16 research outputs found
Nonparametric Modeling and Prognosis of Condition Monitoring Signals Using Multivariate Gaussian Convolution Processes
<p>Condition monitoring (CM) signals play a critical role in assessing the remaining useful life of in-service components. In this article, an alternative view on modeling CM signals is proposed. This view draws its roots from multitask learning and is based on treating each CM signal as an individual task. Each task is then expressed as a convolution of a latent function drawn from a Gaussian process (GP), and the transfer of knowledge is achieved through sharing these latent functions between historical and in-service CM signals. Aside from being nonparametric, the flexible and individualistic approach in our model can account for heterogeneity in the data and automatically infer the commonalities between the new testing observations and CM signals in the historical dataset. The robustness and advantageous features of the proposed method are demonstrated through numerical studies and a case study with real-world data in the application to find the remaining useful life prediction of automotive lead-acid batteries. Technical details and additional numerical results are available in the supplementary materials.</p
Retraining and Optimizing DNA-Hydrolyzing Deoxyribozymes for Robust Single- and Multiple-Turnover Activities
Recently,
we reported two classes of Zn<sup>2+</sup>-dependent
DNA-hydrolyzing deoxyribozymes. The class I deoxyribozymes can adopt
a secondary structure of either hairpin or stem-loop-stem. The corresponding
most active representatives, I-R1 and I-R3, exhibit single-turnover <i>k</i><sub>obs</sub> values of ∼0.059 and ∼1.0
min<sup>–1</sup> at 37 °C, respectively. Further analysis
revealed that I-R3 could perform slow multiple-turnover catalysis
with a <i>k</i><sub>cat</sub> of ∼0.017 min<sup>–1</sup> at 37 °C. In this study, we sought to retrain and optimize
the class I deoxyribozymes for robust single- and multiple-turnover
cleavage activities. Refined consensus sequences were derived based
on the data of <i>in vitro</i> reselection from the degenerate
DNA pools. By examining individual candidates, we obtained the I-R1
mutants I-R1a-c with improved single-turnover <i>k</i><sub>obs</sub> values of 0.68–0.76 min<sup>–1</sup> at 37
°C, over 10 times faster than I-R1. Meanwhile, we further demonstrated
that I-R1a–c and I-R3 are thermophilic. As temperature went
higher beyond 45 °C, I-R3 cleaved faster with the <i>k</i><sub>obs</sub> value reaching its maximum of ∼3.5 min<sup>–1</sup> at 54 °C. Using a series of the <i>k</i><sub>obs</sub> values of I-R3 from 37 to 54 °C, we calculated
the apparent activation energy <i>E</i><sub>a</sub> to be
∼15 ± 3 kcal/mol for the DNA-catalyzed hydrolysis of DNA
phosphodiester bond. In addition, we were able to design a simple
yet efficient thermal-cycling protocol to boost the effective <i>k</i><sub>cat</sub> of I-R3 from 0.017 to 0.50 min<sup>–1</sup>, which corresponds to an ∼30-fold improvement of the multiple-turnover
activity. The data and findings provide insights on the enzymatic
robustness of DNA-catalyzed DNA hydrolysis and offer general strategies
to study various DNA enzymes
Short‑, Medium‑, and Long-Chain Chlorinated Paraffins in Wildlife from Paddy Fields in the Yangtze River Delta
Short-chain
chlorinated paraffins (SCCPs) were added to Annex A
of the Stockholm Convention on Persistent Organic Pollutants in April,
2017. As a consequence of this regulation, increasing production and
usage of alternatives, such as medium- and long-chain chlorinated
paraffins (MCCPs and LCCPs, respectively), is expected. Little is
known about the environmental fate and behavior of MCCPs and LCCPs.
