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The increasing frequency of global drought events poses a significant threat to the stability of grassland ecosystems' functionality. The Inner Mongolian grasslands stand out as one of the world's most drought-prone regions, facing elevated drought risks compared to other biomes. An in-depth comprehension of the impact of drought on grassland ecosystems is paramount for their long-term sustainability. Using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2018, this study identified various drought events within the Inner Mongolian grasslands, encompassing moderate drought, severe drought, and extreme drought. The resistance of the vegetation to the different drought conditions, assessed through net primary productivity (NPP) as a metric (reflecting its capacity to maintain its original level during drought periods), was examined. The research findings indicated that the period from 2001 to 2018 witnessed a substantial increase in both the frequency and the extent of drought events compared to the period from 1982 to 2000, particularly concerning severe and extreme droughts. The areas most severely impacted by extreme drought were the Xilingol League and the Alxa League. From 1982–2000 to 2001–2018, under moderate drought conditions, vegetation resistance exhibited a minor decrease in the central and eastern regions but experienced a slight increase in the western region. In contrast, under severe drought conditions, the western region saw a significant decrease in vegetation resistance. Remarkably, under extreme drought conditions, the western region showed a substantial increase in vegetation resistance, while the central and eastern regions experienced a slight decrease. Across all three drought conditions, as precipitation levels declined, the resistance of the meadow–steppe–desert ecosystems demonstrated a high–low–high distribution pattern. The temperate desert steppe exhibited a minimal vulnerability to drought, boasting resistance levels exceeding 0.9. Notably, extreme drought had the most pronounced impact on the temperate meadow steppe, temperate steppe, and temperate desert steppe, particularly within the temperate meadow steppe category. Given these findings, the authorities responsible for grassland management should prioritize regions characterized by frequent drought occurrences and low drought resistance, such as Ulanqab City, the Xilingol League, and the western part of Hulun Buir City. Safeguarding steppe ecosystems is of paramount importance for stabilizing vegetation productivity and land carbon sinks, especially under the anticipated exacerbation of climate conditions in the future. [ABSTRACT FROM AUTHOR]

Noncontact heart rate monitoring techniques based on millimeter-wave radar have advantages in unique medical scenarios. However, the accuracy of the existing noncontact heart rate estimation methods is still limited by interference, such as DC offsets, respiratory harmonics, and environmental noise. Additionally, these methods still require longer observation times. Most deep learning methods related to heart rate estimation still need to collect more heart rate marker data for training. To address the above problems, this paper introduces a radar signal-based heart rate estimation network named the "masked phase autoencoders with a vision transformer network" (MVN). This network is grounded on masked autoencoders (MAEs) for self-supervised pretraining and a vision transformer (ViT) for transfer learning. During the phase preprocessing stage, phase differencing and interpolation smoothing are performed on the input phase signal. In the self-supervised pretraining step, masked self-supervised training is performed on the phase signal using the MAE network. In the transfer learning stage, the encoder segment of the MAE network is integrated with the ViT network to enable transfer learning using labeled heart rate data. The innovative MVN offers a dual advantage—it not only reduces the cost associated with heart rate data acquisition but also adeptly addresses the issue of respiratory harmonic interference, which is an improvement over conventional signal processing methods. The experimental results show that the process in this paper improves the accuracy of heart rate estimation while reducing the requisite observation time. [ABSTRACT FROM AUTHOR]

When studying an unfamiliar system, we first look for the symmetry that the system has, so that we can make many predictions about the possible properties of the system. The symmetry in ship network security needs to maintain a stable state and maintain a constant state of ship network security. With the rapid development of network information technology, smart ships have become a new hot spot in the international shipping industry. The smart ships cybersecurity discussion is also at the top of the list in the maritime field. More and more shipping companies feel that their smart ship systems need to be upgraded and the main reason behind this is that the systems are maliciously attacked by cyber hackers. Therefore, it is extremely important to detect and protect the security of intelligent ship network systems in real time. The issue of network security has always accompanied the whole process of the development of the Internet. At the same time, with the development of Internet technology, network hacking attacks against the Internet have never stopped developing, and traditional ship network security risk detection and protection cannot achieve good results. After understanding the operation mode of intelligent ship networks, this paper deeply studied the characteristics of cloud computing technology and proposed a real-time risk detection method and protection strategy for intelligent ship network security based on cloud computing. This paper mainly used multi-sensor nodes to analyze data containing malicious attack information and implemented self-execution protection strategy generation nodes to intercept and protect from the attack, so as to achieve the purpose of maintaining the network security of intelligent ships. Through experiments, the virus intrusion detection and defense rate of the algorithm proposed in this paper was able to reach 85% to 95%, while the virus intrusion detection defense rate of the traditional intelligent ship network security protection algorithm was 55% to 65%. The detection rate of the algorithm proposed in this paper was able to reach 96.95% and the false positive rate was 2.56%. The detection rate of the traditional algorithm was only 70.76%, while the false positive rate reached 4.69%. All of the proposed algorithm's data were significantly better than that of traditional algorithms, which proved that the performance of cloud computing-based real-time risk detection and protection algorithms for intelligent ship network security was significantly better than that of traditional algorithms. [ABSTRACT FROM AUTHOR]

In order to obtain the chemical composition characteristics and source apportionment of PM2.5 in a western industrial region of Jinan, manual sampling and analysis of PM2.5 in Pingyin County was conducted during 2019. The results showed that the total concentration of 29 species of PM2.5 was 53.8 μg·m−3. The NO3− concentration (14.6 ± 14.2 μg·m−3) was the highest, followed by OC (9.3 ± 5.5 μg·m−3), SO42− (9.1 ± 6.4 μg·m−3) and NH4+ (8.1 ± 6.8 μg·m−3). Concentrations of OC, NO3− and SO42− were highest in winter and lowest in summer. The concentration of NH4+ was highest in winter and lowest in spring. The annual SOR and NOR were 0.30 ± 0.14 and 0.21 ± 0.12, respectively. SO2 emission and conversion ratio was highest in winter, leading to the highest SO42− concentration. SO2 emission in summer was low, but the conversion ratio was high. NOR in winter and autumn were close and higher than spring and summer. The high NOR in autumn caused a higher NO3− concentration compared with that in spring and summer. The average concentration of SOC during 2019 was 2.8 ± 1.9 μg·m−3, accounting for 30% of OC. The PMF results showed that coal emission accounted for 36.5% of PM2.5 concentration, followed by mobile sources (32.6%), industry emission (17.4%), dust emission (7.1%) and other emissions (6.4%). [ABSTRACT FROM AUTHOR]

(1) Background: Ovarian cancer (OC) and Parkinson's disease (PD) represent a huge public health burden. The relationship of these two diseases is suggested in the literature while not fully understood. To better understand this relationship, we conducted a bidirectional Mendelian ran-domization analysis using genetic markers as a proxy. (2) Methods: Utilizing single nucleotide polymorphisms associated with PD risk, we assessed the association between genetically predicted PD and OC risk, overall and by histotypes, using summary statistics from previously conducted genome-wide association studies of OC within the Ovarian Cancer Association Consortium. Similarly, we assessed the association between genetically predicted OC and PD risk. The inverse variance weighted method was used as the main method to estimate odds ratios (OR) and 95% confidence intervals (CI) for the associations of interest. (3) Results: There was no significant association between genetically predicted PD and OC risk: OR = 0.95 (95% CI: 0.88–1.03), or between genetically predicted OC and PD risk: OR = 0.80 (95% CI: 0.61–1.06). On the other hand, when examined by histotypes, a suggestive inverse association was observed between genetically predicted high grade serous OC and PD risk: OR = 0.91 (95% CI: 0.84–0.99). (4) Conclusions: Overall, our study did not observe a strong genetic association between PD and OC, but the observed potential association between high grade serous OC and reduced PD risk warrants further investigation. [ABSTRACT FROM AUTHOR]

