REAL-TIME SIGNAL PROCESSING FOR FLYING HEIGHT MEASUREMENT AND CONTROL IN HARD DRIVES SUBJECT TO SHOCK AND VIBRATION

Merged with duplicate record 10026.1/829 on 10.04.2017 by CS (TIS)Three readback signal detection methods are investigated for real-time flying height or head disk spacing variation measurement under vibration conditions. This is carried out by theoretical analysis, numerical simulation, and experimental study. The first method (amplitude detection) provides a simple way to study the head disk spacing change. The second method ( PW50 parameter estimation) can be used effectively for real-time spacing variation measurement in normally operated hard disk drives, primarily in low frequency spacing variation conditions. The third method (thermal signal detection), on the other hand, is more effective and suitable for high frequency spacing variation measurement. By combining the PW50 estimation and thermal signal detection methods, a noval spacing variation detection method for the whole frequency range is constructed. This combined signal detection method not only has been used to study the head disk spacing variation itself, but also has the potential of being used for real time flying height control. Analytical models are developed for head disk assembly and head position servo control mechanisms to analyse the operation failure of hard disk drives under vibration conditions. Theoretical analysis and numerical simulation show their good agreement with experimental results. A novel active flying height control method is proposed to suppress the flying height or head-disk spacing variation in hard disk drives under vibration conditions. Simulation results show that this active flying height control can effectively suppress the head-disk spacing variation, therefore the performance and reliability of HDDs can be well improved when working in vibration conditions: The method has a good potential to be applied to future ruggedized hard disk drives

Interplay of tRNA-Derived Fragments and T Cell Activation in Breast Cancer Patient Survival

Effector CD8+ T cell activation and its cytotoxic function are positively correlated with improved survival in breast cancer. tRNA-derived fragments (tRFs) have recently been found to be involved in gene regulation in cancer progression. However, it is unclear how interactions between expression of tRFs and T cell activation affect breast cancer patient survival. We used Kaplan–Meier survival and multivariate Cox regression models to evaluate the effect of interactions between expression of tRFs and T cell activation on survival in 1081 breast cancer patients. Spearman correlation analysis and weighted gene co-expression network analysis were conducted to identify genes and pathways that were associated with tRFs. tRFdb-5024a, 5P_tRNA-Leu-CAA-4-1, and ts-49 were positively associated with overall survival, while ts-34 and ts-58 were negatively associated with overall survival. Significant interactions were detected between T cell activation and ts-34 and ts-49. In the T cell exhaustion group, patients with a low level of ts-34 or a high level of ts-49 showed improved survival. In contrast, there was no significant difference in the activation group. Breast cancer related pathways were identified for the five tRFs. In conclusion, the identified five tRFs associated with overall survival may serve as therapeutic targets and improve immunotherapy in breast cancer

Disrupted Brain Structural Network Connection in de novo Parkinson's Disease With Rapid Eye Movement Sleep Behavior Disorder

ObjectiveTo explore alterations in white matter network topology in de novo Parkinson's disease (PD) patients with rapid eye movement sleep behavior disorder (RBD).Materials and MethodsThis study included 171 de novo PD patients and 73 healthy controls (HC) recruited from the Parkinson's Progression Markers Initiative (PPMI) database. The patients were divided into two groups, PD with probable RBD (PD-pRBD, n = 74) and PD without probable RBD (PD-npRBD, N = 97), according to the RBD screening questionnaire (RBDSQ). Individual structural network of brain was constructed based on deterministic fiber tracking and analyses were performed using graph theory. Differences in global and nodal topological properties were analyzed among the three groups. After that, post hoc analyses were performed to explore further differences. Finally, correlations between significant different properties and RBDSQ scores were analyzed in PD-pRBD group.ResultsAll three groups presented small-world organization. PD-pRBD patients exhibited diminished global efficiency and increased shortest path length compared with PD-npRBD patients and HCs. In nodal property analyses, compared with HCs, the brain regions of the PD-pRBD group with changed nodal efficiency (Ne) were widely distributed mainly in neocortical and paralimbic regions. While compared with PD-npRBD group, only increased Ne in right insula, left middle frontal gyrus, and decreased Ne in left temporal pole were discovered. In addition, significant correlations between Ne in related brain regions and RDBSQ scores were detected in PD-pRBD patients.ConclusionsPD-pRBD patients showed disrupted topological organization of white matter in the whole brain. The altered Ne of right insula, left temporal pole and left middle frontal gyrus may play a key role in the pathogenesis of PD-RBD