In the present study, SCCPs, MCCPs, and LCCPs were analyzed in nine
wildlife species from paddy fields in the Yangtze River Delta, China,
using atmospheric pressure chemical ionization-quadrupole time-of-flight
mass spectrometry. SCCPs, MCCPs, and LCCPs were detected in all samples
at concentrations ranging from <91–43 000, 96–33 000,
and 14–10 000 ng/g lipid, respectively. Most species
contained primarily MCCPs (on average 44%), with the exception of
collared scops owl and common cuckoo, in which SCCPs (43%) accumulated
to a significantly (i.e., <i>p</i> < 0.05) greater extent
than MCCPs (40%). Cl<sub>6</sub> groups were dominant in most species
except for yellow weasel and short-tailed mamushi, which contained
primarily Cl<sub>7</sub> groups. Principal components analysis, together
with CP concentrations and carbon stable isotope analysis showed that
habitat and feeding habits were key factors driving CP accumulation
and congener group patterns in wildlife. This is the first report
of LCCP exposure in wildlife and highlights the need for data on risks
associated with CP usage
Lithium-Ion Batteries: Charged by Triboelectric Nanogenerators with Pulsed Output Based on the Enhanced Cycling Stability
The triboelectric
nanogenerator (TENG) has been used to store its generated energy into
lithium-ion batteries (LIBs); however, the influences of its pulse
current and high voltage on LIB polarization and dynamic behaviors
have not been investigated yet. In this paper, it is found that LIBs
based on the phase transition reaction of the lithium storage mechanism
[LiFePO<sub>4</sub> (LFP) and Li<sub>4</sub>Ti<sub>5</sub>O<sub>12</sub> (LTO) electrodes] are more suitable for charging by TENGs. Thus,
the enhanced cycling capacity, Coulombic efficiency (nearly 100% for
LTO electrode), and energy storage efficiency (85.3% for the LFP–LTO
electrode) are successfully achieved. Moreover, the pulse current
has a positive effect on the increase of the Li-ion extraction, reducing
the charge-transfer resistance (<i>R</i><sub>ct</sub>) for
all studied electrodes as well (LFP, LiNi<sub>0.6</sub>Co<sub>0.2</sub>Mn<sub>0.2</sub>O<sub>2</sub>, LTO, and graphite). The excellent
cyclability, high Coulombic, and energy storage efficiencies demonstrated
the availability of storing pulsed energy generated by TENGs. This
research has provided a promising analysis to obtain an enhanced charging
methodology, which provides significant guidance for the scientific
research of the LIBs
Screen-Printed Washable Electronic Textiles as Self-Powered Touch/Gesture Tribo-Sensors for Intelligent Human–Machine Interaction
Multifunctional
electronic textiles (E-textiles) with embedded
electric circuits hold great application prospects for future wearable
electronics. However, most E-textiles still have critical challenges,
including air permeability, satisfactory washability, and mass fabrication.
In this work, we fabricate a washable E-textile that addresses all
of the concerns and shows its application as a self-powered triboelectric
gesture textile for intelligent human–machine interfacing.
Utilizing conductive carbon nanotubes (CNTs) and screen-printing technology,
this kind of E-textile embraces high conductivity (0.2 kΩ/sq),
high air permeability (88.2 mm/s), and can be manufactured on common
fabric at large scales. Due to the advantage of the interaction between
the CNTs and the fabrics, the electrode shows excellent stability
under harsh mechanical deformation and even after being washed. Moreover,
based on a single-electrode mode triboelectric nanogenerator and electrode
pattern design, our E-textile exhibits highly sensitive touch/gesture
sensing performance and has potential applications for human–machine
interfacing
Screen-Printed Washable Electronic Textiles as Self-Powered Touch/Gesture Tribo-Sensors for Intelligent Human–Machine Interaction
Multifunctional
electronic textiles (E-textiles) with embedded
electric circuits hold great application prospects for future wearable
electronics. However, most E-textiles still have critical challenges,
including air permeability, satisfactory washability, and mass fabrication.
In this work, we fabricate a washable E-textile that addresses all
of the concerns and shows its application as a self-powered triboelectric
gesture textile for intelligent human–machine interfacing.
Utilizing conductive carbon nanotubes (CNTs) and screen-printing technology,
this kind of E-textile embraces high conductivity (0.2 kΩ/sq),
high air permeability (88.2 mm/s), and can be manufactured on common
fabric at large scales. Due to the advantage of the interaction between
the CNTs and the fabrics, the electrode shows excellent stability
under harsh mechanical deformation and even after being washed. Moreover,
based on a single-electrode mode triboelectric nanogenerator and electrode
pattern design, our E-textile exhibits highly sensitive touch/gesture
sensing performance and has potential applications for human–machine
interfacing
Screen-Printed Washable Electronic Textiles as Self-Powered Touch/Gesture Tribo-Sensors for Intelligent Human–Machine Interaction
Multifunctional
electronic textiles (E-textiles) with embedded
electric circuits hold great application prospects for future wearable
electronics. However, most E-textiles still have critical challenges,
including air permeability, satisfactory washability, and mass fabrication.