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature. [ABSTRACT FROM AUTHOR]

Rapeseed (Brassica napus L.) is one of the most important oil crops in the world. The planting area and output of rapeseed are affected by the flowering time, which is a critical agronomic feature. COL9 controls growth and development in many different plant species as a member of the zinc finger transcription factor family. However, BnaCOL9 in rapeseed has not been documented. The aim of this study was to apply CRISPR/Cas9 technology to create an early-flowering germplasm resource to provide useful material for improving the early-maturing breeding of rapeseed. We identified four COL9 homologs in rapeseed that were distributed on chromosomes A05, C05, A03, and C03. We successfully created quadruple BnaCOL9 mutations in rapeseed using the CRISPR/Cas9 platform. The quadruple mutants of BnaCOL9 flowered earlier than the wild-type. On the other hand, the flowering time of the BnaCOL9 overexpression lines was delayed. An analysis of the expression patterns revealed that these genes were substantially expressed in the leaves and flowers. A subcellular localization experiment demonstrated that BnaCOL9 was in the nucleus. Furthermore, we discovered that two key flowering-related genes, BnaCO and BnaFT, were highly elevated in the BnaCOL9 mutants, but dramatically downregulated in the BnaCOL9 overexpression lines. Our findings demonstrate that BnaCOL9 is a significant flowering inhibitor in rapeseed and may be employed as a crucial gene for early-maturing breeding. [ABSTRACT FROM AUTHOR]

It is widely recognized that the iron loss produced by motors at high speeds will directly affect the angle and size of the back electromotive force, and, therefore, it cannot be ignored. In this paper, a high-performance sensorless control algorithm is proposed for high-speed permanent magnet synchronous motors (HSPMSM), taking the iron loss into account. First, the resistance representing the core loss is precalculated by finite element analysis, and then a sliding mode observer with disturbance observation is designed to estimate the rotor position. The observer possesses the advantages of suppressing the chattering phenomenon and enhancing the robustness against uncertainty. Meanwhile, the idea of the characteristic model is used to design an adaptive robust control law to improve the speed control accuracy. Subsequently, a sensorless control scheme is proposed by using the proposed observer in combination with the designed control scheme. The stability of the observer and controller is verified by the Lyapunov theory method. Finally, a simulation example is given to demonstrate the correctness and the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Traffic signs detection and recognition is an essential and challenging task for driverless cars. However, the detection of traffic signs in most scenarios belongs to small target detection, and most existing object detection methods show poor performance in these cases, which increases the difficulty of detection. To further improve the accuracy of small object detection for traffic signs, this paper proposed an optimization strategy based on the YOLOv4 network. Firstly, an improved triplet attention mechanism was added to the backbone network. It was combined with optimized weights to make the network focus more on the acquisition of channel and spatial features. Secondly, a bidirectional feature pyramid network (BiFPN) was used in the neck network to enhance feature fusion, which can effectively improve the feature perception field of small objects. The improved model and some state-of-the-art (SOTA) methods were compared on the joint dataset TT100K-COCO. Experimental results show that the enhanced network can achieve 60.4% mAP(Mean Average Precision), surpassing the YOLOv4 by 8% with the same input size. With a larger input size, it can achieve a best performance capability of 66.4% mAP. This work provides a reference for research on obtaining higher accuracy for traffic sign detection in autonomous driving. [ABSTRACT FROM AUTHOR]

Temperature and precipitation are considered to be the most important indicators affecting the green-up date. Sensitivity of the green-up date to temperature and precipitation is considered to be one of the key indicators to characterize the response of terrestrial ecosystems to climate change. We selected the main grassland types for analysis, including temperate steppe, temperate meadow steppe, upland meadow, and lowland meadow. This study investigates the variation in key meteorological indicators (daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation) between 2001 and 2018. We then examined the partial correlation and sensitivity of green-up date (GUD) to Tmax, Tmin, and precipitation. Our analysis indicated that the average GUD across the whole area was DOY 113. The mean GUD trend was −3.1 days/decade and the 25% region advanced significantly. Tmax and Tmin mainly showed a decreasing trend in winter (p > 0.05). In spring, Tmax mainly showed an increasing trend (p > 0.05) and Tmin a decreasing trend (p > 0.05). Precipitation showed no significant (p > 0.05) change trend and the trend range was ±10 mm/decade. For temperate steppe, the increase in Tmin in March promotes green-up (27.3%, the proportion of significant pixels), with a sensitivity of −0.17 days/°C. In addition, precipitation in April also promotes green-up (21.7%), with a sensitivity of −0.32 days/mm. The GUDs of temperate meadow steppe (73.9%), lowland meadow (65.9%), and upland meadow (22.1%) were mainly affected by Tmin in March, with sensitivities of −0.15 days/°C, −0.13 days/°C, and −0.14 days/°C, respectively. The results of this study reveal the response of vegetation to climate warming and contribute to improving the prediction of ecological changes as temperatures increase in the future. [ABSTRACT FROM AUTHOR]

Simple Summary: The bright red color of Erythraeid mites is conspicuous. The Erythraeid larvae are usually ectoparasitic on arthropods and easily observed. Both the genera Charletonia and Leptus are distributed worldwide. Charletonia has 86 species and Leptus has more than 240 species based on larvae, respectively. To date, two species of the genus Charletonia and 11 species of the genus Leptus have been reported from China. Here, four new species, Charletonia rectangia Xu and Jin sp. nov. collected from tropical rainforests in the Guangxi Province and Yunnan Province, Leptus (Leptus) bomiensis Xu and Jin sp. nov. from the Tibet Autonomous Region, where the altitude ranges from 2673 to 3374 m, Leptus (Leptus) longisolenidionus Xu and Jin sp. nov. from jungles in the Hainan Province (Hainan Island), and Leptus (Leptus) striatus Xu and Jin sp. nov. from Xishuangbanna tropical rainforests in the Yunnan Province. We believe that this study will contribute to further research on the taxonomy and phylogeny of the family. Four new species, Charletonia rectangia Xu and Jin sp. nov., Leptus (Leptus) bomiensis Xu and Jin sp. nov., Leptus (Leptus) longisolenidionus Xu and Jin sp. nov., and Leptus (Leptus) striatus Xu and Jin sp. nov. are described and illustrated based on larvae. All four new species are from biodiversity hotspots, L. (L.) bomiensissp. nov. from the Eastern Himalayas biodiversity hotspot, while the other three species from the Indo–Burma biodiversity hotspot. [ABSTRACT FROM AUTHOR]

At present, with the advance of satellite image processing technology, remote sensing images are becoming more widely used in real scenes. However, due to the limitations of current remote sensing imaging technology and the influence of the external environment, the resolution of remote sensing images often struggles to meet application requirements. In order to obtain high-resolution remote sensing images, image super-resolution methods are gradually being applied to the recovery and reconstruction of remote sensing images. The use of image super-resolution methods can overcome the current limitations of remote sensing image acquisition systems and acquisition environments, solving the problems of poor-quality remote sensing images, blurred regions of interest, and the requirement for high-efficiency image reconstruction, a research topic that is of significant relevance to image processing. In recent years, there has been tremendous progress made in image super-resolution methods, driven by the continuous development of deep learning algorithms. In this paper, we provide a comprehensive overview and analysis of deep-learning-based image super-resolution methods. Specifically, we first introduce the research background and details of image super-resolution techniques. Second, we present some important works on remote sensing image super-resolution, such as training and testing datasets, image quality and model performance evaluation methods, model design principles, related applications, etc. Finally, we point out some existing problems and future directions in the field of remote sensing image super-resolution. [ABSTRACT FROM AUTHOR]

