Hexaaquazinc(II) dinitrate bis[5-(pyridinium-3-yl)tetrazol-1-ide]

Indexación: Scopus.Funding for this research was provided by: Fondecyt Regular (award No. 1151527); Proyecto REDES ETAPA INICIAL, Convocatoria 2017 (award No. REDI170423); Millennium Institute for Research in Optics (MIRO); Basal USA (award No. 1799).Hexaaquazinc(II) dinitrate 5-(pyridinium-3-yl)tetrazol-1-ide, [Zn(H2 O)6](NO 3)2 ·2C6H5 N 5, crystallizes in the space group P. The asymmetric unit contains one zwitterionic 5-(pyridinium-3-yl)tetrazol-1-ide molecule, one NO3-anion and one half of a [Zn(H2 O)6]2+ cation (symmetry). The pyridinium and tetrazolide rings in the zwitterion are nearly coplanar, with a dihedral angle of 5.4 (2)°. Several O-H..N and N-H..O hydrogen-bonding interactions exist between the [Zn(H2 O)6]2+ cation and the N atoms of the tetrazolide ring, and between the nitrate anions and the N-H groups of the pyridinium ring, respectively, giving rise to a three-dimensional network. The 5-(pyridinium-3-yl)tetrazol-1-ide molecules show parallel-displaced π-π stacking interactions; the centroid-centroid distance between adjacent tetrazolide rings is 3.6298 (6) Å and that between the pyridinium and tetrazolide rings is 3.6120 (5) Å. © 2018 Chi-Duran et al.http://journals.iucr.org/e/issues/2018/09/00/cq2025/index.htm

Noncanonical Quantization of Gravity. I. Foundations of Affine Quantum Gravity

The nature of the classical canonical phase-space variables for gravity suggests that the associated quantum field operators should obey affine commutation relations rather than canonical commutation relations. Prior to the introduction of constraints, a primary kinematical representation is derived in the form of a reproducing kernel and its associated reproducing kernel Hilbert space. Constraints are introduced following the projection operator method which involves no gauge fixing, no complicated moduli space, nor any auxiliary fields. The result, which is only qualitatively sketched in the present paper, involves another reproducing kernel with which inner products are defined for the physical Hilbert space and which is obtained through a reduction of the original reproducing kernel. Several of the steps involved in this general analysis are illustrated by means of analogous steps applied to one-dimensional quantum mechanical models. These toy models help in motivating and understanding the analysis in the case of gravity.Comment: minor changes, LaTeX, 37 pages, no figure

Dispersionful analogues of Benney's equations and NN-wave systems

We recall Krichever's construction of additional flows to Benney's hierarchy, attached to poles at finite distance of the Lax operator. Then we construct a ``dispersionful'' analogue of this hierarchy, in which the role of poles at finite distance is played by Miura fields. We connect this hierarchy with $N$-wave systems, and prove several facts about the latter (Lax representation, Chern-Simons-type Lagrangian, connection with Liouville equation, $\tau$-functions).Comment: 12 pages, latex, no figure

Compatible Poisson-Lie structures on the loop group of SL2SL_{2}

We define a 1-parameter family of $r$-matrices on the loop algebra of $sl_{2}$, defining compatible Poisson structures on the associated loop group, which degenerate into the rational and trigonometric structures, and study the Manin triples associated to them.Comment: 5 pages, amstex, no figure

IntelliBeeHive: An Automated Honey Bee, Pollen, and Varroa Destructor Monitoring System

—study, we developed a honey bee monitoring system that aims to enhance our understanding of Colony Collapse Disorder, honey bee behavior, population decline, and overall hive health. The system is positioned at the hive entrance providing real-time data, enabling beekeepers to closely monitor the hive’s activity and health through an account-based website. Using machine learning, our monitoring system can accurately track honey bees, monitor pollen gathering activity, and detect Varroa mites, all without causing any disruption to the honey bees. Moreover, we have ensured that the development of this monitoring system utilizes cost-effective technology, making it accessible to apiaries of various scales, including hobbyists, commercial beekeeping businesses, and researchers. The inference models used to detect honey bees, pollen, and mites are based on the YOLOv7-tiny architecture trained with our own data. The F1-score for honey bee model recognition is 0.95 and the precision and recall value is 0.981. For our pollen and mite object detection model F1-score is 0.95 and the precision and recall value is 0.821 for pollen and 0.996 for ”mite”. The overall performance of our IntelliBeeHive system demonstrates its effectiveness in monitoring the honey bee’s activity, achieving an accuracy of 96.28% in tracking and our pollen model achieved a F1-score of 0.831

IntelliBeeHive: An Automated Honey Bee, Pollen, and Varroa Destructor Monitoring System

Utilizing computer vision and the latest technological advancements, in this study, we developed a honey bee monitoring system that aims to enhance our understanding of Colony Collapse Disorder, honey bee behavior, population decline, and overall hive health. The system is positioned at the hive entrance providing real-time data, enabling beekeepers to closely monitor the hive's activity and health through an account-based website. Using machine learning, our monitoring system can accurately track honey bees, monitor pollen-gathering activity, and detect Varroa mites, all without causing any disruption to the honey bees. Moreover, we have ensured that the development of this monitoring system utilizes cost-effective technology, making it accessible to apiaries of various scales, including hobbyists, commercial beekeeping businesses, and researchers. The inference models used to detect honey bees, pollen, and mites are based on the YOLOv7-tiny architecture trained with our own data. The F1-score for honey bee model recognition is 0.95 and the precision and recall value is 0.981. For our pollen and mite object detection model F1-score is 0.95 and the precision and recall value is 0.821 for pollen and 0.996 for "mite". The overall performance of our IntelliBeeHive system demonstrates its effectiveness in monitoring the honey bee's activity, achieving an accuracy of 96.28 % in tracking and our pollen model achieved a F1-score of 0.831

Parametrization of semi-dynamical quantum reflection algebra

We construct sets of structure matrices for the semi-dynamical reflection algebra, solving the Yang-Baxter type consistency equations extended by the action of an automorphism of the auxiliary space. These solutions are parametrized by dynamical conjugation matrices, Drinfel'd twist representations and quantum non-dynamical $R$-matrices. They yield factorized forms for the monodromy matrices.Comment: LaTeX, 24 pages. Misprints corrected, comments added in Conclusion on construction of Hamiltonian