In this work, we fabricate a washable E-textile that addresses all
of the concerns and shows its application as a self-powered triboelectric
gesture textile for intelligent human–machine interfacing.
Utilizing conductive carbon nanotubes (CNTs) and screen-printing technology,
this kind of E-textile embraces high conductivity (0.2 kΩ/sq),
high air permeability (88.2 mm/s), and can be manufactured on common
fabric at large scales. Due to the advantage of the interaction between
the CNTs and the fabrics, the electrode shows excellent stability
under harsh mechanical deformation and even after being washed. Moreover,
based on a single-electrode mode triboelectric nanogenerator and electrode
pattern design, our E-textile exhibits highly sensitive touch/gesture
sensing performance and has potential applications for human–machine
interfacing
All-Nanofiber-Based Ultralight Stretchable Triboelectric Nanogenerator for Self-Powered Wearable Electronics
The
flexible and stretchable electronics have been considered as next-generation
electronics. Stretchable triboelectric nanogenerators (S-TENGs) with
both multifunction and comfort have become a hot field of research
for wearable electronic devices recently. Here, we designed an all-nanofiber-based,
ultralight, S-TENG that could be softly attached on skins for motion
energy harvesting and self-powered biomechanical monitoring. The S-TENG
consisted of only two nanofiber membranes: a polyvinylidene fluoride
nanofiber membrane (PVDFNM) supported by thermoplastic polyurethane
nanofiber membrane (TPUNM) was used as the frictional layer, and a
multiwalled carbon nanotube (MWCNT) conductive material screen-printed
on the TPUNM was used as the electrode layer. Due to the excellent
stretchability of TPUNM, the S-TENG could generate electricity under
various types of deformation, and regains its original performance
after intense mechanical extension, even if it is partially cut or
damaged. Owing to the great electronegativity of PVDFNM, the device
generated a maximum voltage of 225 V and a current of 4.5 μA
with an electrode area of 6 Ă— 1 cm<sup>2</sup>. The S-TENG has
great potential applications in self-powered wearable devices, electronic
skins, and smart sensor networks
Screen-Printed Washable Electronic Textiles as Self-Powered Touch/Gesture Tribo-Sensors for Intelligent Human–Machine Interaction
Multifunctional
electronic textiles (E-textiles) with embedded
electric circuits hold great application prospects for future wearable
electronics. However, most E-textiles still have critical challenges,
including air permeability, satisfactory washability, and mass fabrication.
In this work, we fabricate a washable E-textile that addresses all
of the concerns and shows its application as a self-powered triboelectric
gesture textile for intelligent human–machine interfacing.
Utilizing conductive carbon nanotubes (CNTs) and screen-printing technology,
this kind of E-textile embraces high conductivity (0.2 kΩ/sq),
high air permeability (88.2 mm/s), and can be manufactured on common
fabric at large scales. Due to the advantage of the interaction between
the CNTs and the fabrics, the electrode shows excellent stability
under harsh mechanical deformation and even after being washed. Moreover,
based on a single-electrode mode triboelectric nanogenerator and electrode
pattern design, our E-textile exhibits highly sensitive touch/gesture
sensing performance and has potential applications for human–machine
interfacing
Screen-Printed Washable Electronic Textiles as Self-Powered Touch/Gesture Tribo-Sensors for Intelligent Human–Machine Interaction
Multifunctional
electronic textiles (E-textiles) with embedded
electric circuits hold great application prospects for future wearable
electronics. However, most E-textiles still have critical challenges,
including air permeability, satisfactory washability, and mass fabrication.
In this work, we fabricate a washable E-textile that addresses all
of the concerns and shows its application as a self-powered triboelectric
gesture textile for intelligent human–machine interfacing.
Utilizing conductive carbon nanotubes (CNTs) and screen-printing technology,
this kind of E-textile embraces high conductivity (0.2 kΩ/sq),
high air permeability (88.2 mm/s), and can be manufactured on common
fabric at large scales. Due to the advantage of the interaction between
the CNTs and the fabrics, the electrode shows excellent stability
under harsh mechanical deformation and even after being washed. Moreover,
based on a single-electrode mode triboelectric nanogenerator and electrode
pattern design, our E-textile exhibits highly sensitive touch/gesture
sensing performance and has potential applications for human–machine
interfacing