Catalpol, an iridoid glucoside extracted from the traditional Chinese herbal medicine, Rehmannia glutinosa, is reported to exert neuroprotective, anti-inflammatory, anti-tumor and anti-apoptotic effects. The main aim of the present study was to investigate whether catalpol ameliorates experimental acute pancreatitis (AP) induced by sodium taurocholate (STC). AP was induced in rats via retrograde injection of 4% STC (0.1 mL/100 g) into the biliopancreatic duct. Rats were pre-treated with saline or catalpol (50 mg/kg) 2 h before STC injection. At 12, 24 and 48 h after injection, the severity of AP was evaluated using biochemical and morphological analyses. Pretreatment with catalpol led to a significant reduction in serum amylase and lipase activities, pancreatic histological damage, myeloperoxidase (MPO) activity, interleukin (IL)-1ß, IL-6 and TNF-a levels, and activation of nuclear factor kappa B (NF-κB). Moreover, administration of catalpol increased the viability of pancreatic acinar cells and inhibited NF-κB expression in vitro. Our results collectively support the potential of catalpol as a highly effective therapeutic agent for treatment of AP. [ABSTRACT FROM AUTHOR]

Soluble starch synthases (SSs) play important roles in the synthesis of cassava starch. However, the expression characteristics of the cassava SSs genes have not been elucidated. In this study, the MeSSIII-1 gene and its promoter, from SC8 cassava cultivars, were respectively isolated by PCR amplification. MeSSIII-1 protein was localized to the chloroplasts. qRT-PCR analysis revealed that the MeSSIII-1 gene was expressed in almost all tissues tested, and the expression in mature leaves was 18.9 times more than that in tuber roots. MeSSIII-1 expression was induced by methyljasmonate (MeJA), abscisic acid (ABA), and ethylene (ET) hormones in cassava. MeSSIII-1 expression patterns were further confirmed in proMeSSIII-1 transgenic cassava. The promoter deletion analysis showed that the −264 bp to −1 bp MeSSIII-1 promoter has basal activity. The range from −1228 bp to −987 bp and −488 bp to −264 bp significantly enhance promoter activity. The regions from −987 bp to −747 bp and −747 bp to −488 bp have repressive activity. These findings will provide an important reference for research on the potential function and transcriptional regulation mechanisms of the MeSSIII-1 gene and for further in-depth exploration of the regulatory network of its internal functional elements. [ABSTRACT FROM AUTHOR]

Laminitis is the inflammation of the lamella, and it has caused great economic loss to the dairy industry and attracted wide attention around the world. In recent years, microbiota are considered to play a significant role in various diseases processes. Therefore, our study aimed to explore the characteristics of ruminal microbiota in laminitis cows. The serum of bovines with or without laminitis was collected to detect concentrations of lipopolysaccharide (LPS), lactic acid, and histamine, and ruminal fluid was collected for 16S rDNA sequence analysis. The results showed a significant increase in LPS and lactic acid levels in the laminitis group compared to the control group cows. In addition, a higher abundance of Candidatus Saccharimonas, Saccharofermentans, Erysipelotrichaceae UCG-009 genus, Acetobacter pasteurianus, Clostridium papyrosolvens, Ruminococcaceae bacterium AE2021, Porphyromonas crevioricanis, Pseudomonas boreopolis, Pseudomonas psychrotolerans, Rothia nasimurium, and Rothia pickettii was detected in the rumen fluid of laminitis bovines. In conclusion, this article confirms that there are differences in rumen microbiota between healthy and laminitis bovines. The elevated abundance of bacteria that enrich acid-enhancing metabolites, as well as increase the concentration of lactic acid and LPS, could be harmful factors to bovines and increase the risk of laminitis. [ABSTRACT FROM AUTHOR]

Nitrogen is an important nutrient element that limits plant growth and yield formation, but excessive nitrogen has negative effects on plants and the environment. It is important to reveal the molecular mechanism of high NUE (nitrogen use efficiency) for breeding peach rootstock and variety with high NUE. In this study, two peach rootstocks, Shannong–1 (S) and Maotao (M), with different NUE were used as materials and treated with 0.1 mM KNO3 for transcriptome sequencing together with the control group. From the results of comparison between groups, we found that the two rootstocks had different responses to KNO3, and 2151 (KCL_S vs. KCL_M), 327 (KNO3_S vs. KCL_S), 2200 (KNO3_S vs. KNO3_M) and 146 (KNO3_M vs. KCL_M) differentially expressed genes (DEGs) were identified, respectively, which included multiple transcription factor families. These DEGs were enriched in many biological processes and signal transduction pathways, including nitrogen metabolism and plant hormone signal transduction. The function of PpNRT2.1, which showed up-regulated expression under KNO3 treatment, was verified by heterologous expression in Arabidopsis. The plant height, SPAD (soil and plant analyzer development) of leaf and primary root length of the transgenic plants were increased compared with those of WT, indicating the roles of PpNRT2.1 in nitrogen metabolism. The study uncovered for the first time the different molecular regulatory pathways involved in nitrogen metabolism between two peach rootstocks and provided gene reserve for studying the molecular mechanism of nitrogen metabolism and theoretical basis for screening peach rootstock or variety with high NUE. [ABSTRACT FROM AUTHOR]

Simple Summary: Erythraeid mite members are large, larvae usually parasitize other arthropods, whereas the nymphs and adults are free-living predators of a small insect. Free-living adults/nymphs and parasitic larvae vary greatly in morphology, and classification is usually treated independently. To date, more than 850 species of erythraeid mites have been recorded. Among them, more than 580 species were described only as larvae. Eatoniana Cambridge, 1898 is a small genus within Erythraeidae comprising, 10 valid species worldwide, three species of which were only reported based on larvae. Erythraeus Latreille, 1806 includes 123 species distributed worldwide, with 69 species reported based on larvae alone. Here, two new species, Eatoniana nanlingensis Xu and Jin sp. nov. from Guangdong Province and Erythraeus (Erythraeus) kunyuensis Xu and Jin sp. nov. from Shandong Province, are described based on larval stage. We believe that the study will contribute to further studies on the taxonomy and phylogeny of Erythraeidae. The species Eatoniana yangshuonicus (Haitlinger) comb. nov. is transferred from the genus Erythraeus to Eatoniana based on the basifemoral setal formula 2-2-1. Two new species, Eatoniana nanlingensis Xu and Jin sp. nov. and Erythraeus (Erythraeus) kunyuensis Xu and Jin sp. nov. are described and illustrated based on larvae. Eatoniana nanlingensis sp. nov. from the Oriental region (Guangdong Province), Er. (Er.) kunyuensis sp. nov. from the Palaearctic region (Shandong Province). An updated key to larval species of the genus Eatoniana of the world is presented. [ABSTRACT FROM AUTHOR]

