Estimating sowing and harvest dates based on the Asian summer monsoon

Sowing and harvest dates are a significant source of uncertainty within crop models, especially for regions where high-resolution data are unavailable or, as is the case in future climate runs, where no data are available at all. Global datasets are not always able to distinguish when wheat is grown in tropical and subtropical regions, and they are also often coarse in resolution. South Asia is one such region where large spatial variation means higher-resolution datasets are needed, together with greater clarity for the timing of the main wheat growing season. Agriculture in South Asia is closely associated with the dominating climatological phenomenon, the Asian summer monsoon (ASM). Rice and wheat are two highly important crops for the region, with rice being mainly cultivated in the wet season during the summer monsoon months and wheat during the dry winter. We present a method for estimating the crop sowing and harvest dates for rice and wheat using the ASM onset and retreat. The aim of this method is to provide a more accurate alternative to the global datasets of cropping calendars than is currently available and generate more representative inputs for climate impact assessments. We first demonstrate that there is skill in the model prediction of monsoon onset and retreat for two downscaled general circulation models (GCMs) by comparing modelled precipitation with observations. We then calculate and apply sowing and harvest rules for rice and wheat for each simulation to climatological estimates of the monsoon onset and retreat for a present day period. We show that this method reproduces the present day sowing and harvest dates for most parts of India. The application of the method to two future simulations demonstrates that the estimated sowing and harvest dates are successfully modified to ensure that the growing season remains consistent with the internal model climate. The study therefore provides a useful way of modelling potential growing season adaptations to changes in future climate

Active Learning with Partial Feedback

While many active learning papers assume that the learner can simply ask for a label and receive it, real annotation often presents a mismatch between the form of a label (say, one among many classes), and the form of an annotation (typically yes/no binary feedback). To annotate examples corpora for multiclass classification, we might need to ask multiple yes/no questions, exploiting a label hierarchy if one is available. To address this more realistic setting, we propose active learning with partial feedback (ALPF), where the learner must actively choose both which example to label and which binary question to ask. At each step, the learner selects an example, asking if it belongs to a chosen (possibly composite) class. Each answer eliminates some classes, leaving the learner with a partial label. The learner may then either ask more questions about the same example (until an exact label is uncovered) or move on immediately, leaving the first example partially labeled. Active learning with partial labels requires (i) a sampling strategy to choose (example, class) pairs, and (ii) learning from partial labels between rounds. Experiments on Tiny ImageNet demonstrate that our most effective method improves 26% (relative) in top-1 classification accuracy compared to i.i.d. baselines and standard active learners given 30% of the annotation budget that would be required (naively) to annotate the dataset. Moreover, ALPF-learners fully annotate TinyImageNet at 42% lower cost. Surprisingly, we observe that accounting for per-example annotation costs can alter the conventional wisdom that active learners should solicit labels for hard examples.Comment: ICLR 201

Cross-Domain Image Matching with Deep Feature Maps

We investigate the problem of automatically determining what type of shoe left an impression found at a crime scene. This recognition problem is made difficult by the variability in types of crime scene evidence (ranging from traces of dust or oil on hard surfaces to impressions made in soil) and the lack of comprehensive databases of shoe outsole tread patterns. We find that mid-level features extracted by pre-trained convolutional neural nets are surprisingly effective descriptors for this specialized domains. However, the choice of similarity measure for matching exemplars to a query image is essential to good performance. For matching multi-channel deep features, we propose the use of multi-channel normalized cross-correlation and analyze its effectiveness. Our proposed metric significantly improves performance in matching crime scene shoeprints to laboratory test impressions. We also show its effectiveness in other cross-domain image retrieval problems: matching facade images to segmentation labels and aerial photos to map images. Finally, we introduce a discriminatively trained variant and fine-tune our system through our proposed metric, obtaining state-of-the-art performance

Hypertension, poor glycemic control, and microalbuminuria in Cuban Americans with type 2 diabetes

