Miracle-dz/UniFAR-FTUs huggingface dataset:
Trapped Energy Gyroscopes Using Thickness Shear Vibrations in a Partially Polarized Piezoelectric Ceramic Plate

A new type of gyroscope using energy trapping of thickness-shear vibrations excited by a parallel electric field is proposed. The vibrator of a trapped-energy gyroscope is constructed using a partially polarized piezoelectric ceramic plate and three electrodes on its surface, and the driving-detecting circuit includes the current detecting circuit. Prior to designing the trapped-energy gyroscope, a method of controlling the resonant frequency of the vibrator by means of the electrode dimensions was identified from the measured impedance characteristics. Based on this method, the trapped-energy gyroscope on a 25-mm-square and 1.5-mm-thick PZT plate is constructed. The detection sensitivity of 2.8 mV/deg/s, which is proportional to the applied angular velocity, is obtained when the driving voltage is 2 Vp-p and the gain of the detecting circuit is 72 dB. Although the edge of the vibrator is firmly attached to the base, the Qm of the resonance is over 900 because of the energy trapping effect. This trapped-energy gyroscope is useful for highly reliable applications such as a yawing sensor for the vehicle stability control systems.
Association between the Inflammatory Potential of the Diet and Biological Aging: A Cross-Sectional Analysis of 4510 Adults from the Moli-Sani Study Cohort

Chronological age (CA) may not accurately reflect the health status of an individual. Rather, biological age (BA) or hypothetical underlying “functional” age has been proposed as a relevant indicator of healthy aging. Observational studies have found that decelerated biological aging or Δage (BA-CA) is associated with a lower risk of disease and mortality. In general, CA is associated with low-grade inflammation, a condition linked to the risk of the incidence of disease and overall cause-specific mortality, and is modulated by diet. To address the hypothesis that diet-related inflammation is associated with Δage, a cross-sectional analysis of data from a sub-cohort from the Moli-sani Study (2005–2010, Italy) was performed. The inflammatory potential of the diet was measured using the Energy-adjusted Dietary Inflammatory Index (E-DIITM) and a novel literature-based dietary inflammation score (DIS). A deep neural network approach based on circulating biomarkers was used to compute BA, and the resulting Δage was fit as the dependent variable. In 4510 participants (men 52.0%), the mean of CA (SD) was 55.6 y (±11.6), BA 54.8 y (±8.6), and Δage −0.77 (±7.7). In a multivariable-adjusted analysis, an increase in E-DIITM and DIS scores led to an increase in Δage (β = 0.22; 95%CI 0.05, 0.38; β = 0.27; 95%CI 0.10, 0.44, respectively). We found interaction for DIS by sex and for E-DIITM by BMI. In conclusion, a pro-inflammatory diet is associated with accelerated biological aging, which likely leads to an increased long-term risk of inflammation-related diseases and mortality.
Everyday sexism in higher education: narratives of women in Indian academia

ABSTRACT The aim of this article is to explore the experiences of different women in higher educational institutions in India. Through this piece the authors investigate how the prevalence of sexism is affecting women in academia in general and their everyday professional negotiations in particular. Furthermore, the article reviews the position of women in higher administrative responsibilities, and academic positions and also views the mundane everyday activities vis-a-vis their experiences of sexism in different universities across India. It is argued that sexism is pervasive in academic institutions in India, but often goes unnoticed and unaddressed in spite of various mechanisms and sensitization programs adopted by the Universities to address the prevailing issues of sexism across academic spaces. Gendered experiences of women have crippling and debilitating implications for women in general and more so it affects their career prospects in universities. in the process it perpetuates patriarchal power structures and hierarchies in the workplace
Necessary and sufficient conditions for solving consensus problems of double‐integrator dynamics via sampled control

