparison. However, at the local scale, we observed increased habitat use close to the wind turbines at one of the wind farms during the operation phase. This may be explained by continued use of an important migration route close to the wind farm. The reduced use at the regional scale nevertheless suggests that there may be an overall avoidance of both wind farms during operation, but further studies of reindeer movement and behavior are needed to gain a better understanding of the mechanisms behind this suggested avoidance.

A Treatment-Response Index From Wearable Sensors for Quantifying Parkinson's Disease Motor States

The goal of this study was to develop an algorithm that automatically quantifies motor states (off, on, dyskinesia) in Parkinsons disease (PD), based on accelerometry during a hand pronation-supination test. Clinicians ratings using the Treatment Response Scale (TRS), ranging from −3 (very Off) to 0 (On) to +3 (very dyskinetic), were used as target. For that purpose, 19 participants with advanced PD and 22 healthy persons were recruited in a single center open label clinical trial in Uppsala, Sweden. The trial consisted of single levodopa dose experiments for the people with PD (PwP), where participants were asked to perform standardized wrist rotation tests, using each hand, before and at prespecified time points after the dose. The participants used wrist sensors containing a three-dimensional accelerometer and gyroscope. Features to quantify the level, variation, and asymmetry of the sensor signals, three-level discrete wavelet transform features, and approximate entropy measures were extracted from the sensors data. At the time of the tests, the PwP were video recorded. Three movement disorder specialists rated the participants’ state on the TRS. A Treatment Response Index from Sensors (TRIS) was constructed to quantify the motor states based on the wrist rotation tests. Different machine learning algorithms were evaluated to map the features derived from the sensor data to the ratings provided by the three specialists. Results from cross validation, both in tenfold and a leave-one-individual out setting, showed good predictive power of a support vector machine model and high correlation to the TRS. Values at the end tails of the TRS were under and over predicted due to the lack of observations at those values but the model managed to accurately capture the dose-effect profiles of the patients. In addition, the TRIS had good test–retest reliability on the baseline levels of the PD participants (Intraclass correlation coefficient of 0.83) and reasonable sensitivity to levodopa treatment (0.33 for the TRIS). For a series of test occasions, the proposed algorithms provided dose-effect time profiles for participants with PD, which could be useful during therapy individualization of people suffering from advanced PD.

How to Determine the Progression of Young Skiers

Sports are popular among children in most countries, and many parents enjoy watching their children participate in sports as leisure activities. Various surveys suggest children play sports because it provides an arena for social relations, and as the child grows older, the stimulus from getting positive feedback of training in terms of race results plays a greater role. A sad aspect of sports and children is the high drop-out rate in the early teen-age years. To the extent the drop-out is caused by an emerging interest in other activities or a greater focus on studies, it is fi ne. But a substantial number of teen-agers drop out because they do not get positive feedback from the training in terms of racing results. Sports associations could probably take various measures to reduce the drop-out rate, and an ongoing debate concerns such measures. One explanation for the high drop-out frequency is that puberty affects individuals differently and the differential effects impact performance in sports. It is well-known that puberty occurs at somewhat different ages for individual teenagers. The risk of dropping out of sports could be high for individuals who experience puberty late because they might perform worse than their peers. That is, it is possible they would be dejected by comparatively weak racing results. Val Abbassi summarized male and female progression curves and the puberty effect in an article in American Academy of Pediatrics titled “Growth and Normal Puberty.” According to this work, the female curve is at its steepest around the age of 12. For males, it is around 14 years of age and steeper than for females. These curves are conventionally assumed to approximate the progression in sports. During the period of rapid change, the estimation of the progression curve is challenging. Skiers at the ages of 14–17 as for-runners in Svenska Skidspelen 2006. The style of skiing is skate. How to Determine the Progression of Young Skiers?

