The changing needs with time for mineral nutrition of organic stone fruit orchard under Mediterranean conditions

Mediterranean climatic conditions for stone fruit production are good but soil fertility is low, mainly due to low (< 2.0%) soil organic matter (OM). Consequently, conventional growers apply high fertiliser rates (typically ~350 Kg N ha-1 yr-1). Our main objectives were to compare the effects of 2 modes of nitrogen nutrition, suitable for organically certified orchard vs a conventional control on tree development, yield, and some soil chemical, physical and biological properties. The orchard is located on a Grumosol soil, in the Jezreel Valley, Israel and is treated organically in terms of plant protection and weed control. The orchard was planted to peach, plums and nectarines in 1998, all grafted onto rootstock CV. 677. The tested treatments were: A. conventional control, receiving an average of 350 Kg N ha-1 yr-1; B. fertilization using cattle manure compost (40 m3ha-1 yr-1) + feather meal (1 tonne ha-1 yr-1); and C. a combination of the same amount of compost + 500 Kg feather meal ha-1 yr-1 + leguminous cover crop (Alfalfa, Medicago sativa cv. Gilboa). The cover crop was mowed 7–8 times per year. There were five replicates per treatment, of nine trees per replicate and the experiment was arranged in a randomised block design. The experiment lasted 6 years. OM content of the native soil (5–30 cm) was 1.8–2.0%. By 2003 the OM content of the conventional control treatment remained stable; that of treatment B increased by 36% while that of treatment C increased by 91%. This change was refl ected in a clear and statistically significant change in soil’s bulk density values which were 0.80, 0.73 and 0.71 gr cm3 for treatments A, B and C, respectively. At the beginning of the experiment levels of soil nitrate, phosphate and potassium ions were somewhat lower in treatments B and C than those in A but they became consistently higher after 2–3 years. The levels of these ions in the 30–60 cm soil layer followed the same trend at a 1–2 years lag. Nitrification capacity of the soils of treatments B and C were twice as high as those of treatment A. Consequently, beginning 2002 application rates of organic amendments were reduced. Yet, no decline in nutrients levels in the organic treatments could be detected over the period 2002–2004, presumably due to continued mineralisation of the OM pool. In 2004 various soil microbial characteristics (microbial counts, fl uorescein diacetate hydrolytic activity, functional richness and diversity) were determined. In all these parameters the organic treatments showed higher levels than treatment A. From the autumn of 2002 on, stem circumference are similar for all treatments and for all species. No statistical differences could be found among the treatments in any of the tested species for the 3 year cumulative yields. It can be concluded that once a significant buildup of organic matter in the soil is occurring, organic matter application can be reduced considerably, as a signifi cant soil’s potential productivity has been built

Sparse image reconstruction for molecular imaging

The application that motivates this paper is molecular imaging at the atomic level. When discretized at sub-atomic distances, the volume is inherently sparse. Noiseless measurements from an imaging technology can be modeled by convolution of the image with the system point spread function (psf). Such is the case with magnetic resonance force microscopy (MRFM), an emerging technology where imaging of an individual tobacco mosaic virus was recently demonstrated with nanometer resolution. We also consider additive white Gaussian noise (AWGN) in the measurements. Many prior works of sparse estimators have focused on the case when H has low coherence; however, the system matrix H in our application is the convolution matrix for the system psf. A typical convolution matrix has high coherence. The paper therefore does not assume a low coherence H. A discrete-continuous form of the Laplacian and atom at zero (LAZE) p.d.f. used by Johnstone and Silverman is formulated, and two sparse estimators derived by maximizing the joint p.d.f. of the observation and image conditioned on the hyperparameters. A thresholding rule that generalizes the hard and soft thresholding rule appears in the course of the derivation. This so-called hybrid thresholding rule, when used in the iterative thresholding framework, gives rise to the hybrid estimator, a generalization of the lasso. Unbiased estimates of the hyperparameters for the lasso and hybrid estimator are obtained via Stein's unbiased risk estimate (SURE). A numerical study with a Gaussian psf and two sparse images shows that the hybrid estimator outperforms the lasso.Comment: 12 pages, 8 figure

Serendipity in Science

Serendipity plays an important role in scientific discovery. Indeed, many of the most important breakthroughs, ranging from penicillin to the electric battery, have been made by scientists who were stimulated by a chance exposure to unsought but useful information. However, not all scientists are equally likely to benefit from such serendipitous exposure. Although scholars generally agree that scientists with a prepared mind are most likely to benefit from serendipitous encounters, there is much less consensus over what precisely constitutes a prepared mind, with some research suggesting the importance of openness and others emphasizing the need for deep prior experience in a particular domain. In this paper, we empirically investigate the role of serendipity in science by leveraging a policy change that exogenously shifted the shelving location of journals in university libraries and subsequently exposed scientists to unsought scientific information. Using large-scale data on 2.4 million papers published in 9,750 journals by 520,000 scientists at 115 North American research universities, we find that scientists with greater openness are more likely to benefit from serendipitous encounters. Following the policy change, these scientists tended to cite less familiar and newer work, and ultimately published papers that were more innovative. By contrast, we find little effect on innovativeness for scientists with greater depth of experience, who, in our sample, tended to cite more familiar and older work following the policy change

