On Approximately Symmetric Informationally Complete Positive Operator-Valued Measures and Related Systems of Quantum States

We address the problem of constructing positive operator-valued measures (POVMs) in finite dimension $n$ consisting of $n^2$ operators of rank one which have an inner product close to uniform. This is motivated by the related question of constructing symmetric informationally complete POVMs (SIC-POVMs) for which the inner products are perfectly uniform. However, SIC-POVMs are notoriously hard to construct and despite some success of constructing them numerically, there is no analytic construction known. We present two constructions of approximate versions of SIC-POVMs, where a small deviation from uniformity of the inner products is allowed. The first construction is based on selecting vectors from a maximal collection of mutually unbiased bases and works whenever the dimension of the system is a prime power. The second construction is based on perturbing the matrix elements of a subset of mutually unbiased bases. Moreover, we construct vector systems in \C^n which are almost orthogonal and which might turn out to be useful for quantum computation. Our constructions are based on results of analytic number theory.Comment: 29 pages, LaTe

Ptychographic X-ray tomography reveals additive zoning in nanocomposite single crystals

Single crystals containing nanoparticles represent a unique class of nanocomposites whose properties are defined by both their compositions and the structural organization of the dispersed phase in the crystalline host. Yet, there is still a poor understanding of the relationship between the synthesis conditions and the structures of these materials. Here ptychographic X-ray computed tomography is used to visualize the three-dimensional structures of two nanocomposite crystals – single crystals of calcite occluding diblock copolymer worms and vesicles. This provides unique information about the distribution of the copolymer nano-objects within entire, micron-sized crystals with nanometer spatial resolution and reveals how occlusion is governed by factors including the supersaturation and calcium concentration. Both nanocomposite crystals are seen to exhibit zoning effects that are governed by the solution composition and interactions of the additives with specific steps on the crystal surface. Additionally, the size and shape of the occluded vesicles varies according to their location within the crystal, and therefore the solution composition at the time of occlusion. This work contributes to our understanding of the factors that govern nanoparticle occlusion within crystalline materials, where this will ultimately inform the design of next generation nanocomposite materials with specific structure/property relationships

Droplet Microfluidics XRD Identifies Effective Nucleating Agents for Calcium Carbonate

The ability to control crystallization reactions is required in a vast range of processes including the production of functional inorganic materials and pharmaceuticals and the prevention of scale. However, it is currently limited by a lack of understanding of the mechanisms underlying crystal nucleation and growth. To address this challenge, it is necessary to carry out crystallization reactions in well‐defined environments, and ideally to perform in situ measurements. Here, a versatile microfluidic synchrotron‐based technique is presented to meet these demands. Droplet microfluidic‐coupled X‐ray diffraction (DMC‐XRD) enables the collection of time‐resolved, serial diffraction patterns from a stream of flowing droplets containing growing crystals. The droplets offer reproducible reaction environments, and radiation damage is effectively eliminated by the short residence time of each droplet in the beam. DMC‐XRD is then used to identify effective particulate nucleating agents for calcium carbonate and to study their influence on the crystallization pathway. Bioactive glasses and a model material for mineral dust are shown to significantly lower the induction time, highlighting the importance of both surface chemistry and topography on the nucleating efficiency of a surface. This technology is also extremely versatile, and could be used to study dynamic reactions with a wide range of synchrotron‐based techniques

Collusion through Joint R&D: An Empirical Assessment

This paper tests whether upstream R&D cooperation leads to downstream collusion. We consider an oligopolistic setting where firms enter in research joint ventures (RJVs) to lower production costs or coordinate on collusion in the product market. We show that a sufficient condition for identifying collusive behavior is a decline in the market share of RJV-participating firms, which is also necessary and sufficient for a decrease in consumer welfare. Using information from the US National Cooperation Research Act, we estimate a market share equation correcting for the endogeneity of RJV participation and R&D expenditures. We find robust evidence that large networks between direct competitors – created through firms being members in several RJVs at the same time – are conducive to collusive outcomes in the product market which reduce consumer welfare. By contrast, RJVs among non-competitors are efficiency enhancing

Wake up, wake up! It's me! It's my life! patient narratives on person-centeredness in the integrated care context: a qualitative study

