335 research outputs found
致香港特別行政區 行政長官候選人的信
香港中文大學賽馬會公共衛生及基層醫療學院與香港大學公共衛生學院的公共衛生專家聯合署名致信香港特別行政區行政長官候選人,指出空氣污染這個香港公共衛生主要問題被長期忽視,並就目前特區政府推出保守的空氣質素目標,發表意見。link_to_OA_fulltex
Flipped SU(5) GUTs from E_8 Singularities in F-theory
In this paper we construct supersymmetric flipped SU(5) GUTs from E_8
singularities in F-theory. We start from an SO(10) singularity unfolded from an
E_8 singularity by using an SU(4) spectral cover. To obtain realistic models,
we consider (3,1) and (2,2) factorizations of the SU(4) cover. After turning on
the massless U(1)_X gauge flux, we obtain the SU(5) X U(1)_X gauge group. Based
on the well-studied geometric backgrounds in the literature, we demonstrate
several models and discuss their phenomenology.Comment: 46 pages, 23 tables, 1 figure, typos corrected, references added, and
new examples presente
On Global Flipped SU(5) GUTs in F-theory
We construct an SU(4) spectral divisor and its factorization of types (3,1)
and (2,2) based on the construction proposed in [1]. We calculate the chiral
spectra of flipped SU(5) GUTs by using the spectral divisor construction. The
results agree with those from the analysis of semi-local spectral covers. Our
computations provide an example for the validity of the spectral divisor
construction and suggest that the standard heterotic formulae are applicable to
the case of F-theory on an elliptically fibered Calabi-Yau fourfold with no
heterotic dual.Comment: 45 pages, 12 tables, 1 figure; typos corrected, footnotes added, and
a reference adde
Addressing Cancer Disparities via Community Network Mobilization and Intersectoral Partnerships: A Social Network Analysis
Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT). As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR) to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate). Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree) increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity). We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications). We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement). The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities. The findings support investment in infrastructure-building and intersectoral mobilization in addressing disparities and highlight the benefits of using CBPR approaches for such work
A meta-analysis of long-term effects of conservation agriculture on maize grain yield under rain-fed conditions
Conservation agriculture involves reduced tillage, permanent soil cover and crop rotations to enhance soil fertility and to supply food from a dwindling land resource. Recently, conservation agriculture has been promoted in Southern Africa, mainly for maize-based farming systems. However, maize yields under rain-fed conditions are often variable. There is therefore a need to identify factors that influence crop yield under conservation agriculture and rain-fed conditions. Here, we studied maize grain yield data from experiments lasting 5 years and more under rain-fed conditions. We assessed the effect of long-term tillage and residue retention on maize grain yield under contrasting soil textures, nitrogen input and climate. Yield variability was measured by stability analysis. Our results show an increase in maize yield over time with conservation agriculture practices that include rotation and high input use in low rainfall areas. But we observed no difference in system stability under those conditions. We observed a strong relationship between maize grain yield and annual rainfall. Our meta-analysis gave the following findings: (1) 92% of the data show that mulch cover in high rainfall areas leads to lower yields due to waterlogging; (2) 85% of data show that soil texture is important in the temporal development of conservation agriculture effects, improved yields are likely on well-drained soils; (3) 73% of the data show that conservation agriculture practices require high inputs especially N for improved yield; (4) 63% of data show that increased yields are obtained with rotation but calculations often do not include the variations in rainfall within and between seasons; (5) 56% of the data show that reduced tillage with no mulch cover leads to lower yields in semi-arid areas; and (6) when adequate fertiliser is available, rainfall is the most important determinant of yield in southern Africa. It is clear from our results that conservation agriculture needs to be targeted and adapted to specific biophysical conditions for improved impact
Clinicians’ response to hyperoxia in ventilated patients in a Dutch ICU depends on the level of FiO2
