Longitudinal association of physical activity during pregnancy with maternal and infant outcomes: Findings from the Australian longitudinal study of women’s health

Background: Physical activity has known benefits during pregnancy; however, the optimum volume of physical activity through the different stages of pregnancy is not well known. Objectives: The aims of this study were to investigate the associations of physical activity volume in pregnant women in each trimester of pregnancy with maternal and infant outcomes. Design: The study involved 1657 pregnant women from the Australian Longitudinal Study on Women’s Health, who completed surveys from 2006 to 2012 (aged 28–39 years). Methods: Women reported being in either the first, second or third trimester of pregnancy. Women were grouped into four groups according to their self-reported physical activity during pregnancy: (1) Nil (0–<33.3 MET.min/week), (2) Low (33.3–<500 MET.min/week), (3) Moderate (500–<1000 MET.min/week) and (4) High (⩾1000 MET.min/week). Women who reported their physical activity during pregnancy completed a survey within three years after the birth, relating to outcomes associated with pregnancy and childbirth (gestational diabetes, hypertension, and antenatal depression and anxiety) and infant outcomes (birthweight and prematurity). Results: There was no association of physical activity in any trimester with infant birthweight, prematurity, gestational diabetes, hypertension or antenatal depression. Antenatal anxiety was less prevalent in women who reported low (1.7%) or moderate (1.1%) physical activity than in those who reported no activity (4.7%; p = 0.01). Conclusion: Different amounts of physical activity during pregnancy were not associated with the measured adverse health outcomes. However, low and moderate amounts of physical activity were associated with reduced incidence of antenatal anxiety

Environment and harvest time affects the combustion qualities of Miscanthus genotypes

Miscanthus spp. are high-yielding perennial C4 grasses, native to Asia, that are being investigated in Europe as potential biofuels. Production of economically viable solid biofuel must combine high biomass yields with good combustion qualities. Good biomass combustion quality depends on minimizing moisture, ash, K, chloride, N, and S. To this end, field trials at five sites in Europe from Sweden to Portugal were planted with 15 different genotypes including M. x giganteus, M. sacchariflorus, M. sinensis, and newly bred M. sinensis hybrids. Yield and combustion quality at an autumn and a late winter/ early spring harvest were determined in the third year after planting when the stands had reached maturity. As expected, delaying the harvest by three to four months improved the combustion quality of all genotypes by reducing ash (from 40 to 25 g kg-1 dry matter), K (from 9 to 4 g kg-1 dry matter), chloride (from 4 to 1 g kg-1 dry matter), N (from 5 to 4 g kg-1 dry matter), and moisture (from 564 to 291 g kg-1 fresh matter). However, the delayed harvest also decreased mean biomass yields from 17 to 14 t ha-1. There is a strong interaction among yield, quality, and site growing conditions. Results show that in northern regions of Europe, M. sinensis hybrids can be recommended for high yields (yielding up to 25 t ha-1), but M. sinensis (nonhybrid) genotypes have higher combustion qualities. In mid- and south Europe, M. giganteus (yielding up to 38 t ha-1) or specific high-yielding M. sinensis hybrids (yielding up to 41 t ha-1) are more suitable for biofuel production

Use of ERTS-A, Skylab, and supporting aircraft to enhance resource management

There are no author-identified significant results in this report

Extended quintessence, inflation, and stable de Sitter spaces

A new gauge-invariant criterion for stability against inhomogeneous perturbations of de Sitter space is applied to scenarios of dark energy and inflation in scalar-tensor gravity. The results extend previous studies.Comment: 16 pages, LaTeX, to appear in Class. Quantum Gra

Length of carotid stenosis predicts peri-procedural stroke or death and restenosis in patients randomized to endovascular treatment or endarterectomy.

