LERMS: A Low-Latency and Reliable Downlink Packet-Level Encoding Transmission Method in Untrusted 5GA Edge Network.

The increasing demand for end-to-end low-latency and high-reliability transmissions between edge computing nodes and user elements in 5G Advance edge networks has brought new challenges to the transmission of data. In response, this paper proposes LERMS, a packet-level encoding transmission scheme designed for untrusted 5GA edge networks that may encounter malicious transmission situations such as data tampering, discarding, and eavesdropping. LERMS achieves resiliency against such attacks by using 5GA Protocol data unit (PDU) coded Concurrent Multipath Transfer (CMT) based on Lagrangian interpolation and Raptor's two-layer coding, which provides redundancy to eliminate the impact of an attacker's malicious behavior. To mitigate the increased queuing delay resulting from encoding in data blocks, LERMS is queue-aware with variable block length. Its strategy is modeled as a Markov chain and optimized using a matrix method. Numerical results demonstrate that LERMS achieves the optimal trade-off between delay and reliability while providing resiliency against untrusted edge networks.

Research on the community electric carbon emission prediction considering the dynamic emission coefficient of power system.

Based on the counted power system emission factors of North China Power Grid, a community carbon emissions sample database is constructed. The support vector regression (SVR) model is trained to forecast the power carbon emissions, which is optimized by genetic algorithm (GA). A community carbon emission warning system is designed according the results. The dynamic emission coefficient curve of the power system is obtained by fitting the annual carbon emission coefficients. The time series SVR carbon emission prediction model is constructed, while the GA is improved to optimize its parameters. Taking Beijing Caochang Community as an example, a carbon emission sample database is generated based on the electricity consumption and emission coefficient curve to train and test the SVR model. The results show that the GA-SVR model fits well with the training set and the testing set, and the prediction accuracy of the testing set reaches 86%. In view of the training model in this paper, the carbon emission trend of community electricity consumption in the next month is predicted. The carbon emission warning system of the community is designed, and the specific strategy of community carbon emission reduction is proposed.

Specific breast cancer prognosis-subtype distinctions based on DNA methylation patterns.

Tumour heterogeneity is an obstacle to effective breast cancer diagnosis and therapy. DNA methylation is an important regulator of gene expression, thus characterizing tumour heterogeneity by epigenetic features can be clinically informative. In this study, we explored specific prognosis-subtypes based on DNA methylation status using 669 breast cancers from the TCGA database. Nine subgroups were distinguished by consensus clustering using 3869 CpGs that significantly influenced survival. The specific DNA methylation patterns were reflected by different races, ages, tumour stages, receptor status, histological types, metastasis status and prognosis. Compared with the PAM50 subtypes, which use gene expression clustering, DNA methylation subtypes were more elaborate and classified the Basal-like subtype into two different prognosis-subgroups. Additionally, 1252 CpGs (corresponding to 888 genes) were identified as specific hyper/hypomethylation sites for each specific subgroup. Finally, a prognosis model based on Bayesian network classification was constructed and used to classify the test set into DNA methylation subgroups, which corresponded to the classification results of the train set. These specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes.

Fabrication of Sustained-release CA-PU Coaxial Electrospun Fiber Membranes for Plant Grafting Application.

Plant grafting is a well-known activity in orchards, greenhouses and vineyards gardens. However, low survival rate still limits the promotion of grafting and breeding of improved varieties. We report on polymeric fibers, obtained through coaxial electrospun, as carriers for the sustained release of drugs to heal wounds in plants. The CA-PU co-electrospun fibers show a rather uniform diameter, a smooth and hydrophilic surface. As long as 10days of sustained drugs release meets with the physiological requirement of plant grafting. The callus toxicity test shows that the CA-PU fibers are not toxic for plant cells. We show that loading the core of CA-PU fibers with 6-Benzylaminopurine (6-BA), a first-generation synthetic cytokinin that elicits plant growth and development, results in fibers that can efficiently promote the healing of plant wounds, thereby significantly improving the grafting survival rate.

Tetra-aqua-bis-(6-chloro-pyridine-3-carboxyl-ato-κO)nickel(II) tetra-hydrate.

In the title compound, [Ni(C(6)H(3)ClNO(2))(2)(H(2)O)(4)]·4H(2)O, the Ni(II) ion is located on an inversion centre and is octa-hedrally coordinated by four O atoms from four water mol-ecules in the equatorial plane and two O atoms of two 6-chloro-3-carboxyl-ate ligands in axial positions. There are also four lattice water molecules present. The organic ligands are bound to the Ni(II) ion in a monodentate manner through a carboxyl-ate O atom. There is one strong intra-molecular O-H⋯O hydrogen bond and six inter-molecular O-H⋯O and O-H⋯N hydrogen-bonding inter-actions in the packing, resulting in a complex three-dimensional network structure.

catena-Poly[[[diaqua-copper(II)]-µ-quinoline-2,3-dicarboxyl-ato-κ(3)N,O(2):O(3)] monohydrate].

In the title compound, {[Cu(C(11)H(5)NO(4))(H(2)O)(2)]·H(2)O}(n), the Cu(II) ion is five-coordinated by two O atoms and one N atom of two symmetry-related quinoline-2,3-dicarboxyl-ate ligands, and two water mol-ecules. The water mol-ecules occupy basal and apical positions of the square-pyramidal coordination polyhedron. Each quinoline-2,3-dicarboxyl-ate dianion bridges two adjacent Cu(II) ions, forming a polymeric chain along [010]. The chains are further connected via O-H⋯O hydrogen-bonding inter-actions and quinoline ring π-π inter-actions [centroid-centroid distance = 3.725 (4) Å], generating a three-dimensional structure. Lattice water mol-ecules participate in the crystal structure via O-H⋯O hydrogen bonds.