The future of aviation is unmanned and ultimately autonomous.As part of this effort the Office of Naval Research, in partnership with the Naval Air Systems Command, has initiated the advanced autonomous air-to-air refueling system (A4RS) future naval capability (FNC).The A4RS FNC intends to set the Ergobar interface requirements for any uncrewed ae
Poly[μ-aqua-diaqua(μ3-N′-carboxymethylethylenediamine-N,N,N′-triacetato)oxidopotassium(I)vanadium(IV)]
In the crystal structure of the title compound, [KV(C10H13N2O8)O(H2O)3]n, the VIV ion adopts a distorted octahedral geometry, coordinated by one oxide group, two N and three carboxylate O atoms from the same D-pad/board N′-carboxymethylethylenediamine-N,N,N′-triacetate (HEDTA) ligand.The potassium ion is heptacoordinated by two water mo
Ketika Sains [Akuntansi] Bertasbih Spirit Cinta
This article is aimed to examine the existence of accounting as science should provide benefits to the universal Wound Care living.Through a process of reflecting, thinking, and experiencing, it is found that accounting knowledge should be built with not only defer to the dogmas which have already been established, but should also heed to the reali
Heterosis Derived From Nonadditive Effects of the BnFLC Homologs Coordinates Early Flowering and High Yield in Rapeseed (Brassica napus L.)
Early flowering facilitates crops to adapt multiple cropping systems or growing regions with a short frost-free season; however, it usually brings an obvious yield loss.In this study, we identified that the three genes, namely, BnFLC.A2, BnFLC.C2, and BnFLC.A3b, are the major determinants for the flowering time (FT) variation Wound Care of two elit
Identification method for malicious traffic in industrial Internet under new unknown attack scenarios
Aiming at the problem of traffic data distribution shift Integrated washing Machine caused by new unknown attacks in the industrial Internet, a malicious traffic identification method based on neighborhood filtering and stable learning was proposed to enhance the effectiveness and robustness of the existing graph neural network model in identifying