Microplastic (MP) pollution poses a huge threat to agroecosystems, but the distribution characteristics of MPs in different types of farmland are still largely unknown. In this work, samples from six ...land-use types were collected from Chinese farmlands in five provinces. It was found that MP abundances were in the range of 2783–6366 items/kg in all samples. MP distribution results showed that over 80% of particles were less than 1 mm, and that MP sizes ranging between 0.02 and 0.2 mm represented the greatest proportion. The particle shape classified as fragment (with edges and angular) was the most frequent shape, with an abundance of approximately 54.05%. Polyethylene (PE) and polyamides (PA) were the most abundant polymers in cropped lands; 20.88% and 20.31%, respectively. Statistical analyses showed that lands used for plastic mulching (mulch film and greenhouse crops) had a significantly higher particle abundance, hence identifying plastic mulching as a major contributor to MP pollution in agricultural lands. Furthermore, paddy lands had a significantly higher MP abundance than wheat lands. Variation analyses of MP characteristics revealed that cereal crop farmlands (wheat, paddy land) were more likely to contain fibrous shapes and large MP particles (1–5 mm). Economically important tree lands (orchards, woodlands) were likely to contain fragment shapes and pony-size MPs (0.02–0.2 mm). Discrepancies among farmlands may depend on various reasons, such as mulching plastic application, irrigation, atmospheric fallout, etc. This study provides firsthand evidences about the characteristics of MP pollution in farmlands and explores some predominant MP sources in agroecosystems.
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•MPs pollution of different land-use types of farmland was studied.•The plastic mulching lands exhibited significantly higher particle abundances.•The MP abundances were significantly higher in paddy lands than wheat lands.•Fibers and large particle size (1–5 mm) dominated the MPs in cereal crops farmlands.•Fragment shapes and pony-size MPs (<0.2 mm) were abundant in economical tree lands.
The MP distribution in six land-use types were distinctive, where cereal croplands were more fibers and large MPs, but economical tree lands were fragments and small MPs.
This paper uses the coevolutionary particle swarm optimization (CPSO) method to identify battery parameters. A parameter identification window (PIW), which has the features of a fixed data length and ...real-time response, is used to store a piece of data that indicates the battery operation at the current moment. CPSO uses the data in the PIW to dynamically identify the battery parameters. Each equivalent circuit model (ECM) parameter uses a separate parameter particle swarm (PPS) to optimize their values. In every algorithm cycle, each particle in every PPS only evolves one step. The currently evolved PPS uses the current optimal values of the other PPS in CPSO to evaluate all of the particles and to find the best particle. Every PPS is scheduled by the CPSO, dynamically evolves one by one, and converges in real time to its optimal value, which is an ECM parameter. Real battery data are used to test the algorithm. The experimental results indicate that the fluctuation patterns of the open circuit voltage (OCV) are accurately identified. For the different algorithm parameters, the identification results for the OCV have good consistency, and the deviations between the identification results are less than 5 mV most of the time.
A resorufin-based highly sensitive and selective fluorescence off-on probe with a new recognition moiety for tyrosinase is developed, and applied to detect and image endogenous tyrosinase activity in ...different living cells.
Microplastics (MPs), tiny particles broken down from larger pieces of plastics, have accumulated everywhere on the earth. As an inert carbon stream in aquatic environment, they have been reported as ...carriers for heavy metals and exhibit diverse interactive effects. However, these interactions are still poorly understood, especially mechanisms driving these interactions and how they pose risks on living organisms. In this mini review, a bibliometric analysis in this field was conducted and then the mechanisms driving these interactions were examined, especially emphasizing the important roles of microorganisms on the interactions. Their combined toxic effects and the potential hazards to human health were also discussed. Finally, the future research directions in this field were suggested. This review summarized the recent research progress in this field and highlighted the essential roles of the microbes on the interactions between MPs and heavy metals with the hope to promote more studies to unveil action mechanisms and reduce/eliminate the risks associated with MP presence.
This study used a double machine learning model (based on the random forest algorithm) and spatial Durbin DIDs model to conduct quasi-natural experiments. The results are as follows: (1) innovation ...and reform policy regarding regional industrial chains as well as their resilience can significantly and positively address the development of China’s impossible triangle coupling of energy; (2) implementing the innovation and reform policy for regional industrial chains in other regions can have a significant positive spatial transmission effect on the impossible triangle coupling coordinated development of energy in the region; (3) regional industrial chain resilience can produce a significant positive mediating effect between the innovation and reform policy of regional industrial chains and the safety, reliability, and economic feasibility of green and clean energy systems; (4) under the counterfactual framework, the mechanism path “innovation and reform policy of the regional industry chain→regional industry chain resilience→coordination degree of impossible triangle coupling of energy” has significantly positive direct and indirect effects in both the treatment group and the control group. However, “innovation and reform policy of the regional industrial chain→regional industrial chain resilience→the energy sector’s impossible triangle coupling coordination degree” and “innovation and reform policy of the regional industrial chain→leading power of the regional industrial chain→the energy sector’s impossible triangle coupling coordination degree” have significantly positive direct and indirect effects in the treatment group, but only the direct effect is significant in the control group.