BACKGROUND: The anatomy of carotid stenosis may influence the outcome of endovascular treatment or carotid endarterectomy. Whether anatomy favors one treatment over the other in terms of safety or efficacy has not been investigated in randomized trials. METHODS: In 414 patients with mostly symptomatic carotid stenosis randomized to endovascular treatment (angioplasty or stenting; n = 213) or carotid endarterectomy (n = 211) in the Carotid and Vertebral Artery Transluminal Angioplasty Study (CAVATAS), the degree and length of stenosis and plaque surface irregularity were assessed on baseline intraarterial angiography. Outcome measures were stroke or death occurring between randomization and 30 days after treatment, and ipsilateral stroke and restenosis ≥50% during follow-up. RESULTS: Carotid stenosis longer than 0.65 times the common carotid artery diameter was associated with increased risk of peri-procedural stroke or death after both endovascular treatment [odds ratio 2.79 (1.17-6.65), P = 0.02] and carotid endarterectomy [2.43 (1.03-5.73), P = 0.04], and with increased long-term risk of restenosis in endovascular treatment [hazard ratio 1.68 (1.12-2.53), P = 0.01]. The excess in restenosis after endovascular treatment compared with carotid endarterectomy was significantly greater in patients with long stenosis than with short stenosis at baseline (interaction P = 0.003). Results remained significant after multivariate adjustment. No associations were found for degree of stenosis and plaque surface. CONCLUSIONS: Increasing stenosis length is an independent risk factor for peri-procedural stroke or death in endovascular treatment and carotid endarterectomy, without favoring one treatment over the other. However, the excess restenosis rate after endovascular treatment compared with carotid endarterectomy increases with longer stenosis at baseline. Stenosis length merits further investigation in carotid revascularisation trials

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers

UAV Remote Sensing for High-Throughput Phenotyping and for Yield Prediction of Miscanthus by Machine Learning Techniques

Miscanthus holds a great potential in the frame of the bioeconomy, and yield prediction can help improve Miscanthus’ logistic supply chain. Breeding programs in several countries are attempting to produce high-yielding Miscanthus hybrids better adapted to different climates and end-uses. Multispectral images acquired from unmanned aerial vehicles (UAVs) in Italy and in the UK in 2021 and 2022 were used to investigate the feasibility of high-throughput phenotyping (HTP) of novel Miscanthus hybrids for yield prediction and crop traits estimation. An intercalibration procedure was performed using simulated data from the PROSAIL model to link vegetation indices (VIs) derived from two different multispectral sensors. The random forest algorithm estimated with good accuracy yield traits (light interception, plant height, green leaf biomass, and standing biomass) using a VIs time series, and predicted yield using a peak descriptor derived from a VIs time series with 2.3 Mg DM ha−1 of the root mean square error (RMSE). The study demonstrates the potential of UAVs’ multispectral images in HTP applications and in yield prediction, providing important information needed to increase sustainable biomass production

Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis

Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e. phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus. We generated over 100 000 single-nucleotide variants (SNVs) by sequencing restriction site-associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs to phenotypic data for 17 traits measured in a field trial. Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance. Genome-wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10 000–20 000, and tended to decline, but remain significant, when cross-validations were performed across subpopulations. Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible

High-Frequency (> 100 GHz) and High-Speed (< 1 ps) Electronic Devices

Contains reports on six research projects and a list of publications.MIT Research Laboratory of Electronics Postdoctoral FellowshipNational Science Foundation Grant DMR 90-22933MIT Lincoln Laboratory Advanced Concept ProgramAdvanced Research Projects Agency Contract MDA972-90-C-0021MIT Lincoln LaboratoryNational Aeronautics and Space Administration Grant NAG2-693U.S. Army Research Office Grant DAAL03-92-G-025

Investigating the potential of novel nonwoven fabrics for efficient pollination control in plant breeding

Plant breeding is achieved through the controlled self- or cross-pollination of individuals and typically involves isolation of floral parts from selected parental plants. Paper, cellulose or synthetic materials are used to avoid self pollination or cross contamination. Low seed set limits the rate of breeding progress and increases costs. We hypothesized that a novel ‘nonwoven’ fabric optimal for both pollination and seed set in multiple plant species could be developed. After determining the baseline pollen characteristics and usage requirements we established iterative three phase development and biological testing. This determined (1) that white fabric gave superior seed return and informed the (2) development of three non-woven materials using different fibre and layering techniques. We tested their performance in selfing and hybridisation experiments recording differences in performance by material type within species. Finally we (3) developed further advanced fabrics with increased air permeability and tested biological performance. An interaction between material type and species was observed and environmental decoupling investigated, showing that the non-woven fabrics had superior water vapour transmission and temperature regulation compared to controls. Overall, non-woven fabrics outperformed existing materials for both pollination and seed set and we found that different materials can optimize species-specific, rather than species-generic performance