Search

Jet noise is a common problem in minimum quantity lubrication (MQL) technology. This should be given great attention because of its serious impacts on the physical and mental health of the operators. In this study, a micro-grooved nozzle is proposed based on the noise reduction concept of biological micro-grooves. The flow field and acoustic characteristics of an original nozzle and a micro-grooved nozzle were investigated numerically to help better understand the noise reduction mechanism. The reasons for noise generation and the effects of the length (L), width (W) and depth (δ) of the micro-grooves on noise reduction were analyzed. It was found that jet noise is generated by the large-scale vortex ring structure and the pressure fluctuations caused by its motion. The overall sound pressure level (OASPL) decreased with the increases in W and δ, and increased with the increase in L. Among of them, δ has the greatest effect on noise reduction. The maximum noise reduction achieved was 6.66 dB, as verified by the OASPL test. Finally, the noise reduction mechanism was discussed in terms of the flow field, vorticity and the frequency characteristics. Micro-grooves can enhance the mixing of airflow inside the nozzle and accelerate the process of large-scale vortices breaking into smaller-scale vortices. It also reduces the sound pressure level (SPL) of middle frequencies, as well as the SPL of high frequencies on specific angles.

Internet of Things (IoT) technology has permeated into all aspects of today’s society and is playing an increasingly important role. Identity authentication is crucial for IoT devices to access the network, because the open wireless transmission environment of the IoT may suffer from various forms of network attacks. The asymmetry in the comprehensive capabilities of gateways and terminals in the IoT poses significant challenges to reliability and security. Traditional encryption-based identity authentication methods are difficult to apply to IoT terminals with limited capabilities due to high algorithm complexity and low computational efficiency. This paper explores physical layer identity identification based on channel state information (CSI) and proposes an intelligent identification method based on deep reinforcement learning (DRL). Specifically, by analyzing and extracting the features of the real received CSI information and a setting low-complexity state, as well as action and reward parameters for the deep neural network of deep reinforcement learning oriented to the scenario, we obtained an authentication method that can efficiently identify identities. The validation of the proposed method using collected CSI data demonstrates that it has good convergence properties. Compared with several existing machine-learning-based identity recognition methods, the proposed method has higher recognition accuracy.

Influenced by the topography, the spatial variation of soil thickness on karst slopes is very large, and accordingly the spatial variation of soil moisture is also large. Therefore, analyzing the spatial heterogeneity of soil moisture on hillslopes is important for maintaining ecosystem stability. Combining geostatistical methods and GIS technology, the spatial variability and distribution pattern of soil moisture and the influencing factors of spatial variation and surface soil moisture (0–7 cm) on a typical karst shrub–grass hillslope were analyzed. The results showed that the mean soil moisture and coefficient of variation (CV) ranged between 25.7–42.6% and 10.3–20.9%, respectively, showing a moderate variation. The soil moisture presented a moderate or strong spatial autocorrelation in the sampling scale. The occurrence of rainfall events can exert a great influence on reducing the spatial heterogeneity of soil moisture. The spatial distribution pattern of soil moisture showed roughly plaque or stripe distribution. When soil moisture was much lower, the patch space fragmentation of soil moisture was higher. The soil moisture was higher in the low and middle parts of the plot. We can conclude that factors such as topography, vegetation, and weather conditions will exert a significant effect on soil moisture spatial variability. Areas with lower slope and higher vegetation coverage were more conducive to the retention of soil moisture.

Mesoscale sea surface temperature (SST) variability triggers mesoscale air–sea interactions and is linked to ocean subsurface mesoscale dynamics. The National Oceanic and Atmospheric Administration (NOAA) daily Optimum Interpolation SST (OISST) products, based on various satellite and in situ SST data, are widely utilized in the investigation of multi-scale SST variabilities and reconstruction of subsurface and deep-ocean fields. The quality of OISST datasets is subjected to temporal inhomogeneity due to alterations in the merged data. Yet, whether this issue can significantly affect mesoscale SST variability is unknown. The analysis of this study detects an abrupt enhancement of mesoscale SST variability after 2007 in the OISST-AVHRR-only version 2 and version 2.1 datasets (hereafter OI.v2-AVHRR-only and OI.v2.1-AVHRR-only). The contrast is most stark in the subtropical western boundary current (WBC) regions, where the average mesoscale SST variance during 2007–2018 is twofold larger than that during 1993–2006. Further comparisons with other satellite SST datasets (TMI, AMSR-E, and WindSAT) suggest that the OISST-AVHRR-only datasets have severely underestimated mesoscale SST variability before 2007. An evaluation of related documents of the OISST data indicates that this bias is mainly caused by the change of satellite AVHRR instrument in 2007. There are no corresponding changes detected in the associated fields, such as the number and activity of mesoscale eddies or the background SST gradient in these regions, confirming that the underestimation of mesoscale SST variability before 2007 is an artifact. Another OISST product, OI.v2-AVHRR-AMSR, shows a similar abrupt enhancement of mesoscale SST variability in June 2002, when the AMSR-E instrument was incorporated. This issue leaves potential influences on scientific research that utilize the OISST datasets. The composite SST anomalies of mesoscale eddies based on the OI.v2-AVHRR-only data are underestimated by up to 37% before 2007 in the subtropical WBC regions. The underestimation of mesoscale variability also affects the total (full-scale) SST variability, particularly in winter. Other SST data products based on the OISST datasets were also influenced; we identify suspicious changes in J-OFURO3 and CFSR datasets; the reconstructed three-dimensional ocean products using OISST data as input may also be inevitably affected. This study reminds caution in the usage of the OISST and relevant data products in the investigation of mesoscale processes.