The accumulation of heat and moderate precipitation are the primary factors that are used by grasslands to trigger a green-up date. The accumulated growing degree-days (AGDD) requirement over the preseason is an important indicator of the response of grassland spring phenology to climate change. This study adopted the Normalized Difference Phenology Index (NDPI), which derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), to extract annual green-up dates in the Hulun Buir grassland in China between 2001–2015. Our analysis indicated that the range (standard deviation) and trend for the green-up date were DOY (day of year) 104 to DOY 144 (10.6 days) and −2.0 days per decade. Nine point two percent of the study area had significant (p < 0.05) changes in AGDD requirements. The partial correlations between the AGDD requirements and chilling days (67.04%, pixels proportion) were negative and significant (p < 0.05). The partial correlations between the AGDD requirement and precipitation (28.87%) were positive and significant (p < 0.05). Finally, the partial correlation between the AGDD requirement and insolation (97.65%) were positive and significant (p < 0.05). The results of this study could reveal the response of vegetation to climate warming and contribute to improving the phenological mechanism model of different grassland types in future research. [ABSTRACT FROM AUTHOR]

Structural health monitoring systems provide many advantages for full-scale measurements in bridge monitoring. In this study, a strong landing typhoon event recorded at the Jintang Bridge (Zhejiang Province, China) in 2019 was selected to study the nonstationary wind and cable vibration characteristics. To study the characteristics of the recorded typhoon, the time-varying mean wind was extracted based on the adaptive method of the wavelet-matrix transform. The nonstationary characteristics of Typhoon Lekima, including the turbulence intensity, gust factor, and fluctuating wind power spectral density, were analyzed and compared with the stationary model characteristics of a typhoon, and the typical characteristics and parameters were obtained. In addition, the measured vibration response of the cables was analyzed. The vibration characteristics of the cables and the energy distribution of the wind speed wavelet packet were investigated. The vibrations at different positions were compared. A power spectrum analysis and a wavelet packet energy analysis of the cable were performed. The results of this study can be used as a basis for wind-resistant design and performance evaluation of bridges under similar operational conditions. [ABSTRACT FROM AUTHOR]

The Maozaishan Sn deposit, located south of the Dayishan ore field in the Nanling Range, is a newly explored greisen-type Sn deposit. Two muscovite samples from tin-bearing ores yielded 40Ar/39Ar plateau ages of 154.7 ± 1.1 Ma (Mean standard weighted deviation (MSWD) = 0.48) and 152.6 ± 0.7 Ma (MSWD = 0.25), respectively. Zircon U–Pb dating result of fine-grained biotite monzogranite in the Maozaishan mining area shows that these zircon grains can be subdivided into two populations, with ages of 154.2 ± 2.0 Ma (MSWD = 0.51) and 159.6 ± 1.9 Ma (MSWD = 0.09), respectively, indicating that the monzogranite is formed by a multi-stage magmatic event. It is indicated that formation of the Maozaishan Sn deposit is closely related to the Middle Jurassic granitic magmatism. Based on the trace element compositions of zircon grains, the calculated magma temperatures and oxygen fugacity (log(fO2)) values range from 638 °C to 754 °C (mean = 704 °C) and from −18.9 to −15.8 (mean = −17.1), respectively. In addition, these intrusive rocks in the Dayishan ore field belong to highly fractionated granites and are characterized by low oxygen fugacity and crust–mantle origin, which are consistent to these tin-bearing granites in the Nanling Range and in favor of the Sn mineralization. [ABSTRACT FROM AUTHOR]

Due to its flexibility and versatility, robotic belt polishing is one of the most effective processing methods to improve the surface quality of aeroengine blades. Since belt polishing of blades is a material removal process aimed at reducing surface roughness, it is difficult to achieve both minimum surface roughness and maximum material removal rates. In order to solve this problem, this paper proposes an optimization method combining grey correlation analysis (GRA), the Taguchi method, and the response surface method (RSM) for the multiobjective optimization of the process parameters of Ti–6Al–4V aeroengine blade polishing. Meanwhile, the problem of the influence of asymmetry on the polishing process parameters vis-a-vis the optimization goal was solved. Experiments of robotic belt polishing for aeroengine blades were carried out. Based on the results of the principal component analysis, the grey relational grade was established to turn multiobjective optimization into single-objective optimization. A quadratic regression model of Grey correlation grade was developed, and an optimal parameter combination was obtained by the RSM. Finally, verification experiments were performed, and the combination of optimal parameters was obtained as follows: feed rate of 232.09 mm/min, compression amount of 0.08 mm, and belt line speed of 16 m/s, which reduced surface roughness by 6.29% and increased the material removal rate by 16.11%. Comparing the results of GRA-RSM and GRA, the Grey correlation grade increased by 10.96%. In other words, the goal of simultaneously reducing the surface roughness and improving the material removal rate was achieved in robotic belt polishing for aeroengine blades. [ABSTRACT FROM AUTHOR]

Through nanoscratch experiments with a spherical diamond indenter, a contrastive study of the nanotribological properties of Ga- and N-faced gallium nitride (GaN) samples was carried out. Nanoindentation results revealed that the elastic modulus of the Ga-faced GaN sample was slightly higher than that of N-faced GaN sample. Particularly, Ga- and N-faced GaN samples exhibited rather different nanotribological properties, and the Ga-faced sample showed a stronger wear resistance. The study indicated that the critical normal load required to cause material removal of N-faced GaN sample was almost two times that of Ga-faced GaN sample. Both Ga- and N-faces exhibited a rather low frictional coefficient at the elastic and elastoplastic stages of material, e.g., ~0.06 for Ga-face and ~0.075 for N-face when scratching under the progressive normal load. Combined with transmission electron microscopy and X-ray photoelectron spectroscopy, we speculated that, except for the intrinsic atomic arrangements attributed to the non-reverse crystallographic symmetry of c-plane wurtzite GaN, the difference of nanotribological properties between Ga- and N-faces may also be related to the preferential formation of a native oxide layer and a slight lattice damage layer on the N-faced GaN surface. This study can enrich the understanding of the nanotribological properties of Ga- and N-polar-faced bulk monocrystalline GaN materials fabricated by the conventional technique. [ABSTRACT FROM AUTHOR]

Trehalose-6-phosphate synthase (TPS) is essential for plant growth and development, linking trehalose-6-phosphate (T6P) to carbon metabolism. However, little is known about the TPS gene family in peaches and their potential roles in regulating carbohydrates in peach fruit. In this study, nine TPS genes were identified in the peach genome and named according to the homologous genes in Arabidopsis. Phylogenetic analysis showed that three subfamilies were identified, including TPSI, TPSII-1, and TPSII-2, which were also consistent with gene structure analysis. Considerable cis-elements were enriched in the promoters, including plant hormone-related elements. Tissue-specific analysis showed that these TPS genes were mainly expressed in leaves, stems, and fruit, showing different expression patterns for each gene. In addition, during fruit development, the content of trehalose-6-phosphate (T6P) was positively correlated with the expression of PpTPS7a and negatively with sucrose non-fermenting-1-related kinase 1 (SnRK1) activity. Transient overexpression and silencing of PpTPS7a in peach fruit validated its function in regulating T6P content and SnRK1 activity. [ABSTRACT FROM AUTHOR]