Geometric and Photometric Data Fusion in Non-Rigid Shape Analysis

In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape descriptors. Our construction is based on the definition of a diffusion process on the shape manifold embedded into a high-dimensional space where the embedding coordinates represent the photometric information. Experimental results show that such data fusion is useful in coping with different challenges of shape analysis where pure geometric and pure photometric methods fai

Active Printed Materials for Complex Self-Evolving Deformations

We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus

Raised erythrocyte creatine in patients with pulmonary arterial hypertension – Evidence for subclinical hemolysis

SummaryBackgroundPulmonary arterial hypertension (PAH) has been associated with hemolytic conditions such as sickle cell disease but the possible role of hemolysis in the pathogenesis or pathophysiology of other forms of PAH has not been studied. Erythrocyte lifespan is the gold-standard test of hemolysis and may be measured by assaying erythrocyte creatine (EC) levels. EC decreases as the erythrocyte ages, so patients with hemolysis have high EC levels.MethodsWe measured EC and other parameters of hemolysis in patients with idiopathic and connective tissue associated PAH and normal controls.ResultsIn patients with PAH (n = 40), EC levels were higher than in controls n = 30 (patients EC 1.72 mcmol/g HgB 95%CI[1.51, 1.96], controls EC 1.05 mcmol/g HgB [0.93, 1.19], p < 0.0001). High levels of EC correlated with worse 6 min walk (r = −0.42, p < 0.0001) and worse functional class (p = 0.002). Other indirect indices of hemolysis (total lactate dehydrogenase, red cell distribution width) were also increased in patients with PAH relative to controls.ConclusionsThere is evidence of subclinical hemolysis in patients with PAH, and higher levels of hemolysis are associated with poorer exercise capacity

Experimental Tools to Study Molecular Recognition within the Nanoparticle Corona

Advancements in optical nanosensor development have enabled the design of sensors using synthetic molecular recognition elements through a recently developed method called Corona Phase Molecular Recognition (CoPhMoRe). The synthetic sensors resulting from these design principles are highly selective for specific analytes, and demonstrate remarkable stability for use under a variety of conditions. An essential element of nanosensor development hinges on the ability to understand the interface between nanoparticles and the associated corona phase surrounding the nanosensor, an environment outside of the range of traditional characterization tools, such as NMR. This review discusses the need for new strategies and instrumentation to study the nanoparticle corona, operating in both in vitro and in vivo environments. Approaches to instrumentation must have the capacity to concurrently monitor nanosensor operation and the molecular changes in the corona phase. A detailed overview of new tools for the understanding of CoPhMoRe mechanisms is provided for future applications.Juvenile Diabetes Research Foundation InternationalMcGovern Institute for Brain Research at MIT. Neurotechnology (MINT) ProgramNational Science Foundation (U.S.) (Postdoctoral Research Fellowship Award DBI-1306229)Burroughs Wellcome Fund (Grant Award 1013994)German Science Foundatio

Quantitative Tissue Spectroscopy of Near Infrared Fluorescent Nanosensor Implants

Implantable, near infrared (nIR) fluorescent nanosensors are advantageous for in vivo monitoring of biological analytes since they can be rendered selective for particular target molecule while utilizing their unique optical properties and the nIR tissue transparency window for information transfer without an internal power source or telemetry. However, basic questions remain regarding the optimal encapsulation platform, geometrical properties, and concentration ranges required for effective signal to noise ratio through biological tissue. In this work, we systematically explore these variables quantitatively to optimize the performance of such optical nanosensors for biomedical applications. We investigate both alginate and polyethylene glycol (PEG) as model hydrogel systems, encapsulating d(GT)[subscript 15] ssDNA-wrapped single walled carbon nanotubes (SWNT) as model fluorescent nanoparticle sensors, responsive to riboflavin. Hydrogel sensors implanted 0.5 mm into thick tissue samples cause 50% reduction of initial fluorescence intensity, allowing an optical detection limit of 5.4 mm and 5.1 mm depth in tissue for alginate and PEG gels, respectively, at a SWNT concentration of 10 mg L−1, and 785 nm laser excitation of 80 mW and 30 s exposure. These findings are supported with in vivo nIR fluorescent imaging of SWNT hydrogels implanted subcutaneously in mice. For the case of SWNT, we find that the alginate system is preferable in terms of emission intensity, sensor response, rheological properties, and shelf life.National Institutes of Health (U.S.) (T32 Training Grant in Environmental Toxicology ES007020)National Cancer Institute (U.S.) (Grant P01 CA26731)National Institute of Environmental Health Sciences (Grant P30 ES002109)Arnold and Mabel Beckman Foundation (Young Investigator Award)National Science Foundation (U.S.) (Presidential Early Career Award for Scientists and Engineers)MIT-Technion FellowshipSamsung Scholarship FoundationSanofi Aventis (Firm) (Biomedical Innovation Grant