Soil aggregate-associated heavy metals subjected to different types of land use in subtropical China

Heavy metal distribution in soils is strongly influenced by soil aggregate size. In this study, we collected surface soil samples from farmlands (FL), woodlands (WL), and bare lands (BL). Air-dried soils were sieved into four size fractions (>3, 1-3, 0.25-1, and 0.25 mm) was significantly higher than that of microaggregates (3 mm) showed an order of FL > ML > BL, while the proportion of microaggregates (<0.25 mm) showed an order of FL < ML < BL. The soil Cd and Pb levels in woodlands were significantly higher than those in farmlands and bare lands. In addition, the concentrations of soil Cu and Zn were elevated in farmlands compared to woodlands and bare lands. For the aggregate-associated heavy metal, contents of most metal elements (except As) in soil aggregates slightly decreased with increasing size class in farmlands. Heavy metals were generally depleted in the larger aggregates but enriched in the smaller aggregates. Interestingly, soil organic matter content was positively related to soil Cd, Cr, Ni, and Pb concentrations, but negatively correlated with soil Cu and As levels. The findings suggest that land use changes can affect the concentrations of soil aggregate-associated heavy metals, and these effects vary among different metals. (C) 2018 The Authors. Published by Elsevier B.V

Prevalence of Work-Related Musculoskeletal Disorders in the Nurses Working in Hospitals of Xinjiang Uygur Autonomous Region

Objective. To investigate the status of work-related musculoskeletal disorders (WMSDs) in nurses working in the hospitals in Xinjiang Uygur Autonomous Region. Methods. The prevalence of WMSDs since working and in the previous 12 months was evaluated using self-administrated modified musculoskeletal questionnaire based on North European questionnaire. In this cross-sectional study, 6674 nurses involved in the nursing profession were selected from 16 hospitals using the stratified cluster sampling method. Results. The most commonly affected regions by WMSDs were lower back, neck, shoulder, and back, with an annual prevalence of 62.71%, 59.77%, 49.66%, and 39.50%, respectively. Statistical differences were noticed in the annual prevalence of WMSDs in those with different ages (P40 hrs per week; poor health status; and feeling of fatigue. Rest time of >10 min and no history of WMSDs were the protective factors of WMSDs. Conclusions. Shift and working/rest duration was closely related to WMSDs

Synthesis, crystal structure, and characterization of Na2SrV4O12: A low‐firing dielectric vanadate

In this work, cyclotetravanadate Na2SrV4O12 was synthesized at a relatively low sintering temperature of ∼ 500 ° C using a solid-state reaction method. X-ray diffraction and transmission electron microscope characterization featured a tetragonal structure that was built by a 3D frame of isolated tetracyclic (V4O12)4−. Dielectric measurements demonstrated strong dependence on frequency and temperature. A low relative permittivity of εr ∼ 8 ± 0.2 and a dielectric (loss tanδ) ∼ 0.4 ± 0.01 was achieved at a frequency of 10 kHz and room temperature. ac impedance and conductivity analysis revealed a thermally activated migration behavior of charge carriers with a short-range hopping feature. XPS analysis validated the existence of oxygen vacancy and reduction in vanadium (from V5+ to V4+), which gave rise to charged lattice defects. The migration or hopping of such charged defects was responsible for the observed electrical behaviors. Owing to the simple composition, inexpensive raw materials, and low density (2.99 g/cm3) make Na2SrV4O12 ceramic a potential candidate for lightweight devices and in photocatalytic degradation and all-solid-state ion batteries

Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson’s disease

Background: Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease. Objectives: To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning methods. Methods: We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net-based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naïve Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model performance. Results: A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62–0.68; ACC range: 0.63–0.77; SEN range: 0.45–0.66; SPE range: 0.64–0.84). Models trained with structural connectivity (AUC range, 0.81–0.84; ACC range, 0.75–0.86; SEN range, 0.77–0.91; SPE range, 0.71–0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81–0.85; ACC range, 0.74–0.85; SEN range, 0.79–0.91; SPE range, 0.70–0.89). Conclusions: Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients