Competing magnetic fluctuations and orders in a multiorbital model of doped SrCo2_2As2_2

We revisit the intriguing magnetic behavior of the paradigmatic itinerant frustrated magnet $\rm{Sr}\rm{Co}_2\rm{As}_2$, which shows strong and competing magnetic fluctuations yet does not develop long-range magnetic order. By calculating the static spin susceptibility $\chi(\mathbf{q})$ within a realistic sixteen orbital Hubbard-Hund model, we determine the leading instability to be ferromagnetic (FM). We then explore the effect of doping and calculate the critical Hubbard interaction strength $U_c$ that is required for the development of magnetic order. We find that $U_c$ decreases under electron doping and with increasing Hund's coupling $J$, but increases rapidly under hole doping. This suggests that magnetic order could possibly emerge under electron doping but not under hole doping, which agrees with experimental findings. We map out the leading magnetic instability as a function of doping and Hund's coupling and find several antiferromagnetic phases in addition to FM. We also quantify the degree of itinerant frustration in the model and resolve the contributions of different orbitals to the magnetic susceptibility. Finally, we discuss the dynamic spin susceptibility, $\chi(\mathbf{q}, \omega)$, at finite frequencies, where we recover the anisotropy of the peaks at $\mathbf{Q}_\pi = (\pi, 0)$ and $(0, \pi)$ observed by inelastic neutron scattering that is associated with the phenomenon of itinerant magnetic frustration. By comparing results between theory and experiment, we conclude that the essential experimental features of doped SrCo$_2$As$_2$ are well captured by a Hubbard-Hund multiorbital model if one considers a small shift of the chemical potential towards hole doping.Comment: 19 pages, 12 figure

The role of honey in the ecology of the hive: Nutrition, detoxification, longevity, and protection against hive pathogens

Honey is the source of energy for the European honey bee, Apis mellifera. Beyond simple nutrition and a hedge against the seasonal, geographic, and chemical unpredictability of nectar, honey has properties that protect the hive against various stresses. Enzyme-mediated detoxification during honey ripening neutralizes potentially toxic phytochemicals, and bees that consume honey have enhanced tolerance to other ingested toxins. Catalase and antioxidant phenolics protect honey bees from oxidative damage caused by reactive oxygen species, promoting their longevity. Phytochemical components of honey and microRNAs have the potential to influence developmental pathways, with diet playing a large role in honey bee caste determination. Components of honey mediate stress response and promote cold tolerance during overwintering. Honey has a suite of antimicrobial mechanisms including osmotic pressure, low water activity, low pH, hydrogen peroxide, and plant-, honey bee-, and microbiota-derived compounds such as phytochemicals and antimicrobial peptides. Certain types of honey, particularly polyfloral honeys, have been shown to inhibit important honey bee pathogens including the bacteria responsible for American and European Foulbrood, the microsporidian Nosema ceranae, and the fungi responsible for Stonebrood. Understanding the diverse functional properties of honey has far-ranging implications for honey bee and hive health and management by beekeepers.</jats:p

Towards Demystifying Dimensions of Source Code Embeddings

Source code representations are key in applying machine learning techniques for processing and analyzing programs. A popular approach in representing source code is neural source code embeddings that represents programs with high-dimensional vectors computed by training deep neural networks on a large volume of programs. Although successful, there is little known about the contents of these vectors and their characteristics. In this paper, we present our preliminary results towards better understanding the contents of code2vec neural source code embeddings. In particular, in a small case study, we use the code2vec embeddings to create binary SVM classifiers and compare their performance with the handcrafted features. Our results suggest that the handcrafted features can perform very close to the highly-dimensional code2vec embeddings, and the information gains are more evenly distributed in the code2vec embeddings compared to the handcrafted features. We also find that the code2vec embeddings are more resilient to the removal of dimensions with low information gains than the handcrafted features. We hope our results serve a stepping stone toward principled analysis and evaluation of these code representations.Comment: 1st ACM SIGSOFT International Workshop on Representation Learning for Software Engineering and Program Languages, Co-located with ESEC/FSE (RL+SE&PL'20

Genome-wide signatures of complex introgression and adaptive evolution in the big cats.