Hyperoxia may induce pulmonary injury and may increase oxidative stress. In this retrospective database study we aimed to evaluate the response to hyperoxia by intensivists in a Dutch academic intensive care unit. All arterial blood gas (ABG) data from mechanically ventilated patients from 2005 until 2009 were extracted from an electronic storage database of a mixed 32-bed intensive care unit in a university hospital in Amsterdam. Mechanical ventilation settings at the time of the ABG tests were retrieved. The results of 126,778 ABG tests from 5,498 mechanically ventilated patients were retrieved including corresponding ventilator settings. In 28,222 (22%) of the ABG tests the arterial oxygen tension (PaO2) was > 16 kPa (120 mmHg). In only 25% of the tests with PaO2 > 16 kPa (120 mmHg) was the fraction of inspired oxygen (FiO(2)) decreased. Hyperoxia was accepted without adjustment in ventilator settings if FiO(2) was 0.4 or lower. Hyperoxia is frequently seen but in most cases does not lead to adjustment of ventilator settings if FiO(2) <0.41. Implementation of guidelines concerning oxygen therapy should be improved and further research is needed concerning the effects of frequently encountered hyperoxi
Only females in poor condition display a clear preference and prefer males with an average badge
<p>Abstract</p> <p>Background</p> <p>Female condition-dependent variation in mate preference may have important evolutionary implications, not only within the same population but also among populations. There are few experiments, however, on how condition and/or genotype influences female mate preferences. The black throat patch of the male house sparrow, <it>Passer domesticus</it>, is an intensively studied plumage trait. It is often referred to as a 'badge of status' and seems to be involved in female mate choice, but differences exist among populations. Between-population variation in mate preference may occur for condition-dependent mate preferences. We tested the hypothesis that female preference may vary with female quality (body condition). Therefore, we measured female preference for badge size using an aviary two-choice test in which females were presented with two males that had different sizes of badges (enlarged or averaged).</p> <p>Results</p> <p>Overall we did not find a female preference for enlarged or average badges, but low-quality females spent more time near average badge males. Conversely, high-quality females did not show a clear preference.</p> <p>Conclusions</p> <p>Collectively, these results indicate that female preference varies with female quality. Differences in female condition are causes of within-population variation in mating preferences. To our knowledge, our results provide one of the first experimental evidences that variation in preference for a male ornament is associated with female condition. In our study, however, only females of low condition displayed a clear mate preference. Differences observed among populations could be partly explained by differences in female condition.</p
Human Gene Coexpression Landscape: Confident Network Derived from Tissue Transcriptomic Profiles
This is an open-access article distributed under the terms of the Creative Commons Attribution License.[Background]: Analysis of gene expression data using genome-wide microarrays is a technique often used in genomic studies to find coexpression patterns and locate groups of co-transcribed genes. However, most studies done at global >omic> scale are not focused on human samples and when they correspond to human very often include heterogeneous datasets, mixing normal with disease-altered samples. Moreover, the technical noise present in genome-wide expression microarrays is another well reported problem that many times is not addressed with robust statistical methods, and the estimation of errors in the data is not provided. [Methodology/Principal Findings]: Human genome-wide expression data from a controlled set of normal-healthy tissues is used to build a confident human gene coexpression network avoiding both pathological and technical noise. To achieve this we describe a new method that combines several statistical and computational strategies: robust normalization and expression signal calculation; correlation coefficients obtained by parametric and non-parametric methods; random cross-validations; and estimation of the statistical accuracy and coverage of the data. All these methods provide a series of coexpression datasets where the level of error is measured and can be tuned. To define the errors, the rates of true positives are calculated by assignment to biological pathways. The results provide a confident human gene coexpression network that includes 3327 gene-nodes and 15841 coexpression-links and a comparative analysis shows good improvement over previously published datasets. Further functional analysis of a subset core network, validated by two