In this paper, consensus problems of double‐integrator dynamics via sampled control are investigated. The sampled control protocol is induced from continuous‐time linear consensus protocol by using periodic sampling technology and zero‐order hold circuit. With the obtained sampled control protocol, the continuous‐time multi‐agent system is equivalently transformed into a linear discrete‐time system. Necessary and sufficient conditions are given to guarantee that all the agents asymptotically travel with zero relative positions and common velocities. Furthermore, consensus problem with continuous‐time consensus protocol is re‐analyzed. A necessary and sufficient condition is also obtained which is consistent with the special case when the sampling period tends to zero. The effectiveness of these algorithms is demonstrated through simulations. Copyright © 2009 John Wiley & Sons, Ltd.
Biorealistic hand prosthesis with compliance control and noninvasive somatotopic sensory feedback

Significant advances have been made to improve control and to provide sensory functions for bionic hands. However, great challenges remain, limiting wide acceptance of bionic hands due to inadequate bidirectional neural compatibility with human users. Recent research has brought to light the necessity for matching neuromechanical behaviors between the prosthesis and the sensorimotor system of amputees. A novel approach to achieving greater neural compatibility leverages the technology of biorealistic modeling with real-time computation. These studies have demonstrated a promising outlook that this unique approach may transform the performance of hand prostheses. Simultaneously, a noninvasive technique of somatotopic sensory feedback has been developed based on evoked tactile sensation (ETS) for conveying natural, intuitive, and digit-specific tactile information to users. This paper reports the recent work on these two important aspects of sensorimotor functions in prosthetic research. A background review is presented first on the state of the art of bionic hand and the various techniques to deliver tactile sensory information to users. Progress in developing the novel biorealistic hand prosthesis and the technique of noninvasive ETS feedback is then highlighted. Finally, challenges to future development of the biorealistic hand prosthesis and implementing the ETS feedback are discussed with respect to shaping a next-generation hand prosthesis.
Single-Doppler Wind Retrieval in the Moving Frame of Reference

Abstract A single Doppler radar analysis scheme is developed, and three-dimensional wind fields am retrieved from single Doppler radar reflectivity and radial velocity fields. The retrieval is based on two assumptions: 1) the Lagrangian conservation of the radar reflectivity and 2) the steadiness of the eddy structures in the wind field. To least violate these assumptions, a moving frame of reference is found where (in the least square sense) the observations are as stationary as possible. Multiple time levels of observations are used to avoid ill-conditioned computations. The retrieval equations, that is, the conservation equation of reflectivity and the relationship between the total wind and its radial component for several time levels, form a simple linear system. This linear system is overdetermined with respect to the three unknown Cartesian components u, v, and w of the vector wind. Thus u, v, and w are solved in the least square sense. Dual Doppler radar analyses are performed to provide verificat.
Allometry of bud dynamic pattern and linkage between bud traits and ecological stoichiometry of Nitraria tangutorum under fertilizer addition

Affected by the pressure and constraints of available resources, plant growth and development, as well as plant life history strategies, usually vary with environmental conditions. Plant buds play a crucial role in the life history of woody plants. Nitraria tangutorum is a common dominant woody species in desertified areas of northern China and its growth is critical to the desert ecosystem. Revealing the allometry of N. tangutorum aboveground bud fates and the linkage between bud traits and plant nutrient contents and stoichiometric ratios can be useful in understanding plant adaptation strategy. We applied seven nitrogen and phosphorus fertilizer addition treatments to natural N. tangutorum ramets in Ulan Buh Desert in three consecutive years. We surveyed three types of aboveground buds (dormant buds, vegetative buds, and reproductive buds) in each N. tangutorum ramet, then measured the plant carbon (C), nitrogen (N), and phosphorus (P) contents and ratios during three consecutive years. We specified that reserve growth potential (RGP), vegetative growth intensity (VGI) and sexual reproduction effort (SRE) are the three indices of bud dynamic pattern. The results showed that the bud dynamic pattern of N. tangutorum ramets differed significantly among different fertilizer addition treatments and sampling years. The allometry of RGP, VGI, and SRE was obvious, showing size dependence. The allometric growth relationship fluctuated among the sampling years. The linkage between bud traits and plant stoichiometric characteristics of N. tangutorum ramets showed close correlation with plant P content, C:P and N:P ratios, no significant correlation with plant C content, N content and C:N ratio. These results contribute to an improved understanding of the adaptive strategies of woody plants growing in desert ecosystems and provide insights for adoption of effective measures to restore and conserve plant communities in arid and semi-arid regions.
DTE-RR: Dynamic Topology Evolution-Based Reliable Routing in VANET

