The streaming instability is a fundamental process that can drive dust–gas dynamics and ultimately planetesimal formation inprotoplanetary discs. As a linear instability, it has been shown that its ...growth with a distribution of dust sizes can be classifiedinto two distinct regimes, fast- and slow-growth, depending on the dust-size distribution and the total dust-to-gas density ratio . Using numerical simulations of an unstratified disc, we bring three cases in different regimes into non-linear saturation. Wefind that the saturation states of the two fast-growth cases are similar to its single-species counterparts. The one with maximumdimensionless stopping timeτs,max=0.1 and =2 drives turbulent vertical dust–gas vortices, while the other withτs,max=2and =0.2 leads to radial traffic jams and filamentary structures of dust particles. The dust density distribution for the former isflat in low densities, while the one for the latter has a low-end cut-off. By contrast, the one slow-growth case results in a virtuallyquiescent state. Moreover, we find that in the fast-growth regime, significant dust segregation by size occurs, with large particlesmoving towards dense regions while small particles remain in the diffuse regions, and the mean radial drift of each dust speciesis appreciably altered from the (initial) drag-force equilibrium. The former effect may skew the spectral index derived frommultiwavelength observations and change the initial size distribution of a pebble cloud for planetesimal formation. The latteralong with turbulent diffusion may influence the radial transport and mixing of solid materials in young protoplanetary discs.
The aim of this work was to develop an easy-to-use food package label for pork shelf-life assessment. Meat samples were packaged in polyethylene terephthalate trays with on-package indicator labels ...and kept at 5 °C for 8 days. These indicators contained three groups of pH-sensitive dyes, i.e., bromocresol purple, bromothymol blue, and a mixture of bromothymol blue and methyl red. Results of pH, total volatile basic nitrogen (TVB-N) contents, aerobic plate counts and sensory scores of pork differentiated between fresh (on 0–3 days), medium fresh (on 4–5 days), and spoiled lean pork (on 6–8 days). Results of total color difference and principal components analysis carried out with colorimetric data of different indicator labels showed that the indicator label made by a mixture of bromothymol blue and methyl red at 3:2 proportion (at an initial pH of 5.0) was able to discriminate fresh (red), medium fresh (goldenrod), and spoiled (green) pork in cold storage. The statistical models obtained by partial least squares, with the color change of label, successfully predicted TVB-N contents and aerobic plate counts of pork. These results suggest the potential feasibility of this particular indicator system for monitoring freshness of packaged pork via color change detected directly using the naked eye.
•pH dye-based indicator labels were studied for lean pork meat spoilage assessment.•Indicator responds via visible color change to volatiles in the package headspace.•Indicator color change presents a similar tendency to microbial growth.•Indicator color change can discriminate fresh, medium fresh, and spoiled pork.
The rapid dissemination of hot information on the Internet has become a common phenomenon in today's society. Traditional methods of information capture and preprocessing often require a lot of ...manpower and material resources, and the captured information has low timeliness and accuracy. The purpose of this paper was to use sensor technology to find and locate network hotspots in time. By collecting user generated content, social media data, news reports, etc., the data is analyzed and mined to identify popular topics and events. In terms of information capture, sensor technology can monitor and understand user activities, the popularity of posts, emotional tendencies, user attention, user interaction, etc., through information monitoring. Network data was collected, such as network latency, data loss rate, and bandwidth utilization. Sensor technology was used to collect social media data to understand the level of public attention to hot events. In information preprocessing, sensor technology was used to remove noise and redundant information in data to ensure data quality. The data were labeled and classified, and the information dissemination rules of network hotspot were analyzed in depth. The average capture accuracy of Method 1 for Hotspot 1, Hotspot 2, and Hotspot 3 was 72.11%, 71.81%, and 72.54%, respectively. The average capture accuracy of Method 2 for Hotspot 1, Hotspot 2, and Hotspot 3 was 82.55%, 83.14%, and 82.91%, respectively. When the data was 40, 80, and 120, the preprocessing times of Method 1 for Post 1 were 8.81 s, 15.47 s, and 18.77 s, respectively. The preprocessing times of Method 2 for Post 1 were 5.97 s, 7.80 s, and 9.25 s, respectively. The application of sensor technology in the capture and preprocessing of network hot information dissemination has brought a variety of innovations, including multi-modal data acquisition, real-time monitoring and analysis, user behavior analysis, data cleaning and integration, anomaly detection and early warning, intelligent recommendation and personalized service, etc., thus improving the accuracy, real-time and personalized degree of information acquisition.