Medical care has become an indispensable part of people’s lives, with a dramatic increase in the volume of medical data (e.g., diagnosis certificates and medical records). Medical data, however, is ...easily stolen, tampered with, or even completely deleted. If the above occurs, medical data cannot be recorded or retrieved in a reliable manner, resulting in delay treatment progress, even endanger the patient’s life. In this paper, we propose a novel blockchain-based data preservation system (DPS) for medical data. To provide a reliable storage solution to ensure the primitiveness and verifiability of stored data while preserving privacy for users, we leverage the blockchain framework. With the proposed DPS, users can preserve important data in perpetuity, and the originality of the data can be verified if tampering is suspected. In addition, we use prudent data storage strategies and a variety of cryptographic algorithms to guarantee user privacy; e.g., an adversary is unable to read the plain text even if the data are stolen. We implement a prototype of the DPS based on the real world blockchain-based platform Ethereum. Performance evaluation results demonstrate the effectiveness and efficiency of the proposed system.
De novo variants (DNVs) with deleterious effects have proved informative in identifying risk genes for early-onset diseases such as congenital heart disease (CHD). A number of statistical methods ...have been proposed for family-based studies or case/control studies to identify risk genes by screening genes with more DNVs than expected by chance in Whole Exome Sequencing (WES) studies. However, the statistical power is still limited for cohorts with thousands of subjects. Under the hypothesis that connected genes in protein-protein interaction (PPI) networks are more likely to share similar disease association status, we developed a Markov Random Field model that can leverage information from publicly available PPI databases to increase power in identifying risk genes. We identified 46 candidate genes with at least 1 DNV in the CHD study cohort, including 18 known human CHD genes and 35 highly expressed genes in mouse developing heart. Our results may shed new insight on the shared protein functionality among risk genes for CHD.
This paper presents a technical overview for low-noise switched reluctance motor (SRM) drives in electric vehicle (EV) applications. With ever-increasing concerns over environmental and cost issues ...associated with permanent magnet machines, there is a technical trend to utilize SRMs in some mass production markets. The SRM is gaining much interest for EVs due to its rare-earth-free characteristic and excellent performance. In spite of many advantages compared with conventional adjustable-speed drives, SRMs suffer from torque ripple and radial distortion (and thus noise and vibration) by their nature. Therefore, for high-performance vehicle applications, it is important and urgent to optimize the SRM system to overcome the drawbacks of the noise and vibration. In order to present clear solutions to the acoustic noise in SRMs, this paper starts by analyzing the mechanism of the radial vibration and torque ripples inherent in the motors, and then focuses on the state-of-the-art technologies to mitigate the radial force and torque ripples. It highlights two categories for low-noise SRMs, including the machine topology improvement and control strategy design for radial vibration mitigation and torque ripple reduction. Advanced technologies are reviewed, classified, and compared accordingly. In addition to these methodologies, the schemes that have been developed by authors are also presented and discussed. Finally, the research status on this topic is summarized and forecast research hotspots are presented. It is our intention that this paper provides the guidance on performance improvements for low-noise SRM drives in EV applications.
Abstract
We study galaxy shapes in the Illustris cosmological hydrodynamic simulation. We find that massive galaxies have a higher probability of being prolate. For galaxies with stellar mass larger ...than 1011 M⊙, 35 out of total 839 galaxies are prolate. For 21 galaxies with stellar mass larger than 1012 M⊙, 9 are prolate, 4 are triaxial while the others are close to being oblate. There are almost no prolate galaxies with stellar mass smaller than 3 × 1011 M⊙. We check the merger history of the prolate galaxies, and find that they are formed by major dry mergers. All the prolate galaxies have at least one such merger, with most having mass ratios between 1:1 and 1:3. The gas fraction (gas mass to total baryon mass) of the progenitors is 0–3 per cent per cent for nearly all these mergers, except for one whose second progenitor contains ∼ 15 per cent gas mass, while its main progenitor still contains less than 5 per cent. For the 35 massive prolate galaxies that we find, 18 of them have minor-axis rotation, and their angular momenta mostly come from the spin angular momenta of the progenitors (usually that of the main progenitor). We analyse the merger orbits of these prolate galaxies and find that most of them experienced a nearly radial merger orbit. Oblate galaxies with major dry mergers can have either radial or circular merger orbits. We further discuss various properties of these prolate galaxies, such as spin parameter λR, spherical anisotropy parameter β, dark matter fraction, as well as inner density slopes for the stellar, dark matter and total mass distributions.
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