independent methods, shows coherent biological modules that share common transcription factors. The network reveals a map of coexpression clusters organized in well defined functional constellations. Two major regions in this network correspond to genes involved in nuclear and mitochondrial metabolism and investigations on their functional assignment indicate that more than 60% are house-keeping and essential genes. The network displays new non-described gene associations and it allows the placement in a functional context of some unknown non-assigned genes based on their interactions with known gene families. [Conclusions/Significance]: The identification of stable and reliable human gene to gene coexpression networks is essential to unravel the interactions and functional correlations between human genes at an omic scale. This work contributes to this aim, and we are making available for the scientific community the validated human gene coexpression networks obtained, to allow further analyses on the network or on some specific gene associations. The data are available free online at http://bioinfow.dep.usal.es/coexpression/. © 2008 Prieto et al.Funding and grant support was provided by the Ministery of Health, Spanish Government (ISCiii-FIS, MSyC; Project reference PI061153) and by the Ministery of Education, Castilla-Leon Local Government (JCyL; Project reference CSI03A06).Peer Reviewe
Optimizing the diagnostic power with gastric emptying scintigraphy at multiple time points
<p>Abstract</p> <p>Background</p> <p>Gastric Emptying Scintigraphy (GES) at intervals over 4 hours after a standardized radio-labeled meal is commonly regarded as the gold standard for diagnosing gastroparesis. The objectives of this study were: 1) to investigate the best time point and the best combination of multiple time points for diagnosing gastroparesis with repeated GES measures, and 2) to contrast and cross-validate Fisher's Linear Discriminant Analysis (LDA), a rank based Distribution Free (DF) approach, and the Classification And Regression Tree (CART) model.</p> <p>Methods</p> <p>A total of 320 patients with GES measures at 1, 2, 3, and 4 hour (h) after a standard meal using a standardized method were retrospectively collected. Area under the Receiver Operating Characteristic (ROC) curve and the rate of false classification through jackknife cross-validation were used for model comparison.</p> <p>Results</p> <p>Due to strong correlation and an abnormality in data distribution, no substantial improvement in diagnostic power was found with the best linear combination by LDA approach even with data transformation. With DF method, the linear combination of 4-h and 3-h increased the Area Under the Curve (AUC) and decreased the number of false classifications (0.87; 15.0%) over individual time points (0.83, 0.82; 15.6%, 25.3%, for 4-h and 3-h, respectively) at a higher sensitivity level (sensitivity = 0.9). The CART model using 4 hourly GES measurements along with patient's age was the most accurate diagnostic tool (AUC = 0.88, false classification = 13.8%). Patients having a 4-h gastric retention value >10% were 5 times more likely to have gastroparesis (179/207 = 86.5%) than those with ≤10% (18/113 = 15.9%).</p> <p>Conclusions</p> <p>With a mixed group of patients either referred with suspected gastroparesis or investigated for other reasons, the CART model is more robust than the LDA and DF approaches, capable of accommodating covariate effects and can be generalized for cross institutional applications, but could be unstable if sample size is limited.</p
Gain-through-filtering enables tuneable frequency comb generation in passive optical resonators
Optical frequency combs (OFCs), consisting of a set of phase-locked, equally spaced laser frequency lines, have enabled a great leap in precision spectroscopy and metrology since seminal works of Hänsch et al. Nowadays, OFCs are cornerstones of a wealth of further applications ranging from chemistry and biology to astrophysics and including molecular fingerprinting and light detection and ranging (LIDAR) systems, among others. Driven passive optical resonators constitute the ideal platform for OFC generation in terms of compactness and low energy footprint. We propose here a technique for the generation of OFCs with a tuneable repetition rate in externally driven optical resonators based on the gain-through-filtering process, a simple and elegant method, due to asymmetric spectral filtering on one side of the pump wave. We demonstrate a proof-of-concept experimental result in a fibre resonator, pioneering a new technique that does not require specific engineering of the resonator dispersion to generate frequency-agile OFCs
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