Article Highlights
Emphasized the effective application of sensor technology;
The main findings of the paper can be summarized as follows:
Sensor technology can effectively help capture network hotspot information. The article mentions that by deploying sensor nodes in the network, it can monitor and capture network hot information in real-time, such as hot news and hot topics on social media. Sensor nodes can collect a large amount of data and transmit it over the network to the server for further processing and analysis.
Sensor technology can preprocess the captured data. The paper points out that the sensor node can preprocess the captured data in real-time through the built-in processing algorithm. For example, the text data can be divided into words, noise removal, keyword extraction and other operations to improve the quality and accuracy of the data. This can reduce the load on the server and improve the effectiveness of subsequent analysis.
Provided more efficient methods for information capture;
The meaning of this paper is to emphasize the importance and application value of sensor technology in the capture and preprocessing of network hot information dissemination. The introduction of sensor technology can be more efficient in obtaining and processing network hotspot information, so as to better understand and deal with network hotspot events.
The article points out that the deployment of sensor nodes can monitor and capture hot online information in real-time, such as hot news and hot topics on social media. The large amount of data collected through the sensor nodes can be further analyzed and mined. This process of data capture and preprocessing can help understand the dissemination rules and trends of network hot information.
Somatic cells can be reprogrammed to an ES‐like state to create induced pluripotent stem cells (iPSCs) by ectopic expression of four transcription factors, Oct4, Sox2, Klf4 and cMyc. Here, we show ...that cellular microRNAs (miRNAs) regulate iPSC generation. Knock‐down of key microRNA pathway proteins resulted in significant decreases in reprogramming efficiency. Three miRNA clusters, miR‐17∼92, miR‐106b∼25 and miR‐106a∼363, were shown to be highly induced during early reprogramming stages. Several miRNAs, including miR‐93 and miR‐106b, which have very similar seed regions, greatly enhanced iPSC induction and modulated mesenchymal‐to‐epithelial transition step in the initiation stage of reprogramming, and inhibiting these miRNAs significantly decreased reprogramming efficiency. Moreover, miR‐iPSC clones reached the fully reprogrammed state. Further analysis revealed that Tgfbr2 and p21 are directly targeted by these miRNAs and that siRNA knock‐down of both genes indeed enhanced iPSC induction. Here, for the first time, we demonstrate that miR‐93 and its family members directly target TGF‐β receptor II to enhance iPSC generation. Overall, we demonstrate that miRNAs function in the reprogramming process and that iPSC induction efficiency can be greatly enhanced by modulating miRNA levels in cells.
The generation of induced pluripotent stem cells is limited by the low reprogramming efficiency of somatic cells. Here, three clusters of miRNAs are shown to enhance reprogramming efficiency by targeting the TGF‐β and p53 pathways, which inhibit the process.
The development of solid electrolytes with the combination of high ionic conductivity, electrochemical stability, and resistance to Li dendrites continues to be a challenge. A promising approach is ...to create inorganic–organic composites, where multiple components provide the needed properties, but the high sintering temperature of materials such as ceramics precludes close integration or co‐sintering. Here, new ceramic–salt composite electrolytes that are cold sintered at 130 °C are demonstrated. As a model system, composites of Li1.5Al0.5Ge1.5(PO4)3 (LAGP) or Li1+x
+y
Alx
Ti2−x
Siy
P3−y
O12 (LATP) with bis(trifluoromethanesulfonyl)imide (LiTFSI) salts are cold sintered. The resulting LAGP–LiTFSI and LATP–LiTFSI composites exhibit high relative densities of about 90% and ionic conductivities in excess of 10−4 S cm−1 at 20 °C, which are comparable with the values obtained from LAGP and LATP sintered above 800 °C. It is also demonstrated that cold sintered LAGP–LiTFSI is electrochemically stable in Li symmetric cells over 1800 h at 0.2 mAh cm−2. Cold sintering provides a new approach for bridging the gap in processing temperatures of different materials, thereby enabling high‐performance composites for electrochemical systems.
Ceramic–salt composite solid electrolytes are fabricated through cold sintering at 130 °C. Cold sintering enables integration of bis(trifluoromethanesulfonyl)imide (LiTFSI) with ceramics to achieve ionic conductivities near 10−4 S cm−1 and relative densities of ≈90%. Stable cycling over 1800 h in Li metal symmetric cells is also demonstrated.
