Miracle-dz/UniFAR-FTUs huggingface dataset:
Shape memory polymers and their composites in aerospace applications: a review

As a new class of smart materials, shape memory polymers and their composites (SMPs and SMPCs) can respond to specific external stimulus and remember the original shape. There are many types of stimulus methods to actuate the deformation of SMPs and SMPCs, of which the thermal- and electro-responsive components and structures are common. In this review, the general mechanism of SMPs and SMPCs are first introduced, the stimulus methods are then discussed to demonstrate the shape recovery effect, and finally, the applications of SMPs and SMPCs that are reinforced with fiber materials in aerospace are reviewed. SMPC hinges and booms are discussed in the part on components; the booms can be divided again into foldable SMPC truss booms, coilable SMPC truss booms and storable tubular extendible member (STEM) booms. In terms of SMPC structures, the solar array and deployable panel, reflector antenna and morphing wing are introduced in detail. Considering the factors of weight, recovery force and shock effect, SMPCs are expected to have great potential applications in aerospace.
Red, Blue, and the Flu: Media Self-Selection and Partisan Gaps in Swine Flu Vaccinations

This study assesses the relationship between political partisanship and attitudes and behavior with respect to the Swine Flu crisis of 2009 in general, and the U.S. mass vaccination program in particular. I argue that even seemingly non-partisan political issues like public health are increasingly characterized by partisan polarization in public attitudes, and that such polarization is in part attributable, at least in part, to the breakdown of the information commons that characterized the American mass media from roughly the 1950s until the early 1990s. In its place has arisen an increasingly fragmented and niche-oriented media marketplace in which individuals are better able to limit their information exposure to attitudes and opinions that reinforce, rather than challenge, their preexisting beliefs. I test my argument against a variety of data sources, including opinion surveys and state level Swine Flu vaccination rate data.
HUMAN OBJECT TRACKING IN VIDEO SEQUENCES

The object representation and tracking is one of the important tasks in computer vision. The object can be represented in various ways and in this paper the objects are represented using the properties of the HSV color space. Adaptive k-means clustering algorithm was applied to cluster objects centroids color values and co-ordinates were sent to next frame for clustering. After clustering, for comparing the objects present in both the reference frame and the target frame, a similarity measure was proposed which uses position, color and size of the objects for comparison. Based on the similarity value, the objects were detected and tracked. The performance of the proposed approach was verified with human objects and the same was effectively tracked. The comparison was carried with similar methods and the results are encouraging.
A Low Quiescent Current Fast Settling Capacitor-less Low Drop Out Regulator Employing Multiple Loops

This paper presents a fast transient and low noise capacitor-less LDO using multiple loops. The proposed LDO exploits adaptive biasing, bulk modulation and a fast reacting control loop for achieving high performance striking reasonable tradeoffs among quiescent current, transient response and stability. The proposed LDO offers a load regulation of 0. 095µV/mA while consuming quiescent current of 16 µA. It exhibits a load transient of 134.23mV with a settling time of 240.8ns against 0 to 100mA load variation with 40pF output capacitor. It exhibits an integrated noise of 31.027 pV2 /Hz at 10 Hz for a maximum load current of 100mA. The proposed LDO is designed using 0.18-µm 1P6 CMOS process.
Deep Differential Recurrent Neural Networks

Due to the special gating schemes of Long Short-Term Memory (LSTM), LSTMs have shown greater potential to process complex sequential information than the traditional Recurrent Neural Network (RNN). The conventional LSTM, however, fails to take into consideration the impact of salient spatio-temporal dynamics present in the sequential input data. This problem was first addressed by the differential Recurrent Neural Network (dRNN), which uses a differential gating scheme known as Derivative of States (DoS). DoS uses higher orders of internal state derivatives to analyze the change in information gain caused by the salient motions between the successive frames. The weighted combination of several orders of DoS is then used to modulate the gates in dRNN. While each individual order of DoS is good at modeling a certain level of salient spatio-temporal sequences, the sum of all the orders of DoS could distort the detected motion patterns. To address this problem, we propose to control the LSTM gates via individual orders of DoS and stack multiple levels of LSTM cells in an increasing order of state derivatives. The proposed model progressively builds up the ability of the LSTM gates to detect salient dynamical patterns in deeper stacked layers modeling higher orders of DoS, and thus the proposed LSTM model is termed deep differential Recurrent Neural Network (d2RNN). The effectiveness of the proposed model is demonstrated on two publicly available human activity datasets: NUS-HGA and Violent-Flows. The proposed model outperforms both LSTM and non-LSTM based state-of-the-art algorithms.
Synchronization of intrinsic 0.1‐Hz blood‐oxygen‐level‐dependent oscillations in amygdala and prefrontal cortex in subjects with increased state anxiety

Low‐frequency oscillations with a dominant frequency at 0.1 Hz are one of the most influential intrinsic blood‐oxygen‐level‐dependent (BOLD) signals. This raises the question if vascular BOLD oscillations (originating from blood flow in the brain) and intrinsic slow neural activity fluctuations (neural BOLD oscillations) can be differentiated. In this study, we report on two different approaches: first, on computing the phase‐locking value in the frequency band 0.07–0.13 Hz between heart beat‐to‐beat interval (RRI) and BOLD oscillations and second, between multiple BOLD oscillations (functional connectivity) in four resting states in 23 scanner‐naïve, anxious healthy subjects. The first method revealed that vascular 0.1‐Hz BOLD oscillations preceded those in RRI signals by 1.7 ± 0.6 s and neural BOLD oscillations lagged RRI oscillations by 0.8 ± 0.5 s. Together, vascular BOLD oscillations preceded neural BOLD oscillations by ~90° or ~2.5 s. To verify this discrimination, connectivity patterns of neural and vascular 0.1‐Hz BOLD oscillations were compared in 26 regions involved in processing of emotions. Neural BOLD oscillations revealed significant phase‐coupling between amygdala and medial frontal cortex, while vascular BOLD oscillations showed highly significant phase‐coupling between amygdala and multiple regions in the supply areas of the anterior and medial cerebral arteries. This suggests that not only slow neural and vascular BOLD oscillations can be dissociated but also that two strategies may exist to optimize regulation of anxiety, that is increased functional connectivity between amygdala and medial frontal cortex, and increased cerebral blood flow in amygdala and related structures.
An Efficient and Privacy-Preserving Multiuser Cloud-Based LBS Query Scheme

Location-based services (LBSs) are increasingly popular in today’s society. People reveal their location information to LBS providers to obtain personalized services such as map directions, restaurant recommendations, and taxi reservations. Usually, LBS providers offer user privacy protection statement to assure users that their private location information would not be given away. However, many LBSs run on third-party cloud infrastructures. It is challenging to guarantee user location privacy against curious cloud operators while still permitting users to query their own location information data. In this paper, we propose an efficient privacy-preserving cloud-based LBS query scheme for the multiuser setting. We encrypt LBS data and LBS queries with a hybrid encryption mechanism, which can efficiently implement privacy-preserving search over encrypted LBS data and is very suitable for the multiuser setting with secure and effective user enrollment and user revocation. This paper contains security analysis and performance experiments to demonstrate the privacy-preserving properties and efficiency of our proposed scheme.
Development of an immunochromatographic assay for the β-adrenergic agonist feed additive zilpaterol

ABSTRACT Zilpaterol is a β-adrenergic agonist feed additive approved in the United States to increase weight gain and improve feed efficiency of cattle. A zilpaterol immunochromatographic assay was developed as an economical and user-friendly rapid detection method for zilpaterol and validated using urine and tissue samples derived from animal studies. The assay sensitivity was 1.7–23.2 ng g−1 or mL−1 across a variety of feed and animal matrices and did not cross-react with clenbuterol or ractopamine. No sample pre-treatment of cattle and sheep urine was needed, but horse urine and feed required dilution; skeletal muscle required solvent extraction prior to testing. Of 32 incurred sheep urine samples tested, zilpaterol content was correctly identified in all but 2 samples. Horse urine containing >10 ng mL−1 of incurred zilpaterol residue (n = 48) was correctly identified as zilpaterol positive. The assay correctly identified 0-day withdrawal sheep muscle samples as zilpaterol positive and the control and longer withdrawal day sheep muscle samples as negative. Zilpaterol was demonstrated to be stable in horse urine when stored at −20°C for 7 years.
Multi-compartment model of brain tissues from T2 relaxometry MRI using gamma distribution

The brain microstructure, especially myelinated axons and free fluids, may provide useful insight into brain neurodegenerative diseases such as multiple sclerosis (MS). These may be distinguished based on their transverse relaxation times which can be measured using T2 relaxometry MRI. However, due to physical limitations on achievable resolution, each voxel contains a combination of these tissues, rendering the estimation complex. We present a novel multi-compartment T2 (MCT2) estimation based on variable projection, applicable to any MCT2 microstructure model. We derive this estimation for a three-gamma distribution model. We validate our framework on synthetic data and illustrate its potential on healthy volunteer and MS patient data.
Clinical and experimental study on fatty acid composition of bone marrow lipid in hematologic disorders.

The fatty acid composition of bone marrow lipid was studied in 10 normal individuals and in 90 patients with a hematologic disorders. Simultaneously , the fatty acid composition of bone marrow was studied in rabbits and dogs which were injected with nitromin and cortisone, and others which were irradiated and subjected to periodic venesection. The fatty acid composition of normal human bone marrow consisted mainly of saturated and unsaturated fatty acid ranging from lauric acid to arachi-donic acid. The predominant fatty acids were as follows: oleic acid 35.2 ±4.9%, palmitic acid 27.8±2.5%, linoleic acid 15.3±2.9%, palmitoleic acid 8.1±2.7%, stearic acid 6.3±1.4%. Lauric, myristic, linolenic, ara-chidonic acid were also present but in smaller amounts. In the patients with hematologic disorders, the fatty acid. composition of bone marrow were variable. In the experimental study, the certain changes of fatty acid composition of the bone marrow were observed, but in adipose tissue similar variation were not observed. The conclusion drawn from this study were: (1) all hematologic disorders were accompanied by the abnormalities of fatty acid metabolism in the bone marrow, and (2) bone marrow, lipid had, in addition to its function as fat stores, protection of tissue, and filling of tissue interstices, an active role in hematopoiesis.
Space-time turbo equalization and symbol detection in frequency selective MIMO channels

A computationally efficient space-time turbo equalization algorithm is derived for frequency selective multiple-input multiple-output (MIMO) channels. The algorithm is an extension of the iterative equalization algorithm by Reynolds and Wang (2001) for frequency selective fading channels. This paper's proposed equalizer performs MIMO channel estimation, multiple user signal detection, and decoding, jointly all in an iterative manner. The iterative channel estimator achieves high accuracy in estimating channel parameters even if only a relatively small number of unique word symbols are available. The multiple user signal detector (MUSD) consists of soft interference cancellers for the multiple users, each followed by a minimum mean square error (MMSE) filter. With this simple structure, the proposed detector achieves a drastic reduction in computational complexity compared with conventional trellis-based turbo equalizers. Simulation results show the proposed equalizer can properly separate multiple user signals in frequency selective MIMO channels.
Gene Therapy for Chronic HBV—Can We Eliminate cccDNA?