The dynamics of Vehicular Ad-hoc Network (VANET) brings tremendous challenges to reliable routing. In the existing topology evolution schemes, the link connectivity and the interaction between links have yet to be well investigated, resulting in the inability to accurately describe the evolution of routing topology. In this letter, we propose a Dynamic Topology Evolution (DTE) based reliable routing algorithm to improve transmission reliability. The DTE model is constructed to formulate the evolution of network topology. Especially, we analyze the network topology changes from the perspective of nodes and links. Meanwhile, the Dynamic Bond Percolation (DBP) model is extended to describe link interaction. Then, the DTE model is completed by deriving the state transition matrix of the network topology based on the link change using Markov theory. Finally, the DTE-based Reliable Routing (DTE-RR) algorithm is designed to optimize routing paths. The experimental results demonstrate that DTE-RR outperforms the existing protocols regarding packet delivery ratio and end-to-end delay.
Campaign-style governance of air pollution in China? A comprehensive analysis of the central environmental protection inspection

Central environmental protection inspection (CEPI) is a major institutional innovation in China's environmental governance, but its effectiveness in improving air quality is still unclear. However, the effectiveness of CEPI is of great significance and can be regarded as an important reference for deepening the reform of environmental governance system in China. This article takes the CEPI as a quasi-natural experiment and uses the regression discontinuity design (RDD) and the difference-in-differences (DID) methods to examine the effectiveness of this policy. The study found that the first round of CEPI reduced the air pollution of cities in the inspected provinces in a short time. Moreover, this positive policy effect persisted in the aftermath of the inspection, but this long-term effect is mainly reflected in PM10 and SO2. Heterogeneity analysis showed that CEPI was only effective in reducing air pollutants of industry-oriented cities, cities in Central and Eastern China, and cities with large or small population size. The moderating effect analysis indicated that a healthy relationship (close and clean) between the local governments and businesses was conducive to reducing air pollution. The research confirmed the presence of “selective” reduction of air pollutants in the long run caused by CEPI, thereby providing new inspiration for the improvement of campaign-style environmental governance and the follow-up CEPI work.
Dynamic reactions of defects in ion-implanted 4H-SiC upon high temperature annealing

Single-photon emitters based on intrinsic defects in silicon carbide (SiC) are promising as solid-state qubits for the quantum information storage, whereas defect engineering in a controllable manner still remains challenging. Herein, the thermally-driven defect dynamic reaction in the ion implanted 4H-SiC has been exploited through the optical emission spectra of defects. For the heavy-ion (Si or Ar) implanted samples with abundant Frenkel pairs, the silicon vacancies (VSi) are energetically converted into the carbon antisite-vacancy pair (CSi-VC) upon annealing till 1300 °C for 30 min, accompanied with the gradual lattice recovery and local strain relaxation. The further temperature elevation dissociates the metastable CSi-VC into carbon antisite (CSi) and carbon vacancy (VC), as supported by the consequent quenching of the (CSi-VC)-related emission at 700 nm. Thus, the whole defect reaction is probed as the vacancy interconversion from VSi to VC with the byproduct of stacking faults. In contrast, the intermediate CSi-VC complexes are not energetically favorable during the annealing of the H-implanted sample, which results from the negligible generation of Frenkel pairs, as supported by the x-ray diffraction patterns and Raman scattering analysis. These findings provide guidance for defect engineering in SiC toward the creation of reliable single photon emitters.
The early life course-related traits with three psychiatric disorders: A two-sample Mendelian randomization study