A typical amphiphilic star polymer adamantane-[poly(lactic-co-glycolic acid)-bis(2-carboxyethyl) sulfide-poly(ethylene glycol) monomethyl ether)]4 with a specific hydrophilic/redox-sensitive/hydrophobic structure was designed and synthesized through ring opening and esterification reactions. The self-assembled nanomicelles were used as doxorubicin (DOX) delivery vehicles with suitable critical micelle concentrations (5.0 mg/L). After the drug being loaded, drug-loaded micelles showed good drug-loading efficiency (10.39%), encapsulation efficiency (58.1%), and drug release (up to 60%) under simulated biological environment conditions. In addition, the backbone structure of the biodegradable polymer was easily hydrolyzed by the action of biological enzymes. As expected, cell-based studies showed that the designed polymer micelles possessed good biocompatibility (a survival rate of 85% for NH-3T3 cells). Moreover, the drug (DOX) still maintained good anti-cancer effects after being loaded, which caused 40% of MCF-7 cells to survive. These redox-sensitive micelles showed anti-tumor therapeutic potential. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) has been proven to be an efficient indicator of vegetation photosynthesis. To investigate the relationship between SIF and Gross Primary Productivity (GPP), tower-based continuous spectral observations coordinated with eddy covariance (EC) measurements are needed. As the strong absorption effect at the O2-A absorption bands has an obvious influence on SIF retrieval based on the Fraunhofer Line Discrimination (FLD) principle, atmospheric correction is required even for tower-based SIF observations made with a sensor tens of meters above the canopy. In this study, an operational and simple solution for atmospheric correction of tower-based SIF observations at the O2-A band is proposed. The aerosol optical depth (AOD) and radiative transfer path length (RTPL) are found to be the dominant factors influencing the upward and downward transmittances at the oxygen absorption band. Look-up tables (LUTs) are established to estimate the atmosphere transmittance using AOD and RTPL based on the MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5) model simulations, and the AOD is estimated using the ratio of the downwelling irradiance at 790 nm to that at 660 nm (E790/E660). The influences of the temperature and pressure on the atmospheric transmittance are also compensated for using a corrector factor of RTPL based on an empirical equation. A series of field measurements were carried out to evaluate the performance of the atmospheric correction method for tower-based SIF observations. The difference between the SIF retrieved from tower-based and from ground-based observations decreased obviously after the atmospheric correction. The results indicate that the atmospheric correction method based on a LUT is efficient and also necessary for more accurate tower-based SIF retrieval, especially at the O2-A band. [ABSTRACT FROM AUTHOR]

The aim of this study was to optimize the adsorption performance of activated carbon (AC), derived from the shell of Penaeus vannamei prawns, on heavy metal ions. Inexpensive, non-toxic, and renewable prawn shells were subjected to carbonization and, subsequently, KOH-activation to produce nanoporous K-Ac. Carbonized prawn shells (CPS) and nanoporous KOH-activated carbon (K-Ac) from prawn shells were prepared and characterized by FTIR, XRD, BET, SEM, and TEM. The results showed that as-produced K-Ac samples were a porous material with microporous and mesoporous structures and had a high specific surface area of 3160 m2/g, average pore size of about 10 nm, and large pore volume of 2.38 m3/g. Furthermore, batches of K-Ac samples were employed for testing the adsorption behavior of Cd2+ in solution. The effects of pH value, initial concentration, and adsorption time on Cd2+ were systematically investigated. Kinetics and isotherm model analysis of the adsorption of Cd2+ on K-Ac showed that experimental data were not only consistent with the Langmuir adsorption isotherm, but also well-described by the quasi-first-order model. Finally, the adsorption behaviors of as-prepared K-Ac were also tested in a ternary mixture of heavy metal ions Cu2+, Cr6+, and Cd2+, and the total adsorption amount of 560 mg/g was obtained. [ABSTRACT FROM AUTHOR]

Microcystin-LR (MC-LR) is the most toxic and frequently detected monocyclic heptapeptide hepatotoxin produced by cyanobacteria, which poses a great threat to the natural ecosystem and public health. It is very important to seek environment-friendly and cost-efficient methods to remove MC-LR in water. In this study, the MC-degrading capacities of a novel indigenous bacterial community designated as YFMCD4 and the influence of environmental factors including various temperatures, MC concentrations and pH on the MC-degrading activities were investigated utilizing high-performance liquid chromatography (HPLC). In addition, the MC-degrading mechanism of YFMCD4 was also studied using HPLC coupled with a mass spectrometry equipped with electrospray ionization interface (HPLC-ESI-MS). The data showed MC-LR was completely removed at the maximum rate of 0.5 µg/(mL·h) under the optimal condition by YFMCD4. Two pure bacterial strains Alcaligenes faecalis and Stenotrophomonas acidaminiohila were isolated from YFMCD4 degraded MC-LR at a slower rate. The MC-degrading rates of YFMCD4 were significantly affected by different temperatures, pH and MC-LR concentrations. Two intermediates of a tetrapeptide and Adda appeared in the degradation process. These results illustrate that the novel YFMCD4 is one of the highest effective MC-degrading bacterial community, which can completely remove MC-LR and possesses a significant potential to treat water bodies contaminated by MC-LR. [ABSTRACT FROM AUTHOR]

Blockchain is widely used in the manufacturing industry. This paper establishes a dual-channel supply chain composed of a manufacturer and an e-retailer. A monopoly manufacturer conducts indirect online selling through retailers as well as direct offline selling. The manufacturer chooses to adopt a self-built blockchain traceability system (SBT) or a third-party blockchain traceability system (TBT). Game analysis is developed to depict the pricing decision for the manufacturer and e-retailer. The optimal pricing decisions of the supply chain between manufacturer and e-retailer for different blockchain traceability strategies are obtained. We explore the influence of consumers' traceability awareness on the decisions of dual-channel supply chain members when adopting different blockchain traceability strategies. The main results show that when the fee paid to the blockchain service provider is low, the manufacturer will prefer to adopt TBT. Moreover, we prove that consumers' traceability awareness, the cost of adopting TBT, the blockchain traceability technology level, and the research and development cost factor of blockchain technology could affect the decisions of supply chain members. Finally, some management suggestions are provided. [ABSTRACT FROM AUTHOR]

Using an atomic force microscope (AFM), the wear of monocrystalline silicon (covered by a native oxide layer) at high humidity was investigated. The experimental results indicated that tribochemistry played an important role in the wear of the silicon at different relative humidity levels (RH = 60%, 90%). Since the tribochemical reactions were facilitated at 60% RH, the wear of silicon was serious and the friction force was around 1.58 μN under the given conditions. However, the tribochemical reactions were restrained when the wear pair was conducted at high humidity. As a result, the wear of silicon was very slight and the friction force decreased to 0.85 μN at 90% RH. The slight wear of silicon at high humidity was characterized by etching tests. It was demonstrated that the silicon sample surface was partly damaged and the native oxide layer on silicon sample surface had not been totally removed during the wear process. These results may help us optimize the tribological design of dynamic microelectromechanical systems working in humid conditions. [ABSTRACT FROM AUTHOR]

Mites, the second largest arthropod group, exhibit rich phenotypic diversity in the development of appendages (legs). For example, the fourth pair of legs (L4) does not form until the second postembryonic developmental stage, namely the protonymph stage. These leg developmental diversities drive body plan diversity in mites. However, little is known about the mechanisms of leg development in mites. Hox genes, homeotic genes, can regulate the development of appendages in arthropods. Three Hox genes, Sex combs reduced (Scr), Fushi tarazu (Ftz) and Antennapedia (Antp), have previously been shown to be expressed in the leg segments of mites. Here, the quantitative real-time reverse transcription PCR shows that three Hox genes are significantly increased in the first molt stage. RNA interference results in a set of abnormalities, including L3 curl and L4 loss. These results suggest that these Hox genes are required for normal leg development. Furthermore, the loss of single Hox genes results in downregulating the expression of the appendage marker Distal-less (Dll), suggesting that the three Hox genes can work together with Dll to maintain leg development in Tetranychus urticae. This study will be essential to understanding the diversity of leg development in mites and changes in Hox gene function. [ABSTRACT FROM AUTHOR]

