HydroBlocks:a field-scale resolving land surface model for application over continental extents

Land surface spatial heterogeneity plays a significant role in the water, energy, and carbon cycles over a range of temporal and spatial scales. Until now, the representation of this spatial heterogeneity in land surface models has been limited to over simplistic schemes due to computation and environmental data limitations. This study introduces HydroBlocks—a novel land surface model that represents field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs). HydroBlocks is a coupling between the Noah-MP land surface model and the Dynamic TOPMODEL hydrologic model. The HRUs are defined by clustering proxies of the drivers of spatial heterogeneity using high-resolution land data. The clustering mechanism allows for each HRU's results to be mapped out in space, facilitating field-scale application and validation. The Little Washita watershed in the United States is used to assess HydroBlocks’ performance and added benefit from traditional land surface models. A comparison between the semi-distributed and fully distributed versions of the model suggests that using 1000 HRUs is sufficient to accurately approximate the fully distributed solution. A preliminary evaluation of model performance using available in-situ soil moisture observations suggests that HydroBlocks is generally able to reproduce the observed spatial and temporal dynamics of soil moisture. Model performance deficiencies can be primarily attributed to parameter uncertainty. HydroBlocks’ ability to explicitly resolve field-scale spatial heterogeneity while only requiring an increase in computation of one to two orders of magnitude when compared to existing land surface models is encouraging—ensemble field-scale land surface modeling over continental extents is now possible

Incremental dimension reduction of tensors with random index

We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable. Component encoding and decoding are performed on-line without computationally expensive re-analysis of the data set. The range of tensor indices can be extended dynamically without modifying the component representation. This idea originates from a mathematical model of semantic memory and a method known as random indexing in natural language processing. We generalize the random-indexing algorithm to tensors and present signal-to-noise-ratio simulations for representations of vectors and matrices. We present also a mathematical analysis of the approximate orthogonality of high-dimensional ternary vectors, which is a property that underpins this and other similar random-coding approaches to dimension reduction. To further demonstrate the properties of random indexing we present results of a synonym identification task. The method presented here has some similarities with random projection and Tucker decomposition, but it performs well at high dimensionality only (n>10^3). Random indexing is useful for a range of complex practical problems, e.g., in natural language processing, data mining, pattern recognition, event detection, graph searching and search engines. Prototype software is provided. It supports encoding and decoding of tensors of order >= 1 in a unified framework, i.e., vectors, matrices and higher order tensors.Comment: 36 pages, 9 figure

Genetic and Physiological Analysis of Iron Biofortification in Maize Kernels

BACKGROUND: Maize is a major cereal crop widely consumed in developing countries, which have a high prevalence of iron (Fe) deficiency anemia. The major cause of Fe deficiency in these countries is inadequate intake of bioavailable Fe, where poverty is a major factor. Therefore, biofortification of maize by increasing Fe concentration and or bioavailability has great potential to alleviate this deficiency. Maize is also a model system for genomic research and thus allows the opportunity for gene discovery. Here we describe an integrated genetic and physiological analysis of Fe nutrition in maize kernels, to identify loci that influence grain Fe concentration and bioavailability. METHODOLOGY: Quantitative trait locus (QTL) analysis was used to dissect grain Fe concentration (FeGC) and Fe bioavailability (FeGB) from the Intermated B73 × Mo17 (IBM) recombinant inbred (RI) population. FeGC was determined by ion coupled argon plasma emission spectroscopy (ICP). FeGB was determined by an in vitro digestion/Caco-2 cell line bioassay. CONCLUSIONS: Three modest QTL for FeGC were detected, in spite of high heritability. This suggests that FeGC is controlled by many small QTL, which may make it a challenging trait to improve by marker assisted breeding. Ten QTL for FeGB were identified and explained 54% of the variance observed in samples from a single year/location. Three of the largest FeGB QTL were isolated in sister derived lines and their effect was observed in three subsequent seasons in New York. Single season evaluations were also made at six other sites around North America, suggesting the enhancement of FeGB was not specific to our farm site. FeGB was not correlated with FeGC or phytic acid, suggesting that novel regulators of Fe nutrition are responsible for the differences observed. Our results indicate that iron biofortification of maize grain is achievable using specialized phenotyping tools and conventional plant breeding techniques

Social factors influencing Russian male alcohol use over the life course: a qualitative study investigating age based social norms, masculinity, and workplace context