Human murine double minute 2 (MDM2) protein is a primary endogenous cellular inhibitor of the tumor suppressor p53 and has been pursued as an attractive cancer therapeutic target. Several potent, ...nonpeptide, small-molecule inhibitors of MDM2 are currently in clinical development. In this paper, we report our design, synthesis, and evaluation of small-molecule MDM2 degraders based on the proteolysis targeting chimera (PROTAC) concept. The most promising compound (MD-224) effectively induces rapid degradation of MDM2 at concentrations <1 nM in human leukemia cells. It achieves an IC
value of 1.5 nM in inhibition of growth of RS4;11 cells and also low nanomolar IC
values in a panel of leukemia cell lines. MD-224 achieves complete and durable tumor regression in vivo in the RS4;11 xenograft tumor model in mice at well-tolerated dose schedules. MD-224 is thus a highly potent and efficacious MDM2 degrader and warrants extensive evaluations as a new class of anticancer agent.
Soil aggregate size significantly impacts microbial communities and soil respiration. Soil total porosity and pH can regulate the distribution of soil bacteria and fungal communities within ...aggregates, thereby influencing soil respiration. However, it is unclear how it affects the microbial community composition distributed in soil aggregates, especially for fungal communities. The roles of soil total porosity and pH in controlling the microbial composition of soil aggregates are also unknown. In this study, we used high-throughput sequencing of the 16S rRNA and ITS gene regions to target bacterial and fungal members of aggregate samples of four sizes (2–4 mm, 1–2 mm, 0.25–1 mm and <0.25 mm). Our results showed that high respiration occurred in soil aggregates of 2–4 mm and 1–2 mm when there was high soil total porosity and low soil pH than in aggregates of 0.25–1 mm and <0.25 mm. Moreover, soil aggregates of 2–4 mm and 1–2 mm were dominated by four bacterial families (Oxalobacteraceae, Sphingomonadaceae, Cytophagaceae and Gemmatimonadaceae) and two fungal families (Lasiosphaeriaceae and Rhizophlyctidaceae), while the 0.25–1 mm and <0.25 mm aggregates were dominated by two bacterial families (Bacillaceae and Clostridiaceae) and one fungal family (Nectriaceae). Our results suggest that soil organic carbon and total porosity positively influenced the bacterial Shannon index, which led to a further positive influence on soil aggregate respiration, while soil pH positively affected the soil fungal Shannon index, leading to increased negative control of the respiration of soil aggregates.
The structural equation modeling (SEM) results show that soil total porosity could directly influence soil respiration. In addition, soil organic carbon and total porosity had a significantly positive direct effect on bacterial Shannon index. Additionally, the soil pH showed a direct negative effect on fungal Shannon index and soil respiration. Soil bacterial and fungal Shannon index had a significantly positive and negative direct effect on soil respiration, respectively. Our study suggests that the difference distribution of soil organic carbon, pH, total porosity in aggregates controlling the soil microbial diversity, and then affect soil aggregate respiration. Display omitted
•Soil aggregates size significantly impacts microbial communities and soil respiration.•High respiration occurred in macro-aggregates with high soil total porosity and low soil pH.•Soil bacterial Shannon index positively influenced the soil respiration.•Soil fungal Shannon index negatively affected the soil respiration.
This paper proposes a framework to perform the sensor classification by using multivariate time series sensors data as inputs. The framework encodes multivariate time series data into two-dimensional ...colored images, and concatenate the images into one bigger image for classification through a Convolutional Neural Network (ConvNet). This study applied three transformation methods to encode time series into images: Gramian Angular Summation Field (GASF), Gramian Angular Difference Field (GADF), and Markov Transition Field (MTF). Two open multivariate datasets were used to evaluate the impact of using different transformation methods, the sequences of concatenating images, and the complexity of ConvNet architectures on classification accuracy. The results show that the selection of transformation methods and the sequence of concatenation do not affect the prediction outcome significantly. Surprisingly, the simple structure of ConvNet is sufficient enough for classification as it performed equally well with the complex structure of VGGNet. The results were also compared with other classification methods and found that the proposed framework outperformed other methods in terms of classification accuracy.
A traction drive control system (TDCS) plays an important role in safety running of high-speed trains. This paper presents a new fault-injection strategy for safety testing and fault diagnosis ...verification in the TDCS. First, the fault scenarios on the signal level of each faulty component are analyzed. Then, the fault-injection method based on signal conditioning is proposed, and the injected signal, reflecting the fault scenario at a fault point, is generated to simulate the fault scenarios. Subsequently, the injected signal benchmark is constructed for all faults in traction converters, traction motors, sensors, and traction control units. Finally, a fault-injection benchmark platform is developed to simulate various fault scenarios in the TDCS. The simulation and comparison results show that the presented strategy is effective and easy to implement.
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