Legal judgments are generally very long, and relevant information is often scattered throughout the text. To complete a legal judgment summarization, capturing important, relevant information comprehensively from a lengthy text is crucial. The existing abstractive-summarization models based on pre-trained language have restrictions on the length of an input text. Another concern is that the generated summaries have not been well integrated with the legal judgment's technical terms and specific topics. In this paper, we used raw legal judgments as information of different granularities and proposed a two-stage text-summarization model to handle different granularities of information. Specifically, we treated the legal judgments as a sequence of sentences and selected key sentence sets from the full texts as an input corpus for summary generation. In addition, we extracted keywords related to technical terms and specific topics in the legal texts and introduced them into the summary-generation model as an attention mechanism. The experimental results on the CAIL2020 and the LCRD datasets showed that our model achieved an overall 0.19–0.41 improvement in its ROUGE score, as compared to the baseline models. Further analysis also showed that our method could comprehensively capture essential and relevant information from lengthy legal texts and generate better legal judgment summaries. [ABSTRACT FROM AUTHOR]

Blockchain technology allows fresh agricultural enterprises to share records stored on the chain, and the technology can benefit information management systems, such as decentralization and transparency. This study uses game theory to examine a blockchain introduction strategy for fresh agricultural enterprises in a competitive environment, considering consumer traceability preferences. We establish a pricing decision model in traditional and blockchain traceability modes and identify optimal solutions. Additionally, we analyze the impact of the blockchain introduction strategy, consumer preferences, and blockchain influence factor on optimal pricing decisions. The results indicate that the introduction of blockchain could improve the profits of enterprises under certain conditions. Moreover, consumer traceability preferences and the blockchain influence factor could significantly affect the blockchain introduction strategy. We also discover that when the blockchain influence factor meets a certain range, introducing blockchain technique in the traceability system could shift demand from traditional enterprises to blockchain enterprises. The total market demand for blockchain enterprises under the blockchain traceability mode will increase, whereas that of traditional enterprises under the blockchain traceability mode will decrease. Both consumer traceability preferences and the blockchain influence factor could significantly affect optimal pricing. Finally, some management suggestions are provided for the traceability of fresh agricultural enterprises based on the research conclusions. [ABSTRACT FROM AUTHOR]

Simple Summary: Ophraella communa Lesage is a specific biological control agent of the invasive weed Ambrosia artemisiifolia L. Understanding the molecular mechanism by which O. communa recognizes A. artemisiifolia will help improve its bio-control effect. Odorant-binding proteins (OBPs) play a vital role in insect olfactory perception. In this study, the sequence and expression characteristics of OcomOBP7 were analyzed. We obtained the pure protein of OcomOBP7 by prokaryotic expression and purification, and its binding characteristics were analyzed using a fluorescence competitive binding assay. Finally, we verified the function of OcomOBP7 in vivo using RNAi combined with an electroantennography (EAG) assay. The results showed that the binding ability of OcomOBP7 was broad-spectrum and was involved in the host plant localization of O. communa. The olfactory system plays a key role in various insect behaviors, and odorant-binding proteins participate in the first step of the olfactory process. Ophraella communa Lesage is an oligophagous phytophagous insect that is a specific biological control agent for Ambrosia artemisiifolia L. The leaf beetle must identify and locate A. artemisiifolia through olfaction; however, its odorant-binding protein (OBP) function has not yet been reported. In this study, OcomOBP7 was cloned, and its tissue expression profile and binding ability were analyzed using RT-qPCR and fluorescence binding assays, respectively. Sequence analysis demonstrated that OcomOBP7 belongs to the classical OBP family. The RT-qPCR results showed that OcomOBP7 was specifically expressed in the antennae, indicating that OcomOBP7 may be involved in chemical communication. The fluorescence binding assay showed that OcomOBP7 has an extensive binding ability to alkenes. The electroantennography experiments showed that O. communa antennal response to α-pinene and ocimene decreased significantly after interference because the two odors specifically bound to OcomOBP7. In summary, α-pinene and ocimene are odorant ligands corresponding to OcomOBP7, indicating that OcomOBP7 is involved in the chemical recognition of A. artemisiifolia. Our study lays a theoretical foundation for research into O. communa attractants, which is helpful for the better biological control of A. artemisiifolia by O. communa. [ABSTRACT FROM AUTHOR]

Grassland aboveground biomass (AGB) is an important indicator for studying the change in grassland ecological quality and carbon cycle. The rapid development of high-resolution remote sensing and unmanned aerial vehicles (UAV) provides a new opportunity for accurate estimation of grassland AGB on the plot scale. In this study, the mountain grassland was taken as the research object. Using UAV Light Detection and Ranging (LiDAR) data and multispectral satellite images, the influence of topographic correction methods on AGB estimation was compared and a series of LiDAR metrics and vegetation indices were extracted. On this basis, a comprehensive indicator, the vegetation index-height-intensity model (VHI), was proposed to estimate AGB quickly. The results show that: (1) Among the four topographic correction methods, the Teillet regression has the best effect, and can effectively improve the accuracy of AGB estimation in mountain grassland. The correlation between corrected ratio vegetation index and AGB was the highest (correlation coefficient: 0.682). (2) Among the height and intensity metrics, median height and max intensity yielded the higher accuracy in estimating AGB, with Root Mean Square Error (RMSE) of 322 g/m2 and 333 g/m2, respectively. (3) The VHI integrated spectrum and LiDAR information, and its accuracy for AGB estimation for mountain grassland, was obviously better than other indicators, with an RMSE of 272 g/m2. We also found that the accuracy of VHI in univariate models was comparable to that of complex multivariate models such as stepwise regression, support vector machine, and random forest. This study provides a new approach for estimating grassland AGB with multi-source data. As a simple and effective indicator, VHI has shown strong application potential for grassland AGB estimating in mountainous areas, and can be further applied to grassland carbon cycle research and fine management. [ABSTRACT FROM AUTHOR]

With their high specific stiffness, corrosion resistance and other characteristics, especially their outstanding performance in product weight loss, fiber-reinforced resin matrix composites are widely used in the aviation, shipbuilding and automotive fields. The difficulties in minimizing defects are an important factor in the high cost of composite material component fabrication. Fiber steering is one of the typical means of producing composite parts with increased strength or stiffness. However, fiber waviness is an important defect induced by fiber steering during the fiber placement process. Meanwhile, the laying speeds of the inner and outer tows along the path width direction are different during the fiber steering process, resulting in different interlaminar bond strengths. Therefore, the fiber waviness and uneven interlaminar bonding strength during fiber steering not only affect the dimensions of a composite product, but also influence the mechanical properties of the part. This study aims to reduce fiber waviness and improve interlaminar bonding uniformity along the path width direction using a multi-piece compaction roller. By analyzing the mechanism of the generation of fiber waviness, the interlaminar bonding strength for each tow during fiber steering is investigated. Through analyzing and optimizing the compaction force, laying temperature and laying velocity during fiber steering experiments, the optimization approach is verified. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cells (PEMFCs) have been recognized as a promising power generation source for a wide range of automotive, stationary, and portable electronic applications. However, the durability of PEMFCs remains as one of the key barriers to their wide commercialization. The membrane electrode assembly (MEA) as a central part of a PEMFC, which consists of a proton exchange membrane with a catalyst layer (CL) and gas diffusion layer (GDL) on each side, is subject to failure and degradation in long-running and cycling load conditions. The real-time monitoring of the degradation evolution process through experimental techniques is challenging. Therefore, different numerical modeling approaches were proposed in the literature to assist the understanding of the degradation mechanisms in PEMFCs. To provide modeling progress in the addressed field, this paper briefly discusses the different degradation mechanisms occurring in the MEA. In particular, we present a detailed review of MEA degradation modeling research work, with special attention paid to the physical-based models (mechanistic models). Following the most recent relevant literature, the results showed that the combination of microstructure component models with macro-scale comprehensive PEMFC models provides a better understanding of degradation mechanisms when compared to single-scale degradation models. In this sense, it is concluded that in order to develop an accurate and efficient predictive degradation model, the different relevant scales ranging from nano- to macro-sized scales should be considered, and coupling techniques for multiscale modeling have to be advanced. Finally, the paper summarizes the degradation models for different MEA components. It is highlighted that the GDL chemical degradation models that describe damage accumulation are relatively limited. The paper provides a useful reference for the recent developments in the MEA degradation modeling of PEMFCs. [ABSTRACT FROM AUTHOR]