Gustavo G Zarini1, Joel C Exebio1, Deva Gundupalli1, Subrata Nath2, Fatma G Huffman11Florida International University, Robert R Stempel School of Public Health, Department of Dietetics and Nutrition, Miami, Florida, USA; 2Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USAPurpose: To investigate to what degree the presence of hypertension (HTN) and poor glycemic control (GC) influences the likelihood of having microalbuminuria (MAU) among Cuban Americans with type 2 diabetes (T2D).Methods: A cross-sectional study conducted in Cuban Americans (n = 179) with T2D. Participants were recruited from a randomly generated mailing list purchased from KnowledgeBase Marketing, Inc. Blood pressure (BP) was measured twice and averaged using an adult size cuff. Glycosylated hemoglobin (A1c) levels were measured from whole blood samples with the Roche Tina-quant method. First morning urine samples were collected from each participant to determine MAU by a semiquantitative assay (ImmunoDip).Results: MAU was present in 26% of Cuban Americans with T2D. A significantly higher percentage of subjects with MA had HTN (P = 0.038) and elevated A1C (P = 0.002) than those with normoalbuminuria. Logistic regression analysis showed that after controlling for covariates, subjects with poor GC were 6.76 times more likely to have MAU if they had hypertension compared with those without hypertension (P = 0.004; 95% confidence interval [CI]: 1.83, 23.05). Conclusion: The clinical significance of these findings emphasizes the early detection of MAU in this Hispanic subgroup combined with BP and good GC, which are fundamentals in preventing and treating diabetes complications and improving individuals’ renal and cardiovascular outcomes.Keywords: blood pressure, A1c, kidney function, cardiovascular disease, Hispanic

Intensive care outcomes in bone marrow transplant recipients: a population-based cohort analysis

Abstract Introduction Intensive care unit (ICU) admission for bone marrow transplant recipients immediately following transplantation is an ominous event, yet the survival of these patients with subsequent ICU admissions is unknown. Our objective was to determine the long-term outcome of bone marrow transplant recipients admitted to an ICU during subsequent hospitalizations. Methods We conducted a population-based cohort analysis of all adult bone marrow transplant recipients who received subsequent ICU care in Ontario, Canada from 1 January 1992 to 31 March 2002. The primary endpoint was mortality at 1 year. Results A total of 2,653 patients received bone marrow transplantation; 504 of which received ICU care during a subsequent hospitalization. Patients receiving any major procedure during their ICU stay had higher 1-year mortality than those patients who received no ICU procedure (87% versus 44%, P < 0.0001). Death rates at 1 year were highest for those receiving mechanical ventilation (87%), pulmonary artery catheterization (91%), or hemodialysis (94%). In combination, the strongest independent predictors of death at 1 year were mechanical ventilation (odds ratio, 7.4; 95% confidence interval, 4.8 to 11.4) and hemodialysis (odds ratio, 8.7; 95% confidence interval, 2.1 to 36.7), yet no combination of procedures uniformly predicted 100% mortality. Conclusion The prognosis of bone marrow transplant recipients receiving ICU care during subsequent hospitalizations is very poor but should not be considered futile

Basis-independent methods for the two-Higgs-doublet model II. The significance of tan(beta)

In the most general two-Higgs-doublet model (2HDM), there is no distinction between the two complex hypercharge-one SU(2) doublet scalar fields, Phi_a (a=1,2). Thus, any two orthonormal linear combinations of these two fields can serve as a basis for the Lagrangian. All physical observables of the model must therefore be basis-independent. For example, tan(beta)=/ is basis-dependent and thus cannot be a physical parameter of the model. In this paper, we provide a basis-independent treatment of the Higgs sector with particular attention to the neutral Higgs boson mass-eigenstates, which generically are not eigenstates of CP. We then demonstrate that all physical Higgs couplings are indeed independent of tan(beta). In specialized versions of the 2HDM, tan(beta) can be promoted to a physical parameter of the Higgs-fermion interactions. In the most general 2HDM, the Higgs-fermion couplings can be expressed in terms of a number of physical "tan(beta)--like" parameters that are manifestly basis-independent. The minimal supersymmetric extension of the Standard Model provides a simple framework for exhibiting such effects.Comment: 56 pages, 5 tables, with Eq. (65) corrected (erratum to appear in Physical Review D

Relationship between MRI Derived Right Ventricular Mass and Left Ventricular Involvement in Patients with Anderson-Fabry Disease

Poster presentationpublished_or_final_versio

GENERATION OF TRANSLUCENT LANGUAGE BY SUPERIMPOSITION OPERATION

We have introduced a new operation called the superimposition operation. The translucent language generated by a given superimposition operation and a language L is the set of words generated by the superimposition of any two words in L. In this paper we study the properties of translucent languages. We also introduce a variant of the operation called Superimposition under control. We examine the properties of languages under this operatio