Chronic infection with the hepatitis B virus (HBV) is a global health concern and accounts for approximately 1 million deaths annually. Amongst other limitations of current anti-HBV treatment, failure to eliminate the viral covalently closed circular DNA (cccDNA) and emergence of resistance remain the most worrisome. Viral rebound from latent episomal cccDNA reservoirs occurs following cessation of therapy, patient non-compliance, or the development of escape mutants. Simultaneous viral co-infections, such as by HIV-1, further complicate therapeutic interventions. These challenges have prompted development of novel targeted hepatitis B therapies. Given the ease with which highly specific and potent nucleic acid therapeutics can be rationally designed, gene therapy has generated interest for antiviral application. Gene therapy strategies developed for HBV include gene silencing by harnessing RNA interference, transcriptional inhibition through epigenetic modification of target DNA, genome editing by designer nucleases, and immune modulation with cytokines. DNA-binding domains and effectors based on the zinc finger (ZF), transcription activator-like effector (TALE), and clustered regularly interspaced short palindromic repeat (CRISPR) systems are remarkably well suited to targeting episomal cccDNA. This review discusses recent developments and challenges facing the field of anti-HBV gene therapy, its potential curative significance and the progress towards clinical application.
Eye on the Ball: Table Tennis as a Pro-Health Form of Leisure-Time Physical Activity

Background: The article is devoted to an analysis of leisure-time (amateur) table tennis in Poland, its practitioners and the regularities of their activity. Methods: The study examined 12,406 persons in 4689 households (representative for the population). We used binary logistic regression and descriptive statistics in order to identify the patterns and determinants of table-tennis practice in Poland. Results: Table tennis is practised by 2.8% of population, and by 6.6% of physically active Poles. Among adults it is predominantly an occasional recreational game, not performed as a sport per se. Among children, it is often the part of physical education (PE) classes. Statistically significant predictors of contact with table tennis are: gender, age, income, place of residence, children in the household and being a student. Conclusions: Due to the undeniable benefits of table tennis (health, pleasure, personal and social development), the sport is recommended for use as a tool in increasing the (overall low) physical activity of Poles. Its popularization requires promotion in the media (as a health-oriented activity) and using various channels, including public places, the workplace (as part of corporate social responsibility) and physical education classes at school.
Characterization of Unsaturated Hydraulic Conductivity in Fractured Media Using the Multistep Outflow Method - 15461

The multistep outflow method is routinely used to characterize the unsaturated hydraulic conductivity of soils. The technique involves placing a soil sample in a pressure plate apparatus, subjecting the sample to multiple gas pressures in discrete steps through time, and measuring the transient volume of pore fluid extracted. Unsaturated hydraulic property values are estimated through inverse modeling of the experimental conditions. In this study the multistep outflow concept was applied to micro-cracked cementitious materials to assess the efficacy of the technique for these materials. The cementitious materials tested were salt-waste simulant grout samples artificially damaged through oven-drying. Compared to typical soils, fractured media exhibit higher saturated conductivity and lower air-entry pressure, and the volume of fluid extractable from fractures is much lower than soil porosity. To accommodate these material differences the standard test apparatus was modified to incorporate a higher conductivity ceramic pressure plate, a high-precision digital balance for logging outflow mass, a low volume (diameter) effluent line, multiple inline high-precision gas regulators, and a high-precision low-range pressure gauge. Testing to date indicates that the modified apparatus can provide a viable means to measure the unsaturated hydraulic properties of micro-fractured cementitious materials. However the accuracy/uniqueness of inverse modeling is limited by the inherent characteristics of fractured media: high saturated conductivity, low air-entry pressure, and strong non-linearities. Hydraulic property results in the form of van Genuchten / Mualem curves are presented for three fractured grout specimens. DOE Performance Assessments often involve cementitious barriers and/or waste forms that are predicted or assumed to degrade over time due to various mechanisms such as carbonation-influenced reinforcing steel corrosion, external sulfate attack, differential settlement, and seismic activity. Physical degradation typically takes the form of small-scale cracking / fracturing, and the affected materials reside in unsaturated hydrogeologic zones. In these cases, unsaturated hydraulic properties are needed for fractured cementitious materials to simulate moisture movement and contaminant transport within and around the facility. The outflow extraction method, as implemented in the present study, provides a suitable method for estimating these material properties.
Numerical simulations of stratocumulus processing of cloud condensation nuclei through

