Nicotinamide adenine dinucleotide treatment confers resistance to neonatal ischemia and hypoxia:effects on neurobehavioral phenotypes

Neonatal hypoxic-ischemic brain injury is the main cause of hypoxic-ischemic encephalopathy and cerebral palsy.Currently,there are few effective clinical treatments for neonatal hypoxic-ischemic brain injury.Here,we investigated the neuroprotective and molecular mechanisms of exogenous nicotinamide adenine dinucleotide,which can protect against hypoxic injury in adulthood,in a mouse model of neonatal hypoxic-ischemic brain injury.In this study,nicotinamide adenine dinucleotide(5 mg/kg)was intraperitoneally administered 30 minutes befo re surgery and every 24 hours thereafter.The results showed that nicotinamide adenine dinucleotide treatment improved body weight,brain structure,adenosine triphosphate levels,oxidative damage,neurobehavioral test outcomes,and seizure threshold in experimental mice.Tandem mass tag proteomics revealed that numerous proteins were altered after nicotinamide adenine dinucleotide treatment in hypoxic-ischemic brain injury mice.Parallel reaction monitoring and western blotting confirmed changes in the expression levels of proteins including serine(or cysteine)peptidase inhibitor,clade A,member 3N,fibronectin 1,5'-nucleotidase,cytosolic IA,microtubule associated protein 2,and complexin 2.Proteomics analyses showed that nicotinamide adenine dinucleotide ameliorated hypoxic-ischemic injury through inflammation-related signaling pathways(e.g.,nuclear factor-kappa B,mitogen-activated protein kinase,and phosphatidylinositol 3 kinase/protein kinase B).These findings suggest that nicotinamide adenine dinucleotide treatment can improve neurobehavioral phenotypes in hypoxic-ischemic brain injury mice through inflammation-related pathways.

Predict the evolution of mechanical property of Al-Li alloys in a marine environment

The ocean is one of the essential fields of national defense in the future,and more and more attention is paid to the lightweight research of Marine equipment and materials.This study it is to develop a Machine learning(ML)-based prediction method to study the evolution of the mechanical properties of Al-Li alloys in the marine environment.We obtained the mechanical properties of Al-Li alloy samples under uniaxial tensile deformation at different exposure times through Marine exposure experiments.We obtained the strain evolution by digital image correlation(DIC).The strain field images are voxelized using 2D-Convolutional Neural Networks(CNN)autoencoders as input data for Long Short-Term Memory(LSTM)neural networks.Then,the output data of LSTM neural networks combined with corrosion features were input into the Back Propagation(BP)neural network to predict the mechanical properties of Al-Li alloys.The main conclusions are as follows:1.The variation law of mechanical properties of2297-T8 in the Marine atmosphere is revealed.With the increase in outdoor exposure test time,the tensile elastic model of 2297-T8 changes slowly,within 10%,and the tensile yield stress changes significantly,with a maximum attenuation of 23.6%.2.The prediction model can predict the strain evolution and mechanical response simultaneously with an error of less than 5%.3.This study shows that a CNN/LSTM system based on machine learning can be built to capture the corrosion characteristics of Marine exposure experiments.The results show that the relationship between corrosion characteristics and mechanical response can be predicted without considering the microstructure evolution of metal materials.

Microstructures and mechanical properties of titanium-reinforced magnesium matrix composites: Review and perspective

Currently, many gratifying signs of progress have been made in magnesium(Mg) matrix composites(MMCs) by virtue of their high mechanical properties both at room and elevated temperatures. Although the commonly used reinforcements in MMCs are ceramic particles,they often provide improved yield and ultimate stresses by a significant loss in ductility. Therefore, hard metallic phases were introduced as alternative candidates for the manufacturing of MMCs, especially titanium(Ti). It has a high melting point, high Young’s modulus, high plasticity, low level of mutual solubility with Mg matrix, and closer thermal expansion coefficient to that of Mg metal than that of ceramic particles. It is highly preferable to provide both high ultimate stress and ductility in Mg matrix. However, many critical challenges for the fabrication of Ti-reinforced MMCs remain, such as Ti’s homogeneity, low recovery rate, and the optimization of interfacial bonding strength between Mg and Ti, etc. Meanwhile, different fabrication methods have various effects on the microstructures, mechanical properties, and the interfacial strength of Ti-reinforced MMCs. Hence, this review placed emphasis on the microstructural characteristics and mechanical properties of Ti-reinforced MMCs fabricated by different techniques. The influencing factors that govern the strengthening mechanisms were systematically compared and discussed. Future research trends, key issues, and prospects were also proposed to develop Ti-reinforced MMCs.

