Generalized multi-photon quantum interference

Non-classical interference of photons lies at the heart of optical quantum information processing. This effect is exploited in universal quantum gates as well as in purpose-built quantum computers that solve the BosonSampling problem. Although non-classical interference is often associated with perfectly indistinguishable photons this only represents the degenerate case, hard to achieve under realistic experimental conditions. Here we exploit tunable distinguishability to reveal the full spectrum of multi-photon non-classical interference. This we investigate in theory and experiment by controlling the delay times of three photons injected into an integrated interferometric network. We derive the entire coincidence landscape and identify transition matrix immanants as ideally suited functions to describe the generalized case of input photons with arbitrary distinguishability. We introduce a compact description by utilizing a natural basis which decouples the input state from the interferometric network, thereby providing a useful tool for even larger photon numbers

Evaluating Knowledge Gaps in Sea-Level Rise Assessments From the United States

There have been many scientific advances regarding future sea-level projections, however it is unclear if these have been transferred to assessment reports used by stakeholders. Here, we present a first-of-its-kind comprehensive analysis of regional sea-level rise (SLR) assessments for the United States (U.S.). We identify variations in time horizons over which regions plan for SLR, with 25 projections from the U.S. Northeast and West that extend to 2150 or beyond, but no projections from the U.S. South beyond 2100. The majority of 2100 projections from the U.S. Northeast (77%) and West (83%) include ranges of future SLR, while 88% of projections from the U.S. South include only single estimates. At least 56% of U.S. communities in the database underestimate the upper end of future SLR compared to the regional projections of the Intergovernmental Panel on Climate Change Sixth Assessment Report

Change in Knowledge of and Adherence to the Low-Sodium Diet in Patients with Heart Failure after Nutrition Education by a Registered Dietitian Nutritionist

Nutrition intervention by a registered dietitian nutritionist (RDN) is effective in improving patients’ knowledge or adherence to low-sodium diet (LSD, <2,000 mg/d); however, changes in knowledge and adherence in heart failure (HF) patients.   have not been simultaneously assessed in the same study Therefore, the objective of the present study was to identify both HF patient sodium knowledge and adherence to the LSD before and after an education session with an RDN. A quasi-experimental study with a one-group, pre-test post-test design was conducted. An RDN conducted a 15-minute individualized nutrition education regarding the LSD at the initial visit. Sodium knowledge was measured by the Parkland Sodium Knowledge Test, and sodium intake was measured by a 29-item sodium-specific food frequency questionnaire created by NutritionQuest© at both the initial and follow-up visits. A total of 71 patients were educated on the LSD and assessed for changes in sodium knowledge and intake at their next visit. Most patients were middle aged, obese, male, and non-Hispanic Black with an education level of greater than 12 years. At the initial visit, the majority of patients were considered knowledgeable but not accordant to the LSD. Following RDN education, sodium knowledge significantly improved and sodium intake significantly decreased. RDNs should be included as members of the HF multidisciplinary team to increase sodium knowledge and reduce sodium intake through individualized nutrition education

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords

Insecticidal Activity of \u3ci\u3eBacillus thuringiensis\u3c/i\u3e Cry1Bh1 against \u3ci\u3eOstrinia nubilalis\u3c/i\u3e (Hübner) (Lepidoptera: Crambidae) and Other Lepidopteran Pests

Bacillus thuringiensis is an important source of insect resistance traits in commercial crops. In an effort to prolong B. thuringiensis trait durability, insect resistance management programs often include combinations of insecticidal proteins that are not cross resistant or have demonstrable differences in their site of action as a means to mitigate the development of resistant insect populations. In this report, we describe the activity spectrum of a novel B. thuringiensis Cry protein, Cry1Bh1, against several lepidopteran pests, including laboratory-selected B. thuringiensis-resistant strains of Ostrinia nubilalis and Heliothis virescens and progeny of field-evolved B. thuringiensis-resistant strains of Plutella xylostella and Spodoptera frugiperda. Cry1Bh1 is active against susceptible and B. thuringiensis-resistant colonies of O. nubilalis, P. xylostella, and H. virescens in laboratory diet-based assays, implying a lack of cross-resistance in these insects. However, Cry1Bh1 is not active against susceptible or Cry1F-resistant S. frugiperda. Further, Cry1Bh1 does not compete with Cry1Fa or Cry1Ab for O. nubilalis midgut brush border membrane binding sites. Cry1Bh1-expressing corn, while not completely resistant to insect damage, provided significantly better leaf protection against Cry1Fa-resistant O. nubilalis than did Cry1Fa-expressing hybrid corn. The lack of cross-resistance with Cry1Ab and Cry1Fa along with independent membrane binding sites in O. nubilalis makes Cry1Bh1 a candidate to further optimize for in-plant resistance to this pest