The role of drop collision-coalescence as a means of reducing drop number concentrations, and hence cloud condensation nucleus (CCN) concentrations as these are cycled in the stratocumulus-capped marine boundary layer, is investigated. We focus on the impact of this process on the mass-mean size of CCN in the absence of wet deposition, and compare this mechanism with size changes resulting from mass addition through aqueous chemistry. The modeling framework is a two-dimensional eddy-resolving model that includes explicit treatment of aerosol and drop spectra, as well as the solute transfer between drop size bins. The microphysical processes considered are droplet activation, condensation/evaporation, collision-coalescence, sedimentation and . regeneration of particles following complete evaporation. It is shown that for a case exhibiting negligible wet deposition, collision-coalescence can significantly reduce drop concentrations (22% 1 h- ) resulting in a measurable increase in particle mass-mean radius of about 7% h -1. In order to extend the validity of these results, trajectory analyses of parcel in-cloud residence times have been used together with box model calculations of collision-coalescence to explore the parameters affecting processing through collision- coalescence. This trajectory information is also used to deduce the extent of in-cloud conversion of SO2 to sulfate. Comparisons show that the two mechanisms may produce comparable rates of increase in the mean particle size under certain conditions. Results for remote marine conditions suggest that aqueous phase chemistry may have a greater impact at lower cloud liquid-water contents, whereas collision-coalescence may dominate at higher liquid-water contents, or for broader drop spectra.
Piezoelectric Nanogenerators Based on Zinc Oxide Nanowire Arrays

We have converted nanoscale mechanical energy into electrical energy by means of piezoelectric zinc oxide nanowire (NW) arrays. The aligned NWs are deflected with a conductive atomic force microscope tip in contact mode. The coupling of piezoelectric and semiconducting properties in zinc oxide creates a strain field and charge separation across the NW as a result of its bending. The rectifying characteristic of the Schottky barrier formed between the metal tip and the NW leads to electrical current generation. The efficiency of the NW-based piezoelectric power generator is estimated to be 17 to 30%. This approach has the potential of converting mechanical, vibrational, and/or hydraulic energy into electricity for powering nanodevices.
Remotely detecting the signal of a local decohering process in spin chains

We study the dynamics of a one dimensional quantum spin chain evolving from unentangled or entangled initial state. At a given instant of time a quantum dynamical process (ex. quantum measurement operation) is performed on a single spin at one end of the chain, decohering the system. Through the further unitary evolution, a signal propagates in the spin chain, which can be detected from a measurement on a different spin at later times. From the dynamical unitary evolution of the decohered state from the epoch time, it is possible to detect the occurrence of the quantum operation. The propagation of the signal for the dynamical process, and the speed of the signal are investigated for various spin models, viz. using the Ising, Heisenberg and transverse-XY dynamics.
New Challenges in Targeting Signaling Pathways in Acute Lymphoblastic Leukemia by NGS Approaches: An Update

The identification and study of genetic alterations involved in various signaling pathways associated with the pathogenesis of acute lymphoblastic leukemia (ALL) and the application of recent next-generation sequencing (NGS) in the identification of these lesions not only broaden our understanding of the involvement of various genetic alterations in the pathogenesis of the disease but also identify new therapeutic targets for future clinical trials. The present review describes the main deletions, amplifications, sequence mutations, epigenetic lesions, and new structural DNA rearrangements detected by NGS in B-ALL and T-ALL and their clinical importance for therapeutic procedures. We reviewed the molecular basis of pathways including transcriptional regulation, lymphoid differentiation and development, TP53 and the cell cycle, RAS signaling, JAK/STAT, NOTCH, PI3K/AKT/mTOR, Wnt/β-catenin signaling, chromatin structure modifiers, and epigenetic regulators. The implementation of NGS strategies has enabled important mutated genes in each pathway, their associations with the genetic subtypes of ALL, and their outcomes, which will be described further. We also discuss classic and new cryptic DNA rearrangements in ALL identified by mRNA-seq strategies. Novel cooperative abnormalities in ALL could be key prognostic and/or predictive biomarkers for selecting the best frontline treatment and for developing therapies after the first relapse or refractory disease.