Person-centered care emphasizes a holistic, humanistic approach that puts patients first, at the center of medical care. Person-centeredness is also considered a core element of integrated care. Yet typologies of integrated care mainly describe how patients fit within integrated services, rather than how services fit into the patient's world. Patient-centeredness has been commonly defined through physician's behaviors aimed at delivering patient-centered care. Yet, it is unclear how 'person-centeredness' is realized in integrated care through the patient voice. We aimed to explore patient narratives of person-centeredness in the integrated care context

On the role of theory and modeling in neuroscience

In recent years, the field of neuroscience has gone through rapid experimental advances and extensive use of quantitative and computational methods. This accelerating growth has created a need for methodological analysis of the role of theory and the modeling approaches currently used in this field. Toward that end, we start from the general view that the primary role of science is to solve empirical problems, and that it does so by developing theories that can account for phenomena within their domain of application. We propose a commonly-used set of terms - descriptive, mechanistic, and normative - as methodological designations that refer to the kind of problem a theory is intended to solve. Further, we find that models of each kind play distinct roles in defining and bridging the multiple levels of abstraction necessary to account for any neuroscientific phenomenon. We then discuss how models play an important role to connect theory and experiment, and note the importance of well-defined translation functions between them. Furthermore, we describe how models themselves can be used as a form of experiment to test and develop theories. This report is the summary of a discussion initiated at the conference Present and Future Theoretical Frameworks in Neuroscience, which we hope will contribute to a much-needed discussion in the neuroscientific community

Environmental Factors in the Relapse and Recurrence of Inflammatory Bowel Disease:A Review of the Literature

The causes of relapse in patients with Crohn's disease (CD) and ulcerative colitis (UC) are largely unknown. This paper reviews the epidemiological and clinical data on how medications (non-steroidal anti-inflammatory drugs, estrogens and antibiotics), lifestyle factors (smoking, psychological stress, diet and air pollution) may precipitate clinical relapses and recurrence. Potential biological mechanisms include: increasing thrombotic tendency, imbalances in prostaglandin synthesis, alterations in the composition of gut microbiota, and mucosal damage causing increased permeability

Temperature and spatial connectivity drive patterns in freshwater macroinvertebrate diversity across the Arctic

Warming in the Arctic is predicted to change freshwater biodiversity through loss of unique taxa and northward range expansion of lower latitude taxa. Detecting such changes requires establishing circumpolar baselines for diversity, and understanding the primary drivers of diversity. We examined benthic macroinvertebrate diversity using a circumpolar dataset of &gt;1,500 Arctic lake and river sites. Rarefied α diversity within catchments was assessed along latitude and temperature gradients. Community composition was assessed through region-scale analysis of β diversity and its components (nestedness and turnover), and analysis of biotic–abiotic relationships. Rarefied α diversity of lakes and rivers declined with increasing latitude, although more strongly across mainland regions than islands. Diversity was strongly related to air temperature, with the lowest diversity in the coldest catchments. Regional dissimilarity was highest when mainland regions were compared with islands, suggesting that connectivity limitations led to the strongest dissimilarity. High contributions of nestedness indicated that island regions contained a subset of the taxa found in mainland regions. High Arctic rivers and lakes were predominately occupied by Chironomidae and Oligochaeta, whereas Ephemeroptera, Plecoptera, and Trichoptera taxa were more abundant at lower latitudes. Community composition was strongly associated with temperature, although geology and precipitation were also important correlates. The strong association with temperature supports the prediction that warming will increase Arctic macroinvertebrate diversity, although low diversity on islands suggests that this increase will be limited by biogeographical constraints. Long-term harmonised monitoring across the circumpolar region is necessary to detect such changes to diversity and inform science-based management.</p

Determinants of self-reporting under the European corporate leniency program

We empirically investigate the determinants of self-reporting under the European corporate leniency program. Applying a data set consisting of 442 firm groups that participated in 76 cartels decided by the European Commission between 2000 and 2011, we find that the probability of a firm becoming the chief witness increases with its character as repeat offender, the size of the expected basic fine, the number of countries active in one group as well as the size of the firm’s share in the cartelized market. Our results have important implications for an effective prosecution of anti-cartel law infringers