Out of sight of wind turbines—Reindeer response to wind farms in operation

Abstract To meet the expanding land use required for wind energy development, a better understanding of the effects on terrestrial animals’ responses to such development is required. Using GPS‐data from 50 freely ranging female reindeer (Rangifer tarandus) in the Malå reindeer herding community, Sweden, we determined reindeer calving sites and estimated reindeer habitat selection using resource selection functions (RSF). RSFs were estimated at both second‐ (selection of home range) and third‐order (selection within home range) scale in relation to environmental variables, wind farm (WF) development phase (before construction, construction, and operation), distance to the WFs and at the second‐order scale whether the wind turbines were in or out of sight of the reindeer. We found that the distance between reindeer calving site and WFs increased during the operation phase, compared to before construction. At both scales of selection, we found a significant decrease in habitat selection of areas in proximity of the WFs, in the same comparison. The results also revealed a shift in home range selection away from habitats where wind turbines became visible toward habitats where the wind turbines were obscured by topography (increase in use by 79% at 5 km). We interpret the reindeer shift in home range selection as an effect of the wind turbines per se. Using topography and land cover information together with the positions of wind turbines could therefore help identify sensitive habitats for reindeer and improve the planning and placement of WFs. In addition, we found that operation phase of these WFs had a stronger adverse impact on reindeer habitat selection than the construction phase. Thus, the continuous running of the wind turbines making a sound both day and night seemed to have disturbed the reindeer more than the sudden sounds and increased human activity during construction work.

Detecting road pavement deterioration with finite mixture models

Abstract Budget restrictions often limit the number of possible maintenance activities in a road network each year. To effectively allocate resources, the rate of road pavement deterioration is of great importance. If two maintenance candidates have an equivalent condition, it is reasonable to maintain the segment with the highest deterioration rate first. To identify such segments, finite mixture models were applied to road condition data from a part of the M4 highway in England. Assuming that data originates from two different normal distributions – defined as a ‘change’ distribution and an ‘unchanged’ distribution – all road segments were classified into one of the groups. Comparisons with known measurement errors and maintenance records showed that segments in the unchanged group had a stationary road condition. Segments classified into the change group showed either a rapid deterioration, improvement in condition because of previous maintenance or unusual measurement errors. Together with additional information from maintenance records, finite mixture models can identify segments with the most rapid deterioration rate, and contribute to more efficient maintenance decisions.

Minimizing levodopa titration period for Parkinson’s disease

This free journal suppl. entitled: Supplement: Abstracts of the Twentieth International Congress of Parkinsons Disease and Movement DisordersObjective: To investigate the possible disease-association and pathogenic mechanisms of heterozygous PINK1 mutations from a genetic, functional, and structural perspective. Background: It has been postulated that heterozygous mutations in recessive PD genes may increase disease risk. In particular, the PINK1 p.G411S mutation has been reported in families with dominant inheritance patterns, suggesting that it might confer a sizeable disease risk. Methods: We performed a pedigree analysis of seven patients with a heterozygous PINK1 p.G411S mutation with at least one additional affected family member. We screened five case-control series and performed a meta-analysis of previous studies that had examined the variant. For functional cell-based analyses, we used patients skin fibroblast from PINK1 p.G411S or p.Q456X heterozygotes and investigated endogenous protein levels and kinase activity by biochemistry and imaging. For structural analyses, we performed molecular modeling and generated monomeric and dimeric forms of wild type (WT) and mutant PINK1 protein. Using molecular dynamics simulations, we analyzed effects of the p.G411S mutation on WT PINK1 in a heterodimeric complex over time. Results: Our analyses revealed a genetic association of heterozygous PINK1 p.G411S mutation with an increased risk for PD and a possible dominant inheritance with incomplete co-segregation. In patients skin fibroblasts, we establish a dominant negative mode for heterozygous p.G411S mutations under endogenous conditions. While total PINK1 protein levels were similar to controls upon mitochondrial stress, cellular PINK1 kinase activity was significantly reduced in p.G411S heterozygotes compared to WT and importantly to p.Q456X heterozygotes, which resulted in 50% reduction of PINK1 protein levels. Structural analyses supported our hypothesis that the p.G411S mutation can poison PINK1 WT in a heterodimeric complex and thus effectively reduce cellular PINK1 kinase activity. This in turn impairs the protective functions of the PINK1/PARKIN-mediated mitochondrial quality control. Conclusions: Our study uncovers increased disease risk and molecular mechanisms of a particular heterozygous mutation in a recessive PD gene. Based on genetic and clinical evaluation as well as functional and structural characterization, we established PINK1 p.G411S as a rare genetic risk factor with a relatively large effect size conferred by a dominant negative function phenotype. (Less)Objective: The aim of this study is to develop and evaluate methods for quantifying motor symptoms in Parkinson’s disease (PD) using combined upper limb motor test data collected during tapping and ...20th International Congress of Parkinson’s disease and Movement Disorders, Berlin, Germany, 19-23 June, 2016Upper limb motor tests are related to clinical ratings of motor function in advanced Parkinsons disease