Currently, the rotational speed of spindle motors in HDDs (Hard-Disk Drives) are increasing to improve high data throughput and decrease rotational latency for ultra-high data transfer rates. However, the disk platters are excited to vibrate at their natural frequencies due to higher air-flow excitation as well as eccentricities and imbalances in the disk-spindle assembly. These factors contribute directly to TMR (Track Mis-Registration) which limits achievable high recording density essential for future mobile HDDs. In this paper, the natural mode shapes of an annular disk mounted on a spindle motor used in current HDDs are characterized using FEM (Finite Element Methods) analysis and verified with SLDV (Scanning Laser Doppler Vibrometer) measurements. The identified vibration frequencies and amplitudes of the disk ODS (Operating Deflection Shapes) at corresponding disk mode shapes are modelled as repeatable disturbance components for servo compensation in HDDs. Our experimental results show that the SLDV measurements are accurate in capturing static disk mode shapes without the need for intricate air-flow aero-elastic models, and the proposed disk ODS vibration model correlates well with experimental measurements from a LDV. 相似文献
A two-oscillator transducer incorporating a laser-illuminated Fabry-Perot cavity with a finesse of 77,500 and a power dissipation of 1.2 μW was tested at room temperature. The energy of the last resonator with a mass of 1.25 g was measured to be k(B)T within 8%, and no back action from the sensor could be detected. The lowest value of the noise measured away from resonance was 1.0 × 10(-15)m/√Hz, and the electronic noise was 3.2 × 10(-17) m/√Hz. That transducer is designed for a 2400-kg gravitational wave antenna operating at cryogenic temperatures. At 4.2 K and for mechanical quality factors of 3 × 10(6), the measured thermal and electronic noise levels would translate into a sensitivity in h equal to 7.0 × 10 (-19) and 1.5 × 10(-19), respectively. 相似文献
The accumulation of reactive oxygen species (ROS) and minimal osteogenic raw material in the osteoporotic bone microenvironment greatly inhibits the activity of osteoblasts. Herein, it is originally proposed to construct a biomatrix multifaceted bone microenvironment amendment -Mineralized zippered G4-Hemin DNAzyme hydrogel (MDH)-to improve osteoporotic osteogenic capacity and promote high-quality bone defect repair. The programmed design of the rolling circle amplified DNA hydrogel synthesis system allows the introduction of massive amounts of zippered G4-Hemin DNAzyme in MDH. The zippered G4-Hemin DNAzyme highly mimics the tight catalytic configuration of horseradish peroxidase and exerts excellent enzyme-like activity with considerable ROS molecule scavenging ability. In addition, the DNA amplification by-product pyrophosphate is ingeniously employed as a sufficient phosphorus source, thus constituting an autonomous mineralization system for waste reuse through the introduction of pyrophosphate hydrolase and calcium ions, which deposits in MDH as an osteogenic raw material and addresses the challenge of DNA hydrogel bio-application stability. The remarkable in vitro and in vivo outcomes demonstrate that MDH can effectively improve the oxidative stress status of osteoblasts, restore the balance of mitochondrial membrane potential, and reduce apoptosis, ultimately demonstrating superior osteogenic capacity. 相似文献
The traditional emotion–cause extraction task needs to give the exact emotion annotation contained in the document before extracting the cause. Different from this, the emotion–cause pair extraction (ECPE) task, which aims to extract emotion–cause pairs with causal relationships directly from the document, is a task proposed in the natural language processing field recently. At present, the task of ECPE is divided into two steps: emotion annotations and cause clause extraction, emotion–cause clause pair combining and filtering. In this article, we optimize these two steps. On the one hand, in the first step of ECPE, a mutual assistance single-task model proposed by us is used to replace the original multi-task model. On the other hand, the position information of the clause is added as an additional feature in the second step of ECPE. Furthermore, based on different levels of semantic features, we design three filtering models and explore their performance on ECPE tasks. The experimental results on the benchmark corpus show that our approach can make the ECPE task achieve better performance. Compared with the referenced method, F1-score is increased by 5.3%. Moreover, these optimization strategies improve the subtasks contained in ECPE to varying degrees.