Recent advances in alkaline hydrogen oxidation reaction

The development of highly efficient electrocatalysts toward hydrogen oxidation reaction(HOR)under alkaline media is essential for the commercialization of alkaline exchange membrane fuel cells(AEMFCs).However,the HOR kinetics in alkaline is two to three orders of magnitude slower than that in acid.More critically,fundamental understanding of the sluggish kinetics derived from the p H effect is still debatable.In this review,the recent development of understanding HOR mechanism and rational design of advanced HOR electrocatalysts are summarized.First,recent advances in the theories focusing on fundamental understandings of HOR under alkaline electrolyte are comprehensively discussed.Then,from the aspect of intermediates binding energy,optimizing hydrogen binding energy(HBE)and increasing hydroxyl binding energy(OHBE),the strategies for designing efficient alkaline HOR catalysts are summarized.At last,perspectives for the future research on alkaline HOR are pointed out.

A self-centering and stiffness-controlled MEMS accelerometer

This paper presents a high-performance MEMS accelerometer with a DC/AC electrostatic stiffness tuning capability based on double-sided parallel plates(DSPPs).DC and AC electrostatic tuning enable the adjustment of the effective stiffness and the calibration of the geometric offset of the proof mass,respectively.A dynamical model of the proposed accelerometer was developed considering both DC/AC electrostatic tuning and the temperature effect.Based on the dynamical model,a self-centering closed loop is proposed for pulling the reference position of the forceto-rebalance(FTR)to the geometric center of DSPP.The self-centering accelerometer operates at the optimal reference position by eliminating the temperature drift of the readout circuit and nulling the net electrostatic tuning forces.The stiffness closed-loop is also incorporated to prevent the pull-in instability of the tuned low-stiffness accelerometer under a dramatic temperature variation.Real-time adjustments of the reference position and the DC tuning voltage are utilized to compensate for the residue temperature drift of the proposed accelerometer.As a result,a novel controlling approach composed of a self-centering closed loop,stiffness-closed loop,and temperature drift compensation is achieved for the accelerometer,realizing a temperature drift coefficient(TDC)of approximately 7μg/℃ and an Allan bias instability of less than 1μg.

Deteriorated corrosion performance of micro-alloyed Mg-Zn alloy after heat treatment and mechanical processing

The corrosion performances of the as-cast and solution-treated Mg-0.5Zn samples were investigated in 0.9%Na Cl solution and compared.From the electrochemical measurement results and corrosion morphology observations,it is found that the corrosion resistance of Mg-0.5Zn deteriorated with the extension of solution treatment duration.The main reason was the formation of Fe-Si precipitates with higher Fe concentrations during heat treatment.The Fe-Si precipitates,especially the ones with high Fe contents influenced the corrosion initiation and propagation significantly.In regard of corrosion performance,the solution-treated and then extruded sample was also performing not as good as the cast and then directly extruded sample.

pH-Dependent binding energy-induced inflection-point behaviors for pH-universal hydrogen oxidation reaction

The kinetics of hydrogen oxidation reaction(HOR)declines with orders of magnitude when the electrolyte varies from acid to base.Therefore,unveiling the mechanism of pH-dependent HOR and narrowing the acid-base kinetic gap are indispensable and challenging.Here,the HOR behaviors of palladium phosphides and their counterpart(PdP_2/C,Pd_5P_2/C,Pd_3P/C,and Pd/C)in the whole pH region(from pH 1 to 13)are explored.Unexpectedly,there are non-monotonous relationships between their HOR kinetics and varied pHs,showing distinct inflection-point behaviors(inflection points and acid-base kinetic gaps).We find the inflection-point behaviors can be explained by the discrepant role of pH-dependent hydroxyl binding energy(OHBE)and hydrogen binding energy(HBE)induced HOR kinetics under the entire pH range.We further reveal that the strengthened OHBE is responsible for the earlier appearance of the inflection point and much narrower acid-base kinetic gap.These findings are conducive to understanding the mechanism of the pH-targeted HOR process,and provide a new strategy for rational designing advanced HOR electrocatalysts under alkaline electrolyte.

Temperature Bias Drift Phase-Based Compensation for a MEMS Accelerometer with Stiffness-Tuning Double-Sided Parallel Plate Capacitors

This paper reports an approach of in-operation temperature bias drift compensation based on phase-based calibration for a stiffness-tunable MEMS accelerometer with double-sided parallel plate(DSPP)capacitors.The temperature drifts of the components of the accelerometer are characterized,and analytical models are built on the basis of the measured drift results.Results reveal that the temperature drift of the acceleration output bias is dominated by the sensitive mechanical stiffness.An out-of-bandwidth AC stimulus signal is introduced to excite the accelerometer,and the interference with the acceleration measurement is minimized.The demodulated phase of the excited response exhibits a monotonic relationship with the effective stiffness of the accelerometer.Through the proposed online compensation approach,the temperature drift of the effective stiffness can be detected by the demodulated phase and compensated in real time by adjusting the stiffness-tuning voltage of DSPP capacitors.The temperature drift coefficient(TDC)of the accelerometer is reduced from 0.54 to 0.29 mg/℃,and the Allan variance bias instability of about 2.8μg is not adversely affected.Meanwhile,the pull-in resulting from the temperature drift of the effective stiffness can be prevented.TDC can be further reduced to 0.04 mg/℃through an additional offline calibration based on the demodulated carrier phase representing the temperature drift of the readout circuit.