Objectives: Several studies have indicated a potential association between early life course-related traits and neurological and psychiatric disorders in adulthood, but the causal link remains unclear. Methods: Instrumental variables (IVs) that have been shown to be strongly associated with exposure were obtained from summary data of genome-wide association studies (GWASs). Four early life course-related traits [i.e., birthweight (BW), childhood body mass index (BMI), early body size, and age at first birth (AFB)] were used as exposure IVs to estimate their causal associations with three neurological and psychiatric diseases [i.e., Alzheimer’s disease (AD), major depressive disorder (MDD), and attention-deficit hyperactivity disorder (ADHD)]. Four different statistical methods, i.e., inverse-variance weighting (IVW), MR–Egger (MRE), weighted median (WM), and weighted mode (Wm), were performed in our MR analysis. Sensitivity analysis was performed by using the leave-one-out method, and horizontal pleiotropy was assessed using the MR-PRESSO package. Results: There was evidence suggesting that BW has a causal effect on AD (ORMR-PRESSO = 1.05, p = 1.14E-03), but this association was not confirmed via multivariable Mendelian randomization (MVMR) (ORMVMR = 0.97, 95% CI 0.92–1.02, p = 3.00E-01). A strong relationship was observed between childhood BMI and ADHD among both sexes; a 1-SD increase in BMI significantly predicted a 1.46-fold increase in the OR for ADHD (p = 9.13E-06). In addition, a similar relationship was found between early life body size and ADHD (ORMR-PRESSO = 1.47, p = 9.62E-05), and this effect was mainly driven by male participants (ORMR-PRESSO = 1.50, p = 1.28E-3). Earlier AFB could significantly predict a higher risk of MDD (ORMR-PRESSO = 1.19, p = 1.96E-10) and ADHD (ORMR-PRESSO = 1.45, p = 1.47E-15). No significant causal associations were observed between the remaining exposures and outcomes. Conclusion: Our results reveal the adverse effects of childhood obesity and preterm birth on the risk of ADHD later in life. The results of MVMR also show that lower BW may have no direct relationship with AD after adjusting for BMI. Furthermore, AFB may predict a higher risk of MDD.
Symmetric Variants of Logistic Smooth Transition Autoregressive Models: Monte Carlo Evidences

The Smooth Transition Autoregressive (STAR) models are becoming popular in modeling economic and financial time series. The asymmetric type of the model is the Logistic STAR (LSTAR) model, which is limited in its applications as a result of its asymmetric property, which makes it suitable for modelling specific macroeconomic time series. This study was designed to develop the Absolute Error LSTAR (AELSTAR) and Quadratic LSTAR (QLSTAR) models for improving symmetry and performance in terms of model fitness. Modified Teräsvirta's Procedure (TP) and Escribano and Jordá's Procedure (EJP) were used to test for nonlinearity in the series. The performance of the AELSTAR and QLSTAR models showed that TP and EJP realized time series with improved symmetry as indicated by the lower relative frequencies than that realized with the existing LSTAR model. The AELSTAR model performed better than QLSTAR model at higher nonlinearity, and the selection of both models showed evidence of asymptotic property. The AELSTAR and QLSTAR models showed improved symmetry over the existing asymmetric LSTAR model.
AoI-Aware Optimization of Service Caching-Assisted Offloading and Resource Allocation in Edge Cellular Networks

The rapid development of the Internet of Things (IoT) has led to computational offloading at the edge; this is a promising paradigm for achieving intelligence everywhere. As offloading can lead to more traffic in cellular networks, cache technology is used to alleviate the channel burden. For example, a deep neural network (DNN)-based inference task requires a computation service that involves running libraries and parameters. Thus, caching the service package is necessary for repeatedly running DNN-based inference tasks. On the other hand, as the DNN parameters are usually trained in distribution, IoT devices need to fetch up-to-date parameters for inference task execution. In this work, we consider the joint optimization of computation offloading, service caching, and the AoI metric. We formulate a problem to minimize the weighted sum of the average completion delay, energy consumption, and allocated bandwidth. Then, we propose the AoI-aware service caching-assisted offloading framework (ASCO) to solve it, which consists of the method of Lagrange multipliers with the KKT condition-based offloading module (LMKO), the Lyapunov optimization-based learning and update control module (LLUC), and the Kuhn–Munkres (KM) algorithm-based channel-division fetching module (KCDF). The simulation results demonstrate that our ASCO framework achieves superior performance in regard to time overhead, energy consumption, and allocated bandwidth. It is verified that our ASCO framework not only benefits the individual task but also the global bandwidth allocation.
Part decomposition of 3d surfaces

