Irrigation and drainage in the new millennium

Presented at the 2000 USCID international conference, Challenges facing irrigation and drainage in the new millennium on June 20-24 in Fort Collins, Colorado.Irrigation scheduling has been promoted as management tool to minimize irrigation water application, however, few irrigators regularly followed any rigorous scheduling methodology. Kansas State University Research and Extension in conjunction with an irrigation association, Water PACK, began a long-term project to promote ET based irrigation scheduling and other management technology. Area irrigators serve as the focal point of the project and over time have been asked to assume responsibility of scheduling the project fields. A long-term commitment and on-farm activities such as variable water application tests and center pivot uniformity tests seems to have generated confidence and acceptance of ET-based irrigation scheduling

Meta-analysis of generalized additive models in neuroimaging studies

Contains fulltext : 231772.pdf (publisher's version ) (Open Access)Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to systematically investigate between-study differences. Restrictions due to privacy or proprietary data as well as more practical concerns can make it hard to share neuroimaging datasets, such that analyzing all data in a common location might be impractical or impossible. Meta-analytic methods provide a way to overcome this issue, by combining aggregated quantities like model parameters or risk ratios. Most meta-analytic tools focus on parametric statistical models, and methods for meta-analyzing semi-parametric models like generalized additive models have not been well developed. Parametric models are often not appropriate in neuroimaging, where for instance age-brain relationships may take forms that are difficult to accurately describe using such models. In this paper we introduce meta-GAM, a method for meta-analysis of generalized additive models which does not require individual participant data, and hence is suitable for increasing statistical power while upholding privacy and other regulatory concerns. We extend previous works by enabling the analysis of multiple model terms as well as multivariate smooth functions. In addition, we show how meta-analytic p-values can be computed for smooth terms. The proposed methods are shown to perform well in simulation experiments, and are demonstrated in a real data analysis on hippocampal volume and self-reported sleep quality data from the Lifebrain consortium. We argue that application of meta-GAM is especially beneficial in lifespan neuroscience and imaging genetics. The methods are implemented in an accompanying R package metagam, which is also demonstrated

Does timing of decisions in a mixed duopoly matter?

We determine the endogenous order of moves in a mixed pricesetting duopoly. In contrast to the existing literature on mixed oligopolies we establish the payo equivalence of the games with an exogenously given order of moves if the most plausible equilibrium is realized in the market. Hence, in this case it does not matter whether one becomes a leader or a follower. We also establish that replacing a private firm by a public firm in the standard Bertrand-Edgeworth game with capacity constraints increases social welfare and that a pure-strategy equilibrium always exists

Engineering monolayer poration for rapid exfoliation of microbial membranes

The spread of bacterial resistance to traditional antibiotics continues to stimulate the search for alternative antimicrobial strategies. All forms of life, from bacteria to humans, are postulated to rely on a fundamental host defense mechanism, which exploits the formation of open pores in microbial phospholipid bilayers. Here we predict that transmembrane poration is not necessary for antimicrobial activity and reveal a distinct poration mechanism that targets the outer leaflet of phospholipid bilayers. Using a combination of molecular-scale and real-time imaging, spectroscopy and spectrometry approaches, we introduce a structural motif with a universal insertion mode in reconstituted membranes and live bacteria. We demonstrate that this motif rapidly assembles into monolayer pits that coalesce during progressive membrane exfoliation, leading to bacterial cell death within minutes. The findings offer a new physical basis for designing effective antibiotics

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development

Improved Classification of Alzheimer's Disease Data via Removal of Nuisance Variability

Diagnosis of Alzheimer's disease is based on the results of neuropsychological tests and available supporting biomarkers such as the results of imaging studies. The results of the tests and the values of biomarkers are dependent on the nuisance features, such as age and gender. In order to improve diagnostic power, the effects of the nuisance features have to be removed from the data. In this paper, four types of interactions between classification features and nuisance features were identified. Three methods were tested to remove these interactions from the classification data. In stratified analysis, a homogeneous subgroup was generated from a training set. Data correction method utilized linear regression model to remove the effects of nuisance features from data. The third method was a combination of these two methods. The methods were tested using all the baseline data from the Alzheimer's Disease Neuroimaging Initiative database in two classification studies: classifying control subjects from Alzheimer's disease patients and discriminating stable and progressive mild cognitive impairment subjects. The results show that both stratified analysis and data correction are able to statistically significantly improve the classification accuracy of several neuropsychological tests and imaging biomarkers. The improvements were especially large for the classification of stable and progressive mild cognitive impairment subjects, where the best improvements observed were 6% units. The data correction method gave better results for imaging biomarkers, whereas stratified analysis worked well with the neuropsychological tests. In conclusion, the study shows that the excess variability caused by nuisance features should be removed from the data to improve the classification accuracy, and therefore, the reliability of diagnosis making

Inflammation, Amyloid, and Atrophy in The Aging Brain: Relationships with Longitudinal Changes in Cognition

Amyloid deposition occurs in aging, even in individuals free from cognitive symptoms, and is often interpreted as preclinical Alzheimer’s disease (AD) pathophysiology. YKL-40 is a marker of neuroinflammation, being increased in AD, and hypothesized to interact with amyloid-β (Aβ) in causing cognitive decline early in the cascade of AD pathophysiology. Whether and how Aβ and YKL-40 affect brain and cognitive changes in cognitively healthy older adults is still unknown. We studied 89 participants (mean age: 73.1 years) with cerebrospinal fluid samples at baseline, and both MRI and cognitive assessments from two time-points separated by two years. We tested how baseline levels of Aβ42 and YKL-40 correlated with changes in cortical thickness and cognition. Thickness change correlated with Aβ42 only in Aβ42+ participants (<600 pg/mL, n = 27) in the left motor and premotor cortices. Aβ42 was unrelated to cognitive change. Increased YKL-40 was associated with less preservation of scores on the animal naming test in the total sample (r = –0.28, p = 0.012) and less preservation of a score reflecting global cognitive function for Aβ42+ participants (r = –0.58, p = 0.004). Our results suggest a role for inflammation in brain atrophy and cognitive changes in cognitively normal older adults, which partly depended on Aβ accumulation

Is short sleep bad for the brain? Brain structure and cognitive function in short sleepers

Many sleep less than recommended without experiencing daytime tiredness. According to prevailing views, short sleep increases risk of lower brain health and cognitive function. Chronic mild sleep deprivation could cause undetected sleep debt, negatively affecting cognitive function and brain health. However, it is possible that some have less sleep need and are more resistant to negative effects of sleep loss. We investigated this question using a combined cross-sectional and longitudinal sample of 47,029 participants (age 20-89 years) with measures of self-reported sleep, including 51,295 MRIs of the brain and cognitive tests. 701 participants who reported to sleep < 6 hours did not experience daytime tiredness or sleep problems. These short sleepers showed significantly larger regional brain volumes than both short sleepers with daytime tiredness and sleep problems (n = 1619) and participants sleeping the recommended 7-8 hours (n = 3754). However, both groups of short sleepers showed slightly lower general cognitive function, 0.16 and 0.19 standard deviations, respectively. Analyses using acelerometer-estimated sleep duration confirmed the findings, and the associations remained after controlling for body mass index, depression symptoms, income and education. The results suggest that some people can cope with less sleep without obvious negative consequences for brain morphometry, in line with a view on sleep need as individualized. Tiredness and sleep problems seem to be more relevant for brain structural differences than sleep duration per se. However, the slightly lower performance on tests of general cognitive function warrants closer examination by experimental designs in natural settings