The draft genome of a socially polymorphic halictid bee, Lasioglossum albipes

Background: Taxa that harbor natural phenotypic variation are ideal for ecological genomic approaches aimed at understanding how the interplay between genetic and environmental factors can lead to the evolution of complex traits. Lasioglossum albipes is a polymorphic halictid bee that expresses variation in social behavior among populations, and common-garden experiments have suggested that this variation is likely to have a genetic component. Results: We present the L. albipes genome assembly to characterize the genetic and ecological factors associated with the evolution of social behavior. The de novo assembly is comparable to other published social insect genomes, with an N50 scaffold length of 602 kb. Gene families unique to L. albipes are associated with integrin-mediated signaling and DNA-binding domains, and several appear to be expanded in this species, including the glutathione-s-transferases and the inositol monophosphatases. L. albipes has an intact DNA methylation system, and in silico analyses suggest that methylation occurs primarily in exons. Comparisons to other insect genomes indicate that genes associated with metabolism and nucleotide binding undergo accelerated evolution in the halictid lineage. Whole-genome resequencing data from one solitary and one social L. albipes female identify six genes that appear to be rapidly diverging between social forms, including a putative odorant receptor and a cuticular protein. Conclusions: L. albipes represents a novel genetic model system for understanding the evolution of social behavior. It represents the first published genome sequence of a primitively social insect, thereby facilitating comparative genomic studies across the Hymenoptera as a whole

Discordance between the predictors of clinical and imaging remission in patients with early rheumatoid arthritis in clinical practice: implications for the use of ultrasound within a treatment to target strategy

Objective: To assess the prevalence, relationship between and predictors of clinical and imaging remission in early rheumatoid arthritis (RA), achieved with treat-to-target management in clinical practice. Methods: A prospective observational study was conducted in patients with new-onset RA. The treatment target was remission by disease activity score (DAS28-CRP<2.6). Twelve month outcomes included DAS28-CRP remission, DAS44-CRP remission, ACR/EULAR Boolean remission (BR) and absent or absent/minimal power Doppler activity (PDA) on ultrasound (US) of 26 joints (total PDA score=0 or ≤1, respectively). Logistic regression was conducted to identify baseline predictors of these outcomes. Results: Of 105 patients with complete 12-month data, the rate of DAS28-CRP remission was 43%, DAS44-CRP remission was 39%, BR was 14%, absent PDA was 40% and absent/minimal PDA was 57%. Amongst patients achieving clinical remission defined by DAS28-CRP, DAS44-CRP or BR, absence of PDA was observed in 42%, 44% and 40%, respectively; absent/minimal PDA was detected in 62%, 66% and 67%, respectively. On multivariable analysis, shorter symptom duration, male gender, fewer tender joints and lower disability were associated with the clinical remission definitions. Lack of osteoarthritis predicted absence of PDA and lower total baseline PDA predicted absent/minimal PDA. Conclusion: DAS28-CRP remission and absence of PDA were observed in almost half of patients, but less than a quarter achieved both. Achievement of BR was rare. The low agreement between any of the clinical and imaging outcomes and differences in their predictors highlight the complex interaction between symptoms and synovitis, with implications for treat-to-target management. Long-term follow-up should determine the most appropriate target

Structural insight into mitochondrial β-barrel outer membrane protein biogenesis.

In mitochondria, -barrel outer membrane proteins mediate protein import, metabolite transport, lipid transport, and biogenesis. The Sorting and Assembly Machinery (SAM) complex consists of three proteins that assemble as a 1:1:1 complex to fold -barrel proteins and insert them into the mitochondrial outer membrane. We report cryoEM structures of the SAM complex from Myceliophthora thermophila, which show that Sam50 forms a 16-stranded transmembrane -barrel with a single polypeptide-transport associated (POTRA) domain extending into the intermembrane space. Sam35 and Sam37 are located on the cytosolic side of the outer membrane, with Sam35 capping Sam50, and Sam37 interacting extensively with Sam35. Sam35 and Sam37 each adopt a GST-like fold, with no functional, structural, or sequence similarity to their bacterial counterparts. Structural analysis shows how the Sam50 barrel opens a lateral gate to accommodate its substrates

The pheromones of laying workers in two honeybee sister species : Apis cerana and Apis mellifera

When a honeybee colony loses its queen, workers activate their ovaries and begin to lay eggs. This is accompanied by a shift in their pheromonal bouquet, which becomes more queen like. Workers of the Asian hive bee Apis cerana show unusually high levels of ovary activation and this can be interpreted as evidence for a recent evolutionary arms race between queens and workers over worker reproduction in this species. To further explore this, we compared the rate of pheromonal bouquet change between two honeybee sister species of Apis cerana and Apis mellifera under queenright and queenless conditions. We show that in both species, the pheromonal components HOB, 9-ODA, HVA, 9-HDA, 10-HDAA and 10-HDA have significantly higher amounts in laying workers than in non-laying workers. In the queenright colonies of A. mellifera and A. cerana the ratios (9-ODA)/ (9-ODA+9-HDA+10-HDAA+10-HDA) are not significantly different between the two species, but in queenless A. cerana colonies the ratio is significant higher than in A. mellifera, suggesting that in A. cerana, the workers’ pheromonal bouquet is dominated by the queen compound, 9-ODA. The amount of 9-ODA in laying A. cerana workers increase by over 585% compared to the non-laying workers, that is 6.75 times higher than in A. mellifera were laying workers only had 86% more 9-ODA compared to non-laying workers.Financial support was provided to Ken Tan by Key Laboratory of Tropical Forest Ecology of Xishuangbanna Tropical Botanical Garden, and Yunnan Agricultural University.http://www.springer.com/life+sci/zoology/journal/359hb2013ab201