The massive fluctuations occurring in Russian alcohol-related mortality since the mid-1980s cannot be seen outside of the context of great social and economic change. There is a dearth of qualitative studies about Russian male drinking and especially needed are those that address social processes and individual changes in drinking. Conducted as part of a longitudinal study on men’s alcohol consumption in Izhevsk, this qualitative study uses 25 semi-structured biographical interviews with men aged 33–60 years to explore life course variation in drinking. The dominant pattern was decreasing binge and frequent drinking as men reached middle age which was precipitated by family building, reductions in drinking with work colleagues, and health concerns. A minority of men described chaotic drinking histories with periods of abstinence and heavy drinking. The results highlight the importance of the blue-collar work environment for conditioning male heavy drinking in young adulthood through a variety of social, normative and structural mechanisms. Post-Soviet changes had a structural influence on the propensity for workplace drinking but the important social function of male drinking sessions remained. Bonding with workmates through heavy drinking was seen as an unavoidable and essential part of young men’s social life. With age peer pressure to drink decreased and the need to perform the role of responsible breadwinner put different behavioural demands on men. For some resisting social pressure to drink became an important site of self-determination and a mark of masculine maturity. Over the lifetime the place where masculine identity was asserted shifted from the workplace to the home, which commonly resulted in a reduction in drinking. We contribute to existing theories of Russian male drinking by showing that the performance of age-related social roles influences Russian men’s drinking patterns, drinking contexts and their attitudes. Further research should be conducted investigating drinking trajectories in Russian men

Brain age predicts mortality

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N = 2001), then tested in the Lothian Birth Cohort 1936 (N = 669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death

Residual effects of natural Zn chelates on navy bean response, Zn leaching and soil status

greenhouse experiment was conducted on weakly acidic and calcareous soils to evaluate the aging and residual effects of three natural organic Zn chelates [Zn-ethylenediaminedisuccinate (Zn-EDDS), Zn-polyhydroxyphenylcarboxylate and Zn-aminelignosulfonate] each administered in a single application to a first navy bean (Phaseolus vulgaris L.) crop at several different Zn application rates. In a second navy bean crop, we determined the following parameters: the extent of Zn leaching, the amount of available Zn remaining in soils, the amount of easily leachable Zn, the size of Zn fractions in soils, the pH and redox potential, the dry matter yield, and the soluble and total Zn concentrations in plants. The residual effect after 2 years of Zn fertilization mainly depended on the aging effect of Zn chelates and losses due to Zn leaching. The data relating to the evolution from the first to the second crop showed that the aging effect was noticeable in the calcareous soil. In the latter soil, the Zn-S,S-EDDS treatments showed greater decreases in the Zn uptake by plants than the other Zn treatments and the greatest Zn uptake by plants occurred when Zn was applied as Zn-aminelignosulfonate (10 mg Zn kg−1 rate, 6.85 mg Zn per lysimeter; 5 mg Zn kg−1 rate, 3.36 mg Zn per lysimeter). In contrast, in the calcareous soil, the maximum amount of Zn uptake, for the three chelates was 0.82 mg Zn per lysimeter. Consequently, a further application of Zn would be needed to prevent Zn deficiencies in the plants of a subsequent crop. The behaviour of the pH and Eh parameters in the soils and leachates did not depend on the natural Zn sources applied. In this study, the easily leachable Zn estimated by BaCl2 extraction was not adequate to predict Zn leaching from the soils in subsequent crops

Sexual Dimorphism in Healthy Aging and Mild Cognitive Impairment: A DTI Study

Previous PET and MRI studies have indicated that the degree to which pathology translates into clinical symptoms is strongly dependent on sex with women more likely to express pathology as a diagnosis of AD, whereas men are more resistant to clinical symptoms in the face of the same degree of pathology. Here we use DTI to investigate the difference between male and female white matter tracts in healthy older participants (24 women, 16 men) and participants with mild cognitive impairment (21 women, 12 men). Differences between control and MCI participants were found in fractional anisotropy (FA), radial diffusion (DR), axial diffusion (DA) and mean diffusion (MD). A significant main effect of sex was also reported for FA, MD and DR indices, with male control and male MCI participants having significantly more microstructural damage than their female counterparts. There was no sex by diagnosis interaction. Male MCIs also had significantly less normalised grey matter (GM) volume than female MCIs. However, in terms of absolute brain volume, male controls had significantly more brain volume than female controls. Normalised GM and WM volumes were found to decrease significantly with age with no age by sex interaction. Overall, these data suggest that the same degree of cognitive impairment is associated with greater structural damage in men compared with women

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta