Complete Deconstruction of SF6 by an Aluminium(I) Compound

<b>The room-temperature activation of SF₆, a potent greenhouse gas, is reported using a monovalent aluminium(I) reagent to form well-defined aluminium(III) fluoride and aluminium(III) sulfide products. New reactions have been developed to utilise the aluminium(III) fluoride and aluminium(III) sulfide as a nucleophilic source of F^– and S^2–for a range of electrophiles. The overall reaction sequence results in the net transfer of fluorine or sulfur atoms from an environmentally detrimental gas to useful organic products.</b>

Complete Deconstruction of SF6 by an Aluminium(I) Compound

<b>The room-temperature activation of SF₆, a potent greenhouse gas, is reported using a monovalent aluminium(I) reagent to form well-defined aluminium(III) fluoride and aluminium(III) sulfide products. New reactions have been developed to utilise the aluminium(III) fluoride and aluminium(III) sulfide as a nucleophilic source of F^– and S^2–for a range of electrophiles. The overall reaction sequence results in the net transfer of fluorine or sulfur atoms from an environmentally detrimental gas to useful organic products.</b>

A new bearing fault diagnosis method using elastic net transfer learning and LSTM

Although the existing transfer learning method based on deep learning can realize bearing fault diagnosis under variable load working conditions, it is difficult to obtain bearing fault data and the training data of fault diagnosis model is insufficient£¬which leads to the low accuracy and generalization ability of fault diagnosis model, A fault diagnosis method based on improved elastic net transfer learning under variable load working conditions is proposed. The improved elastic net transfer learning is used to suppress the over fitting and improve the training efficiency of the model, and the long short-term memory network is introduced to train the fault diagnosis model, then a small amount of target domain data is used to fine tune the model parameters. Finally, the fault diagnosis model under variable load working conditions based on improved elastic net transfer learning is constructed. Finally, through model experiments and comparison with conventional deep learning fault diagnosis models such as long short-term memory network (LSTM), gated recurrent unit (GRU) and Bi-LSTM, it shows that the proposed method has higher accuracy and better generalization ability, which verifies the effectiveness of the method.

E-Money

The definition of electronic money (also called electronic cash or digital cash) is a term that is still evolving. It includes transactions carried out electronically with a net transfer of funds from one party to another, which may be either debit or credit and can be either anonymous or identified.

Iron absorption during pregnancy is underestimated when iron utilization by the placenta and fetus is ignored

ABSTRACT Background Maternal iron absorption during pregnancy can be evaluated using RBC incorporation of orally administered stable iron isotope. This approach underestimates true maternal absorption of iron as it does not account for absorbed iron that is transferred to the fetus or retained within the placenta. Objective Our objective was to re-evaluate maternal iron absorption after factoring in these losses and identify factors associated with iron partitioning between the maternal, neonatal, and placental compartments. Methods This study utilized data from stable iron isotope studies carried out in 68 women during the third trimester of pregnancy. Iron status indicators and stable iron isotopic enrichment were measured in maternal blood, umbilical cord blood, and placental tissue when available. Factors associated with iron isotope partitioning between the maternal, neonatal, and placental compartments were identified. Results On average, true maternal absorption of iron increased by 10% (from 19% to 21%) after accounting for absorbed iron present in the newborn (P &lt; 0.001), and further increased by 7%, (from 39% to 42%, P &lt; 0.001) after accounting for iron retained within the placenta. On average, 2% of recovered tracer was present in the placenta and 6% was found in the newborn. Net transfer of iron to the neonate was higher in women with lower total body iron (standardized β = −0.48, P &lt; 0.01) and lower maternal hepcidin (standardized β = −0.66, P &lt; 0.01). In women carrying multiple fetuses, neonatal hepcidin explained a significant amount of observed variance in net placental transfer of absorbed iron (R = 0.95, P = 0.03). Conclusions Maternal RBC iron incorporation of an orally ingested tracer underestimated true maternal iron absorption. The degree of underestimation was greatest in women with low body iron. Maternal hepcidin was inversely associated with maternal RBC iron utilization, whereas neonatal hepcidin explained variance in net transfer of iron to the neonatal compartment. These trials were registered at clinicaltrials.gov as NCT01019096 and NCT01582802.