The great cats of the genus Panthera comprise a recent radiation whose evolutionary history is poorly understood. Their rapid diversification poses challenges to resolving their phylogeny while offering opportunities to investigate the historical dynamics of adaptive divergence. We report the sequence, de novo assembly, and annotation of the jaguar (Panthera onca) genome, a novel genome sequence for the leopard (Panthera pardus), and comparative analyses encompassing all living Panthera species. Demographic reconstructions indicated that all of these species have experienced variable episodes of population decline during the Pleistocene, ultimately leading to small effective sizes in present-day genomes. We observed pervasive genealogical discordance across Panthera genomes, caused by both incomplete lineage sorting and complex patterns of historical interspecific hybridization. We identified multiple signatures of species-specific positive selection, affecting genes involved in craniofacial and limb development, protein metabolism, hypoxia, reproduction, pigmentation, and sensory perception. There was remarkable concordance in pathways enriched in genomic segments implicated in interspecies introgression and in positive selection, suggesting that these processes were connected. We tested this hypothesis by developing exome capture probes targeting ~19,000 Panthera genes and applying them to 30 wild-caught jaguars. We found at least two genes (DOCK3 and COL4A5, both related to optic nerve development) bearing significant signatures of interspecies introgression and within-species positive selection. These findings indicate that post-speciation admixture has contributed genetic material that facilitated the adaptive evolution of big cat lineages

Toxic metal enrichment and boating intensity: sediment records of antifoulant copper in shallow lakes of eastern England

Tributyltin (TBT), an aqueous biocide derived from antifouling paint pollution, is known to have impacted coastal marine ecosystems, and has been reported in the sediment of the Norfolk and Suffolk Broads, a network of rivers and shallow lakes in eastern England. In the marine environment, the 1987 TBT ban has resulted in expanded use of alternative biocides, raising the question of whether these products too have impacted the Broads ecosystem and freshwaters in general. Here we examine the lake sediment record in the Norfolk and Suffolk Broads for contamination by copper (Cu) (as an active biocide agent) and zinc (Zn) (as a component of booster biocides), to assess their occurrence and potential for causing environmental harm in freshwater ecosystems. We find that, after the introduction of leisure boating, there is a statistically significant difference in Cu enrichment between heavily and lightly boated sites, while no such difference exists prior to this time. At the heavily boated sites the onset of Cu enrichment coincides with a period of rapid increase in leisure boating. Such enrichment is maintained to the present day, with some evidence of continued increase. We conclude that Cu-based antifouling has measurably contaminated lakes exposed to boating, at concentrations high enough to cause ecological harm. Similar findings can be expected at other boated freshwater ecosystems elsewhere in the world

Consistent model of magnetism in ferropnictides

The discovery of superconductivity in LaFeAsO introduced the ferropnictides as a major new class of superconducting compounds with critical temperatures second only to cuprates. The presence of magnetic iron makes ferropnictides radically different from cuprates. Antiferromagnetism of the parent compounds strongly suggests that superconductivity and magnetism are closely related. However, the character of magnetic interactions and spin fluctuations in ferropnictides, in spite of vigorous efforts, has until now resisted understanding within any conventional model of magnetism. Here we show that the most puzzling features can be naturally reconciled within a rather simple effective spin model with biquadratic interactions, which is consistent with electronic structure calculations. By going beyond the Heisenberg model, this description explains numerous experimentally observed properties, including the peculiarities of the spin wave spectrum, thin domain walls, crossover from first to second order phase transition under doping in some compounds, and offers new insight in the occurrence of the nematic phase above the antiferromagnetic phase transition.Comment: 5 pages, 3 figures, revtex

Finite element-based micromechanical modeling of the influence of phase properties on the elastic response of cementitious mortars

