This paper proposes a quadrature-shaped pickup coil, which can realize an angular-misalignment insensitive omnidirectional wireless charging system. Recently, the three-dimensional wireless charging ...has shown promising prospects for removing the performance deterioration caused by the positional misalignment, which can transfer power to arbitrary spatial objectives. In the conventional design, the strength and the direction of the induced magnetic field can be adjusted by controlling the excitation currents of transmitting coils. However, the existence of angular misalignment caused by the self-rotation of the pickup unit still can result in a sharp decrease of the transmitted power. Accordingly, this paper proposes and implements a novel pickup coil topology to compensate such huge fluctuations in power transfer, which aims to ensure an angular misalignment insensitive omnidirectional wireless charging. Simulated and experimental results are both given to verify the feasibility of the proposed quadrature-shaped topology.
Human machine interface (HMI) devices, which can convert human motions to electrical signals to control/charge electronic devices, have attracted tremendous attention from the engineering and science ...fields. Herein, the high output voltage from a nonpiezoelectric meso‐poly(lactic acid) (meso‐PLA) electret‐based triboelectric nanogenerator (NG) is combined with the relatively high current from a double‐layered poly(l‐lactic acid) (PLLA)‐based piezoelectric nanogenerator (PENG) for an E‐skin (electronic skin) (HMI) device application. The hybrid NG with a cantilever structure can generate an output voltage of 70 V and a current of 25 µA at the resonance frequency of 19.7 Hz and a tip load of 4.71 g. Moreover, the output power of the hybrid NG reaches 0.31 mW, which is 11% higher than that from the PLLA‐based PENG. Furthermore, it is demonstrated that the PLA‐based hybrid NG can be used to turn a light‐emitting diode light on and off through an energy management circuit during a bending test. Finally, it is demonstrated that the PLA‐based woven E‐skin device can generate the output signals of 35 V (Voc) and 1 µA (Isc) during an elbow bending test. The advantages of biocompatible, ease of fabrication, and relatively high output power in the hybrid NG device show great promise for future E‐skin applications.
A hybrid nanogenerator consisting of a meso‐poly(lactic acid) electret and a poly(l‐lactic acid)‐based piezoelectric nanogenerator for electronic skin applications is reported. It is demonstrated that the hybrid nanogenerator can wirelessly turn a light‐emitting diode light on and off. Finally, the fabricated woven E‐skin device can generate output signals of 35 V and 1 µA during an elbow bending test.
Rapid and efficient tools for early cancer detection have diagnostic and therapeutic value. Given that the DNA hairpin‐based hybridization chain reaction (HCR) is effective in detecting various ...biological targets, a tetrahedral framework DNA‐enhanced (TDN‐enhanced) HCR detection system (T‐probe system) is introduced for cancer‐related targets and its versatility is demonstrated by detecting intracellular target miRNA 21 and cellular membrane target nucleolin. Benefiting from the spatial confinement of the TDN, the T‐probe system demonstrates a high detection rate. It increases the reaction efficiency of nude hairpins in vitro while accurately and rapidly recognizing both membrane and intracellular cancer‐related targets in living cells. Furthermore, it exhibits superior fluorescence in vivo within 15 s of peripheral‐tumor injection and 10 min of tail‐vein injection. The T‐probe system efficiently and accurately images tumor‐related biomarkers in vitro and in vivo, thereby demonstrating great potential for clinical diagnosis and therapeutic applications.
The T‐probe is composed of a hybridization chain reaction (HCR) motif (hairpins) and skeleton motifs (tetrahedral framework DNA (TDNs)), which can recognize the membrane and intracellular tumor biomarkers and trigger a hybridization chain reaction, inducing fluorescence signal release and amplification. This approach leads to a rapid and efficient tumor imaging and detection system in vivo.
•This study reports COVID-19 vaccine effectiveness (VE) in real-world settings.•COVID-19 VE for fully and partially vaccinated individuals.•COVID-19 VE for healthcare workers, the elderly, and ...adults.•The effectiveness of different COVID-19 vaccine brands.
