Regularized Regression Problem in hyper-RKHS for Learning Kernels

This paper generalizes the two-stage kernel learning framework, illustrates its utility for kernel learning and out-of-sample extensions, and proves {asymptotic} convergence results for the introduced kernel learning model. Algorithmically, we extend target alignment by hyper-kernels in the two-stage kernel learning framework. The associated kernel learning task is formulated as a regression problem in a hyper-reproducing kernel Hilbert space (hyper-RKHS), i.e., learning on the space of kernels itself. To solve this problem, we present two regression models with bivariate forms in this space, including kernel ridge regression (KRR) and support vector regression (SVR) in the hyper-RKHS. By doing so, it provides significant model flexibility for kernel learning with outstanding performance in real-world applications. Specifically, our kernel learning framework is general, that is, the learned underlying kernel can be positive definite or indefinite, which adapts to various requirements in kernel learning. Theoretically, we study the convergence behavior of these learning algorithms in the hyper-RKHS and derive the learning rates. Different from the traditional approximation analysis in RKHS, our analyses need to consider the non-trivial independence of pairwise samples and the characterisation of hyper-RKHS. To the best of our knowledge, this is the first work in learning theory to study the approximation performance of regularized regression problem in hyper-RKHS.Comment: 25 pages, 3 figure

Assessing Short‐Term Impacts of Management Practices on N2O Emissions From Diverse Mediterranean Agricultural Ecosystems Using a Biogeochemical Model

Croplands are important sources of nitrous oxide (N2O) emissions. The lack of both long‐term field measurements and reliable methods for extrapolating these measurements has resulted in a large uncertainty in quantifying and mitigating N2O emissions from croplands. This is especially relevant in regions where cropping systems and farming management practices (FMPs) are diverse. In this study, a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC), was tested against N2O measurements from five cropping systems (alfalfa, wheat, lettuce, vineyards, and almond orchards) representing diverse environmental conditions and FMPs. The model tests indicated that DNDC was capable of predicting seasonal and annual total N2O emissions from these cropping systems, and the model\u27s performance was better than the Intergovernmental Panel on Climate Change emission factor approach. DNDC also captured the impacts on N2O emissions of nitrogen fertilization for wheat and lettuce, of stand age for alfalfa, as well as the spatial variability of N2O fluxes in vineyards and orchards. DNDC overestimated N2O fluxes following some heavy rainfall events. To reduce the biases of simulating N2O fluxes following heavy rainfall, studies should focus on clarifying mechanisms controlling impacts of environmental factors on denitrification. DNDC was then applied to assess the impacts on N2O emissions of FMPs, including tillage, fertilization, irrigation, and management of cover crops. The practices that can mitigate N2O emissions include reduced or no tillage, reduced N application rates, low‐volume irrigation, and cultivation of nonleguminous cover crops. This study demonstrates the necessity and potential of utilizing process‐based models to quantify N2O emissions from regions with highly diverse cropping systems

Beta(2)-adrenergic receptor (ADRB2) gene polymorphisms and risk of COPD exacerbations : the Rotterdam study

The role of the beta(2)-adrenergic receptor (ADRB2) gene in patients with chronic obstructive pulmonary disease (COPD) is unclear. We investigated the association between ADRB2 variants and the risk of exacerbations in COPD patients treated with inhaled beta(2)-agonists. Within the Rotterdam Study, a population-based cohort study, we followed 1053 COPD patients until the first COPD exacerbation or end of follow-up and extracted rs1042713 (16Arg > Gly) and rs1042714 (27Gln > Glu) in ADRB2. Exposure to inhaled beta(2)-agonists was categorized into current, past, or non-use on the index date (date of COPD exacerbation for cases and on the same day of follow-up for controls). COPD exacerbations were defined as acute episodes of worsening symptoms requiring systemic corticosteroids and/or antibiotics (moderate exacerbations), or hospitalization (severe exacerbations). The associations between ADRB2 variants and COPD exacerbations were assessed using Cox proportional hazards models, adjusting for age, sex, use of inhaled corticosteroids, daily dose of beta(2)-agonists, and smoking. In current users of beta(2)-agonists, the risk of COPD exacerbation decreased by 30% (hazard ratio (HR); 0.70, 95% CI: 0.59-0.84) for each copy of the Arg allele of rs1042713 and by 20% (HR; 0.80, 95% CI: 0.69-0.94) for each copy of the Gln allele of rs1042714. Furthermore, current users carrying the Arg16/Gln27 haplotype had a significantly lower risk (HR; 0.70, 95% CI: 0.59-0.85) of COPD exacerbation compared to the Gly16/Glu27 haplotype. In conclusion, we observed that the Arg16/Gln27 haplotype in ADRB2 was associated with a reduced risk of COPD exacerbation in current users of inhaled beta(2)-agonists

Analysis of the practice guidelines of the Dutch College of General Practitioners with respect to the use of blood tests

OBJECTIVE: To determine the consistency among the practice guidelines of the Dutch College of General Practitioners with respect to the use of blood tests. METHODS: The authors evaluated 64 practice guidelines of the Dutch College of General Practitioners. For each guideline, they analyzed each sentence that contained a reference to a blood test to determine the clinical situation in which the test should be performed (the indication) and to determine the tests that should be performed in that situation (the recommended test). An incomplete recommendation refers to a guideline that mentioned a blood test but did not identify the indication for that test. An inconsistency refers to the situation in which one guideline recommended a certain test for a given indication whereas another guideline mentioned the same indication but did not recommend the same test. RESULTS: Twenty-seven practice guidelines mentioned blood tests. Of these, three explicitly recommended not to request blood tests. Five guidelines contained incomplete recommendations, and the authors encountered two inconsistencies among the guidelines. Twenty-three guidelines mentioned blood tests and allowed the authors to identify indications and recommended tests. CONCLUSION: The identification of indications and recommended tests allows evaluation of consistency among practice guidelines. Although some incomplete recommendations and inconsistencies were discovered, the majority of the guidelines provide clear and unambiguous recommendations for blood-test ordering in primary care