Aspongopus chinensis Dallas is used as a traditional Chinese medicine as well as an edible insect. Although its anti-tumor effects have been observed, the anti-tumor active component(s) in the hemolymph of A. chinensis remains unknown. In this study, a combination usage of ultrafiltration, gel filtration chromatography, FPLC and RP-HPLC to separate and purify active peptides was performed based on the proliferation of the human gastric cancer SGC-7901 cell line treated with candidates. One peptide (MW = 2853.3 Da) was isolated from the hemolymph of A. chinensis. A total of 24 amino acid residues were continuously determined for the active peptide: N′-ECGYCAEKGIRCDDIHCCTGLKKK-C′. In conclusion, a peptide that can inhibit the proliferation of gastric cancer SGC-7901 cells in the hemolymph of A. chinensis was purified in this study, which is homologous to members of the spider toxin protein family. These results should facilitate further works for this peptide, such as the cloning of genes, expression in vitro by prokaryotic or eukaryotic systems, more specific tests of anti-tumor activity, and so on. [ABSTRACT FROM AUTHOR]

Quercetin and kaempferol are flavonoids widely present in fruits, vegetables, and medicinal plants. They have attracted much attention due to their antioxidant, anti-inflammatory, anticancer, antibacterial, and neuroprotective properties. As the guarantee cells in direct contact with germ cells, Sertoli cells exert the role of support, nutrition, and protection in spermatogenesis. In the current study, network pharmacology was used to explore the targets and signaling pathways of quercetin and kaempferol in treating spermatogenic disorders. In vitro experiments were integrated to verify the results of quercetin and kaempferol against heat stress-induced Sertoli cell injury. The online platform was used to analyze the GO biological pathway and KEGG pathway. The results of the network pharmacology showed that quercetin and kaempferol intervention in spermatogenesis disorders were mostly targeting the oxidative response to oxidative stress, the ROS metabolic process and the NFκB pathway. The results of the cell experiment showed that Quercetin and kaempferol can prevent the decline of cell viability induced by heat stress, reduce the expression levels of HSP70 and ROS in Sertoli cells, reduce p-NF-κB-p65 and p-IκB levels, up-regulate the expression of occludin, vimentin and F-actin in Sertoli cells, and protect cell structure. Our research is the first to demonstrate that quercetin and kaempferol may exert effects in resisting the injury of cell viability and structure under heat stress. [ABSTRACT FROM AUTHOR]

Cassava starch is a widely used raw material for industrial production. South Chinese cassava cultivar 8 (Manihot esculenta Crantz cv. SC8) is one of the main locally planted cultivars. In this study, an efficient transformation system for cassava SC8 mediated with Agrobacterium strain LBA4404 was presented for the first time. Cassava friable embryogenic calli (FECs) were transformed through the binary vector pCAMBIA1304 harboring GUS- and GFP-fused genes driven by the CaMV35S promoter. The transformation efficiency was increased in the conditions of Agrobacterium strain cell infection density (OD600 = 0.65), 250 µM acetosyringone induction, and agro-cultivation with wet FECs for 3 days in dark. Based on the optimized transformation protocol, approximately 120–140 independent transgenic lines per mL settled cell volume (SCV) of FECs were created by gene transformation in approximately 5 months, and 45.83% homozygous mono-allelic mutations of the MePDS gene with a YAO promoter-driven CRISPR/Cas9 system were generated. This study will open a more functional avenue for the genetic improvement of cassava SC8. [ABSTRACT FROM AUTHOR]

At present, the situation of air pollution is still serious, and research on air filtration is still crucial. For the nanofiber air filtration membrane, the diameter, porosity, tensile strength, and hydrophilicity of the nanofiber will affect the filtration performance and stability. In this paper, based on the far-field electrospinning process and the performance effect mechanism of the stacked structure fiber membrane, nanofiber membrane was prepared by selecting the environmental protection, degradable and pollution-free natural polysaccharide biopolymer pullulan, and polyvinylidene fluoride polymer with strong hydrophobicity and high impact strength. By combining two kinds of fiber membranes with different fiber diameter and porosity, a three-layer composite nanofiber membrane with better hydrophobicity, higher tensile strength, smaller fiber diameter, and better filtration performance was prepared. Performance characterization showed that this three-layer composite nanofiber membrane had excellent air permeability and filtration efficiency, and the filtration efficiency of particles above PM 2.5 reached 99.9%. This study also provides important reference values for the preparation of high-efficiency composite nanofiber filtration membrane. [ABSTRACT FROM AUTHOR]

Natural gas plays an important role in the transition from fossil fuels to new energy sources. With the expansion of pipeline networks, there are also problems with the safety of pipeline network operations in the process of transportation. Among them, third-party damage is a key factor affecting the safety of pipelines. In this paper, the risk factors of third-party damage are analyzed, and an evaluation model of natural gas pipeline damage is established using the GeNIe Modeler. Through Bayesian network reverse reasoning and a maximum cause chain analysis from the four aspects of personnel, environment, management, and equipment, it was found that the top five factors that have significant influence on third-party damage, are safety investment, the completeness of equipment, safety inspection frequency, the management of residents along the pipeline, and safety performance, with the posteriori probability in the model of 97.3%, 95.4%, 95.2%, 95.1%, 95.1%, respectively. Consequently, it is necessary for pipeline operation companies to secure investment on safety, to make sure that the safety equipment (system) works and is in a good condition, to maintain the safety inspection frequency in an organization, to build a management system for residents along the pipeline, and to conduct routine safety performance assessments accordingly. [ABSTRACT FROM AUTHOR]

X-ray diffraction (XRD) analysis showed that metal oxide peaks appear at 2θ = 47.7°, 54.5°, and 56.3°, corresponding to Yb2O3 (440), Co2O3 (422), and Co2O3 (511). It was found that oxide formation plays an important role in magnetic, electrical, and surface energy. For magnetic and electrical measurements, the highest alternating current magnetic susceptibility (χac) and the lowest resistivity (×10−2 Ω·cm) were 0.213 and 0.42, respectively, and at 50 nm, it annealed at 300 °C due to weak oxide formation. For mechanical measurement, the highest value of hardness was 15.93 GPa at 200 °C in a 50 nm thick film. When the thickness increased from 10 to 50 nm, the hardness and Young's modulus of the Co60Fe20Yb20 film also showed a saturation trend. After annealing at 300 °C, Co60Fe20Yb20 films of 40 nm thickness showed the highest surface energy. Higher surface energy indicated stronger adhesion, allowing for the formation of multilayer thin films. The optimal condition was found to be 50 nm with annealing at 300 °C due to high χac, strong adhesion, high nano-mechanical properties, and low resistivity. [ABSTRACT FROM AUTHOR]