This study reports the influence of inclusion stiffness and its distribution on the stress distributions in the microstructural phases of different cementitious mortars using microstructure-guided finite element simulations. Randomly generated periodic microstructures with single/multiple inclusion sizes and random spatial distribution, subjected to periodic boundary conditions and a strain-controlled virtual testing regime are chosen for final analysis. Numerical simulations reveal: (i) the differences in locations/magnitudes of stress concentrations as a function of inclusion stiffness and size distribution, and (ii) the sometimes detrimental influence of matrix and interface stiffening/strengthening on the overall composite response, leading to material design strategies when non-conventional inclusions are used in cementitious systems for special properties. The constitutive behavior in the linear elastic regime is extracted based on the predicted dominant principal stresses and strains in the representative area element. Thus, in addition to the microstructural phase stresses, this methodology also provides predictions of the composite elastic modulus, which are observed to be more reliable than those obtained from analytical prediction models

Key features of palliative care service delivery to Indigenous peoples in Australia, New Zealand, Canada and the United States: A comprehensive review

Background: Indigenous peoples in developed countries have reduced life expectancies, particularly from chronic diseases. The lack of access to and take up of palliative care services of Indigenous peoples is an ongoing concern. Objectives: To examine and learn from published studies on provision of culturally safe palliative care service delivery to Indigenous people in Australia, New Zealand (NZ), Canada and the United States of America (USA); and to compare Indigenous peoples’ preferences, needs, opportunities and barriers to palliative care. Methods: A comprehensive search of multiple databases was undertaken. Articles were included if they were published in English from 2000 onwards and related to palliative care service delivery for Indigenous populations; papers could use quantitative or qualitative approaches. Common themes were identified using thematic synthesis. Studies were evaluated using Daly’s hierarchy of evidence-for-practice in qualitative research. Results: Of 522 articles screened, 39 were eligible for inclusion. Despite diversity in Indigenous peoples’ experiences across countries, some commonalities were noted in the preferences for palliative care of Indigenous people: to die close to or at home; involvement of family; and the integration of cultural practices. Barriers identified included inaccessibility, affordability, lack of awareness of services, perceptions of palliative care, and inappropriate services. Identified models attempted to address these gaps by adopting the following strategies: community engagement and ownership; flexibility in approach; continuing education and training; a whole-of-service approach; and local partnerships among multiple agencies. Better engagement with Indigenous clients, an increase in number of palliative care patients, improved outcomes, and understanding about palliative care by patients and their families were identified as positive achievements. Conclusions: The results provide a comprehensive overview of identified effective practices with regards to palliative care delivered to Indigenous populations to guide future program developments in this field. Further research is required to explore the palliative care needs and experiences of Indigenous people living in urban areas

Multiobjective optimization of classifiers by means of 3-D convex hull based evolutionary algorithms

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The receiver operating characteristic (ROC) and detection error tradeoff(DET) curves are frequently used in the machine learning community to analyze the performance of binary classifiers. Recently, the convex-hull-based multiobjective genetic programming algorithm was proposed and successfully applied to maximize the convex hull area for binary classifi- cation problems by minimizing false positive rate and maximizing true positive rate at the same time using indicator-based evolutionary algorithms. The area under the ROC curve was used for the performance assessment and to guide the search. Here we extend this re- search and propose two major advancements: Firstly we formulate the algorithm in detec- tion error tradeoffspace, minimizing false positives and false negatives, with the advantage that misclassification cost tradeoffcan be assessed directly. Secondly, we add complexity as an objective function, which gives rise to a 3D objective space (as opposed to a 2D pre- vious ROC space). A domain specific performance indicator for 3D Pareto front approxima- tions, the volume above DET surface, is introduced, and used to guide the indicator-based evolutionary algorithm to find optimal approximation sets. We assess the performance of the new algorithm on designed theoretical problems with different geometries of Pareto fronts and DET surfaces, and two application-oriented benchmarks: (1) Designing spam filters with low numbers of false rejects, false accepts, and low computational cost us- ing rule ensembles, and (2) finding sparse neural networks for binary classification of test data from the UCI machine learning benchmark. The results show a high performance of the new algorithm as compared to conventional methods for multicriteria optimization