This dissertation describes a general algorithm that automatically decomposes real-world scenes and objects into visual parts. The input to the algorithm is a 3D triangle mesh that approximates the surfaces of a scene or object. This geometric mesh completely specifies the shape of interest. The output of the algorithm is a set of boundary contours that dissect the mesh into parts where these parts agree with human perception. In this algorithm, shape alone defines the location of a boundary contour for a part. The algorithm leverages a human vision theory known as the minima rule that states that human visual perception tends to decompose shapes into parts along lines of negative curvature minima. Specifically, the minima rule governs the location of part boundaries, and as a result the algorithm is known as the Minima Rule Algorithm. Previous computer vision methods have attempted to implement this rule but have used pseudo measures of surface curvature. Thus, these prior methods are not true implementations of the rule. The Minima Rule Algorithm is a three step process that consists of curvature estimation, mesh segmentation, and quality evaluation. These steps have led to three novel algorithms known as Normal Vector Voting, Fast Marching Watersheds, and Part Saliency Metric, respectively. For each algorithm, this dissertation presents both the supporting theory and experimental results. The results demonstrate the effectiveness of the algorithm using both synthetic and real data and include comparisons with previous methods from the research literature. Finally, the dissertation concludes with a summary of the contributions to the state of the art.
Association of SARS-CoV-2 nucleocapsid viral antigen and the receptor for advanced glycation end products with development of severe disease in patients presenting to the emergency department with COVID-19

Introduction There remains a need to better identify patients at highest risk for developing severe Coronavirus Disease 2019 (COVID-19) as additional waves of the pandemic continue to impact hospital systems. We sought to characterize the association of receptor for advanced glycation end products (RAGE), SARS-CoV-2 nucleocapsid viral antigen, and a panel of thromboinflammatory biomarkers with development of severe disease in patients presenting to the emergency department with symptomatic COVID-19. Methods Blood samples were collected on arrival from 77 patients with symptomatic COVID-19, and plasma levels of thromboinflammatory biomarkers were measured. Results Differences in biomarkers between those who did and did not develop severe disease or death 7 days after presentation were analyzed. After adjustment for multiple comparisons, RAGE, SARS-CoV-2 nucleocapsid viral antigen, interleukin (IL)-6, IL-10 and tumor necrosis factor receptor (TNFR)-1 were significantly elevated in the group who developed severe disease (all p<0.05). In a multivariable regression model, RAGE and SARS-CoV-2 nucleocapsid viral antigen remained significant risk factors for development of severe disease (both p<0.05), and each had sensitivity and specificity >80% on cut-point analysis. Discussion Elevated RAGE and SARS-CoV-2 nucleocapsid viral antigen on emergency department presentation are strongly associated with development of severe disease at 7 days. These findings are of clinical relevance for patient prognostication and triage as hospital systems continue to be overwhelmed. Further studies are warranted to determine the feasibility and utility of point-of care measurements of these biomarkers in the emergency department setting to improve patient prognostication and triage.
Squeeze air bearing based on ultrasonic oscillation: Motion error compensation using amplitude modulation

This article reports an active air bearing that utilizes air films generated by ultrasonic oscillation. The films on the bearing surfaces of a horn, which is a stator, lift and restrain the rotor. Moreover, the oscillation that modulates the amplitude via the positioning signal varies the thickness of the air film. Thus, this bearing regulates the position of the rotor using a PI controller with a displacement sensor so that its runouts become zero. Furthermore, no pneumatic plant is needed in this bearing. The repetitive runouts were 0.23 μm p-p in an axial direction and 1.0 μm p-p in a radial without compensation. Nonrepetitive runouts were 0.061 μm 3σ in an axial direction and 0.065 μm 3σ in a radial without compensation. PI feedback control, in which a fiber optic displacement sensor measures the movement of a master ball mounted on the rotor, decreased repetitive axial runout from 0.232 μm p-p to 0.118 μm p-p. The settling time for 0.2 μm step positioning in an axial direction was less than 0.2 s. Th.