Island-type petrochemical parks have gradually become the 'trend' in establishing new parks because of the security advantages brought by their unique geographical locations. However, due to the frequent occurrence of natural disasters and difficulties in rescue in island-type parks, an early warning model is urgently needed to provide a basis for risk management. Previous research on early warning models of island-type parks seldom considered the particularity. In this study, the early warning indicator system is used as the input parameter to construct the early warning model of an island-type petrochemical park based on the back propagation (BP) neural network, and an actual island-type petrochemical park was used as a case to illustrate the model. Firstly, the safety influencing factors were screened by designing questionnaires and then an early warning indicator system was established. Secondly, particle swarm optimization (PSO) was introduced into the improved BP neural network to optimize the initial weights and thresholds of the neural network. A total of 30 groups of petrochemical park data were taken as samples—26 groups as training samples and 4 groups as test samples. Moreover, the safety status of the petrochemical park was set as the output parameter of the neural network. The comparative analysis shows that the optimized neural network is far superior to the unoptimized neural network in evaluation indicators. Finally, the Zhejiang Petrochemical Co., Ltd., park was used as a case to verify the accuracy of the proposed early warning model. Ultimately, the final output result was 0.8324, which indicates that the safety status of the case park was "safer". The results show that the BP neural network introduced with PSO can effectively realize early warning, which is an effective model to realize the safety early warning of island-type petrochemical parks. [ABSTRACT FROM AUTHOR]

Based on the generalized gradient approximation of density functional theory, the geometric structure and electronic properties of the intrinsic Ti3C2 and Cu-, Pt-, Co-, Si-, F-, Cl- or Br-doped Ti3C2 are optimized, and the adsorption process of HCHO on the surface of the intrinsic Ti3C2 and doped Ti3C2 is calculated. The effects of adsorption energy, stability, DOS and doping on bond length were discussed. The results show that the adsorption energy of the intrinsic Ti3C2 crystal plane at the top site is the strongest, at −7.58 eV. The optimal adsorption sites of HCHO on various doping systems are Cu-Top, Pt-Top, Co-Top, Si-Hollow, Cl-Hollow, F-Bridge and Br-Hollow, respectively. Among the doped elements, anion (F, Cl, Br) doping at each adsorption site generally reduces the formaldehyde adsorption activity of the substrate; cationic doping (Cu, Pt, Co, Si) enhances the adsorption activity of the substrate for formaldehyde at most of the adsorption sites, indicating that the modification effect of anions on Ti3C2 is not as good as that of cations. The adsorption capacity of Si-doped Ti3C2 for formaldehyde was significantly improved. Compared with the intrinsic Ti3C2 crystal plane at the same adsorption site, the adsorption activity of HCHO was improved, and the highest adsorption energy was −8.09 eV. [ABSTRACT FROM AUTHOR]

Blast-related mild traumatic brain injury (bmTBI) often leads to long-term sequalae, but diagnostic approaches are lacking due to insufficient knowledge about the predominant pathophysiology. This study aimed to build a diagnostic model for future verification by applying machine-learning based support vector machine (SVM) modeling to diffusion tensor imaging (DTI) datasets to elucidate white-matter features that distinguish bmTBI from healthy controls (HC). Twenty subacute/chronic bmTBI and 19 HC combat-deployed personnel underwent DTI. Clinically relevant features for modeling were selected using tract-based analyses that identified group differences throughout white-matter tracts in five DTI metrics to elucidate the pathogenesis of injury. These features were then analyzed using SVM modeling with cross validation. Tract-based analyses revealed abnormally decreased radial diffusivity (RD), increased fractional anisotropy (FA) and axial/radial diffusivity ratio (AD/RD) in the bmTBI group, mostly in anterior tracts (29 features). SVM models showed that FA of the anterior/superior corona radiata and AD/RD of the corpus callosum and anterior limbs of the internal capsule (5 features) best distinguished bmTBI from HCs with 89% accuracy. This is the first application of SVM to identify prominent features of bmTBI solely based on DTI metrics in well-defined tracts, which if successfully validated could promote targeted treatment interventions. [ABSTRACT FROM AUTHOR]

Our work proposes a comparison between Spark Plasma Sintering of LiFePO4 carried out using an Alternating Current (AC) and Direct Current (DC). It quantifies the Li-ion migration using DC, and it validates such hypothesis using impedance spectroscopy, X-ray photoelectron spectroscopy and inductively coupled plasma optical emission spectroscopy. The use of an AC field seems effective to inhibit undesired Li-ion migration and achieve high ionic conductivity as high as 4.5 × 10−3 S/cm, which exceeds by one order of magnitude samples processed under a DC field. These results anticipate the possibility of fabricating a high-performance all-solid-state Li-ion battery by preventing undesired Li loss during SPS processing. [ABSTRACT FROM AUTHOR]

Data missing is a common problem in wireless sensor networks. Currently, to ensure the performance of data processing, making imputation for the missing data is the most common method before getting into sensor data analysis. In this paper, the temporal and spatial nearest neighbor values-based missing data imputation (TSNN), a new imputation based on the temporal and spatial nearest neighbor values has been presented. First, four nearest neighbor values have been defined from the perspective of space and time dimensions as well as the geometrical and data distances, which are the bases of the algorithm that help to exploit the correlations among sensor data on the nodes with the regression tool. Next, the algorithm has been elaborated as well as two parameters, the best number of neighbors and spatial–temporal coefficient. Finally, the algorithm has been tested on an indoor and an outdoor wireless sensor network, and the result shows that TSNN is able to improve the accuracy of imputation and increase the number of cases that can be imputed effectively. [ABSTRACT FROM AUTHOR]

Superheated steam temperature (SST) is a significant index for a coal-fired power plant. Its control is becoming more and more challenging for the reason that the control requirements are stricter and the load command changes extensively and frequently. To deal with the aforementioned challenges, previously the cascade control strategy was usually applied to the control of SST. However, its structure and tuning procedure are complex. To solve this problem, this paper proposes a single-loop control strategy for SST based on a hybrid active disturbance rejection control (ADRC). The stability and ability to reject the secondary disturbance are analyzed theoretically in order to perfect the theory of the hybrid ADRC. Then a tuning procedure is summarized for the hybrid ADRC by analyzing the influences of all parameters on control performance. Using the proposed tuning method, a simulation is carried out illustrating that the hybrid ADRC is able to improve the dynamic performance of SST with good robustness. Eventually, the hybrid ADRC is applied to the SST system of a power plant simulator. Experimental results indicate that the single-loop control strategy based on the hybrid ADRC has better control performance and simpler structure than cascade control strategies. The successful application of the proposed hybrid ADRC shows its promising prospect of field tests in future power industry with the increasing demand on integrating more renewables into the grid. [ABSTRACT FROM AUTHOR]

In the demonstration phase of a missile scheme, to obtain the optimum proposal, designers need to modify the parameters of the overall structure frequently and significantly, and perform the structural analysis repeatedly. In order to reduce the manual workload and improve the efficiency of research and development, a general integrated method of missile structure modeling, analysis and optimization was proposed. First, CST (Class and Shape transformation functions) parametric method was used to describe the general structure of the missile. The corresponding software geometric modeling and FEM (Finite Element Method) analyzing of the missile were developed in C/C++ language on the basis of the CST parametric method and UG (Unigraphics) secondary development technology. Subsequently, a novel surrogate model-based optimation strategy was proposed to obtain a relatively light mass missile structure under existing shape size. Eventually, different missile models were used to verify the validity of the method. After executing the structure modeling, analysis and optimization modules, satisfactory results can be obtained that demonstrated the stability and adaptability of the proposed method. The method presented saves plenty of time comparing to the traditional manual modeling and analysis method, which provides a valuable technique to improve the efficiency of research and development. [ABSTRACT FROM AUTHOR]