To estimate the coronavirus disease 2019 (COVID-19) vaccine effectiveness (VE) against concerned outcomes in real-world settings.
Studies reporting COVID-19 VE from August 6, 2020 to October 6, 2021 were included. The summary VE (with 95% confidence intervals (95% CI)) against disease related to COVID-19 was estimated. The results were presented in forest plots. Predefined subgroup analyses and sensitivity analyses were also performed.
A total of 51 records were included in this meta-analysis. In fully vaccinated populations, the VE against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, COVID-19-related hospitalization, admission to the intensive care unit, and death was 89.1% (95% CI 85.6–92.6%), 97.2% (95% CI 96.1–98.3%), 97.4% (95% CI 96.0–98.8%), and 99.0% (95% CI 98.5–99.6%), respectively. The VE against infection in the general population aged ≥16 years, the elderly, and healthcare workers was 86.1% (95% CI 77.8–94.4%), 83.8% (95% CI 77.1–90.6%), and 95.3% (95% CI 92.0–98.6%), respectively. For those fully vaccinated against infection, the observed effectiveness of the Pfizer-BioNTech vaccine was 91.2% and of the Moderna vaccine was 98.1%, while the effectiveness of the CoronaVac vaccine was found to be 65.7%.
The COVID-19 vaccines are highly protective against SARS-CoV-2-related diseases in real-world settings.
In real-world decision problems, decision makers usually express their opinions with different preference structures. In order to deal with the heterogeneous preference information in group decision ...making, this paper presents an optimization-based consensus model for group decision making with heterogeneous preference structures (utility values, preference orderings, multiplicative preference relations and additive preference relations). This proposal seeks to minimize the information loss between decision makers’ heterogeneous preference information and individual preference vectors and also seeks the collective solution with a consensus. Meanwhile, in order to justify the consensus model, we discuss its internal aggregation operator between the obtained individual and group preference vectors, demonstrate that the proposed model satisfies the Pareto principle of social choice theory, and prove the uniqueness of the solution to the optimization model. Furthermore, based on the proposed optimization-based consensus model, we present an automatic mechanism to support consensus reaching in the group decision making with heterogeneous preference structures. In the consensus reaching process, the obtained individual and group preference vectors are considered as a decision aid which decision makers can use as a reference to adjust their preference opinions. Finally, detailed simulation experiments and comparison analysis are conducted to demonstrate the feasibility and effectiveness of our proposed model.
With the growing penetration of power electronic converters in power systems, the issue of reliability becomes more critical than ever before. This paper proposes a hierarchical reliability framework ...to evaluate the electric power system reliability from the power electronic converter level to the overall system level. On the converter level, the reliability model of a power electronic converter is developed based on the power electronic devices it is composed of, for which various hourly based input profiles and converter topologies are considered. On the system level, reliability metrics such as expected energy not served (EENS) and loss of load expectation (LOLE) are estimated through a non-sequential Monte Carlo simulation. Machine learning regression models, such as support vector regression (SVR), and random forests (RF) are implemented to bridge the nonlinear reliability relationship between two levels. The proposed framework is demonstrated through the modified IEEE Reliability Test System (RTS) 24-bus network. Numerical results show power converter reliability should be considered as an important factor when evaluating overall system reliability performance.
Chaos has been one of the most effective cryptographic sources since it was first used in image-encryption algorithms. This paper closely examines the development process of chaos-based ...image-encryption algorithms from various angles, including symmetric and asymmetric algorithms, block ciphers and stream ciphers, and integration with other technologies. The unique attributes of chaos, such as sensitivity to initial conditions, topological transitivity, and pseudo-randomness, are conducive to cross-referencing with other disciplines and improving image-encryption methods. Additionally, this paper covers practical application scenarios and current challenges of chaotic image encryption, thereby encouraging researchers to continue developing and complementing existing situations, and may also serve as a basis of future development prospects for chaos-based image encryption.
