Total Pairwise Quantum Correlation and Entanglement in a Mixed-Three-Spin Ising-XY Model with Added Dzyaloshinskii-Moriya Interaction under Decoherence

We investigate the behavior of geometric global quantum discord （GGQD） and concurrence （C） between half- spins of a mixed-three-spin （1/2, 1, 1/2） system with the Ising-XY model for which spins （1, 1/2） have the Ising interaction and half-spins （1/2, 1/2） have both XY and the Dzyaloshinskii Moriya interactions together, under the decoherence action. A single-ion anisotropy property with coefficient ζ is assumed for the spin-integer. This system which includes an analytical Hamiltonian is considered at the front of an external homogeneous magnetic field B in thermal equilibrium. Finally, we compare GGQD and C and express some interesting phase flip reactions of the total quantum correlation and pairwise entanglement between spins （1/2, 1/2）. Generally, we conclude that the concurrence and GGQD have different behaviors under the phase flip channel.

Correlations in Werner States

Werner states are paradigmatic examples of quantum states and play an innovative role in quantum information theory. In investigating the correlating capability of Werner states, we find the curious phenomenon that quantum correlations, as quantified by the entanglement of formation, may exceed the total correlations, as measured by the quantum mutual information. Consequently, though the entanglement of formation is so widely used in quantifying entanglement, it cannot be interpreted as a consistent measure of quantum correlations per se if we accept the folklore that total correlations are measured （or rather upper bounded） by the quantum mutual information.

Variability in total antioxidant capacity, antioxidant leaf pigments and foliage yield of vegetable amaranth

Twenty vegetable amaranth genotypes were evaluated for total antioxidant capacity, antioxidant leaf pigments, vitamins, and selection of suitable genotypes for extraction of juice in a randomized complete block design（RCBD） with three replications. Vegetable amaranth was rich in chlorophyll, β-cyanins, β-xanthins, betalains, carotene, ascorbic acid and total antioxidant. The genotypes VA14, VA16, VA18, VA15, and VA20 could be selected as amaranth vegtable varieties with high yields and abundance antioxidant leaf pigments and vitamins to produce juice. The genotypes VA13 and VA19 had above-average foliage yield and high antioxidant profiles while the genotypes VA2, VA3, VA9, VA11, VA12, and VA17 had a high antioxidant profiles and below-average foliage yield. These genotypes could be used as a donor parent for integration of potential high antioxidant profiles genes into other genotypes. The correlation study revealed a strong positive association among all the antioxidant leaf pigments, total antioxidant capacity and foliage yield. Selection based on total antioxidant capacity, antioxidant leaf pigments could economically viable to improve the yield potential of vegetable amaranth genotypes. Total carotene and ascorbic acid exhibited insignificant genotypic correlation with all the traits except total antioxidant capacity. This indicates that selection for antioxidant vitamins might be possible without compromising yield loss.

Exploring Chemovar-Specific Cannabis Extracts Quantification and Evaluation of Cytotoxic Compounds for Targeting Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) represents one of the most aggressive and metastatic brain tumors, with a dismal success rate of less than three percent after five years, particularly in tumors with active immune checkpoints. This necessitates the development of targeted endogenous agents for precise GBM treatment. Previous experiments utilizing Chemovar Specific Cannabis Extractions (CSCEs), fractionated with polar solvents and quantified using Liquid and Gas Column Chromatography combined with Mass Spectrometry (LC/GCMS), have shown reduced viability and motility in human GBM cell lines. However, the complexity of the botanical substance has hindered the personalization of standard cannabis medicines for GBM due to unknown synergistic effects of multiple compounds. To address this limitation, our study focuses on exposing AM251 cells to chemovar fractions extracted using a non-polar solvent, thereby isolating a broader spectrum of constituents. By employing LC/GCMS in conjunction with Nuclear Magnetic Resonance (NMR), we have identified and quantified nine* compounds present in the non-polar CSCE that exhibit significant efficacy (0.1 μM) in inducing cytotoxicity* in GBM tumor cells. Conversely, the polar fraction in our experiment did not demonstrate efficacy against UM251 cells. The quantification of individual compounds within a cannabis extraction that selectively induces cell death in brain tumors holds promise for guiding future research and facilitating the development of a standardized CSCE for GBM therapy.

Extracting invariable fault features of rotating machines with multi-ICA networks

This paper proposes novel multi-layer neural networks based on Independent Component Analysis for feature extraction of fault modes. By the use of ICA, invariable features embedded in multi-channel vibration measurements under different operating conditions (rotating speed and/or load) can be captured together.Thus, stable MLP classifiers insensitive to the variation of operation conditions are constructed. The successful results achieved by selected experiments indicate great potential of ICA in health condition monitoring of rotating machines.