Amazon droughts have impacted regional ecosystem functioning as well as global carbon cycling. The severe dry‐season droughts in 2005 and 2010, driven by Atlantic sea surface temperature (SST) ...anomaly, have been widely investigated in terms of drought severity and impacts on ecosystems. Although the influence of Pacific SST anomaly on wet‐season precipitation has been well recognized, it remains uncertain to what extent the droughts driven by Pacific SST anomaly could affect forest greenness and photosynthesis in the Amazon. Here, we examined the monthly and annual dynamics of forest greenness and photosynthetic capacity when Amazon ecosystems experienced an extreme drought in 2015/2016 driven by a strong El Niño event. We found that the drought during August 2015–July 2016 was one of the two most severe meteorological droughts since 1901. Due to the enhanced solar radiation during this drought, overall forest greenness showed a small increase, and 21.6% of forests even greened up (greenness index anomaly ≥1 standard deviation). In contrast, solar‐induced chlorophyll fluorescence (SIF), an indicator of vegetation photosynthetic capacity, showed a significant decrease. Responses of forest greenness and photosynthesis decoupled during this drought, indicating that forest photosynthesis could still be suppressed regardless of the variation in canopy greenness. If future El Niño frequency increases as projected by earth system models, droughts would result in persistent reduction in Amazon forest productivity, substantial changes in tree composition, and considerable carbon emissions from Amazon.
Amazon drought of 2015/2016 was one of the two most severe meteorological droughts since 1901. This drought largely reduced forest photosynthesis but had little impact on forest greenness.
The piezoelectric polymer poly(vinylidene fluoride) (PVDF) has been widely employed for energy harvesting or sensors. Its piezoelectricity originates from the unique crystal structure and the ...oriented electric dipoles. Generally, electrospinning (ES) is able to improve the crystallinity and piezoelectricity of PVDF. In this investigation, three types of ES, including far-field ES with random (R-PVDF-FFES) or aligned distribution (A-PVDF-FFES) and near-field ES (PVDF-NFES), are applied to fabricate a one-step polarized PVDF membrane. To compare the piezoelectricity of separated PVDF-NFES fibers, the array of PVDF-NFES fibers is encapsulated in polylactic acid (PLA). The result shows that the piezoelectricity of PVDF is dramatically enhanced by NFES and FFES. In d 31 mode, the current density of PVDF-NFES-PLA is 75.63 pA cm–2 with a 2 Hz shear force, which is four times larger than A-PVDF-FFES (17.62 pA cm–2) or seven times larger than R-PVDF-FFES (10.63 pA cm–2). Due to its outstanding property, the PVDF-NFES-PLA membrane is designed to be applied as a self-powered device. The unimorph cantilevers are prepared to harvest the vibration energy and their output power density reaches 95.3 μW m–2 at a resonance frequency of 31 Hz. Meanwhile, the flexible bending sensor and pressure sensor are fabricated with a PVDF-NFES-PLA membrane, which shows the stable response for pressure with sensitivity values of 864.68 and 22.6 mV kPa–1, respectively.
Extracellular vesicles (EVs) are cell-derived membrane structures enclosing proteins, lipids, RNAs, metabolites, growth factors, and cytokines. EVs have emerged as essential intercellular ...communication regulators in multiple physiological and pathological processes. Previous studies revealed that mesenchymal stem cells (MSCs) could either support or suppress tumor progression in different cancers by paracrine signaling via MSC-derived EVs. Evidence suggested that MSC-derived EVs could mimic their parental cells, possessing pro-tumor and anti-tumor effects, and inherent tumor tropism. Therefore, MSC-derived EVs can be a cell-free cancer treatment alternative. This review discusses different insights regarding MSC-derived EVs' roles in cancer treatment and summarizes bioengineered MSC-derived EVs' applications as safe and versatile anti-tumor agent delivery platforms. Meanwhile, current hurdles of moving MSC-derived EVs from bench to bedside are also discussed. Keywords: Mesenchymal stem cell, Extracellular vesicle, Exosome, Cancer therapy, Drug delivery
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