This paper considers the problem of stabilizing switched time-delay linear systems through a state-dependent switching strategy. In contrast to the existing works, we adopt a less restrictive assumption of the system, and show that this assumption is sufficient to guarantee asymptotic stability of the considered system under the min-projection switching strategy. Our results also imply that the min-projection switching strategy, originally designed for delay-free switched systems, is robust with respect to small state delays. An optimization problem is formulated to estimate the upper bound of the tolerable time delay. Numerical examples are presented to show that our method is applicable to a larger class of switched systems and leads to a greater delay bound.

This paper studied the impact of moisture on the correlated characteristics of the condenser bushings oil-paper insulation system. The oil-impregnated paper samples underwent accelerated thermal aging at 130 °C after preparation at different initial moisture contents (1%, 3%, 5% and 7%). All the samples were extracted periodically for the measurement of the moisture content, the degree of polymerization (DP) and frequency domain dielectric spectroscopy (FDS). Next, the measurement results of samples were compared to the related research results of transformer oil-paper insulation, offering a theoretical basis of the parameter analysis. The obtained results show that the moisture fluctuation amplitude can reflect the different initial moisture contents of insulating paper and the mass ratio of oil and paper has little impact on the moisture content fluctuation pattern in oil-paper but has a great impact on moisture fluctuation amplitude; reduction of DP presents an accelerating trend with the increase of initial moisture content, and the aging rate of test samples is higher under low moisture content but lower under high moisture content compared to the insulation paper in transformers. Two obvious “deceleration zones” appeared in the dielectric spectrum with the decrease of frequency, and not only does the integral value of dielectric dissipation factor (tan δ) reflect the aging degree, but it reflects the moisture content in solid insulation. These types of research in this paper can be applied to evaluate the condition of humidified insulation and the aging state of solid insulation for condenser bushings.

Residual current protection can detect and isolate the grounding (leakage) fault of low-voltage distribution networks in time, which is an essential technical measure to reduce electric shocks and fire accidents and improve power supply safety. This paper systematically analyzes the operating characteristics of low-voltage distribution networks and proposes a distributed residual current protection method based on closed sections. It utilizes the capabilities of a distribution IoT platform to provide comprehensive measurement information for the entire substation area. A method was introduced to divide the low-voltage distribution substation into different protection closed surfaces, defining the current phasor at the external contact point of the closed surface and the remaining current of the closed surface. A calculation method for the critical current based on the remaining current of the closed surface for fault detection was proposed. Case studies have shown that this method is less affected by the inherent current and can significantly improve the sensitivity of protection. For TN-C and TN-C-S systems, in the selection of closed surfaces, the repeated grounding point of the neutral line is excluded from the closed surface. This method can also overcome the impact of residual current changes when load switching, demonstrating the flexibility of the new principle.

Multitudinous broadly neutralizing antibodies (bNAbs) against HIV-1 have been developed as novel antiviral prophylactic and therapeutic agents. Combinations of bNAbs are generally even more effective than when they are applied individually, showing excellent neutralization coverage and limiting the emergence of escape mutants. In this study, we investigated the design and characterization of three trispecific antibodies that allow a single molecule to interact with independent HIV-1 envelope determinants—(1) the host receptor CD4, (2) the host co-receptor CCR5 and (3) distinct domains in the envelope glycoprotein of HIV-1—using an ELISA, an HIV-1 pseudovirus neutralization assay and in vivo antiviral experiments in humanized mice. We found that trispecific bNAbs and monovalent ones all had satisfactory binding activities against the corresponding antigens in the ELISA, exhibited higher potency and breadth than any previously described single bnAb in the HIV-1 pseudovirus neutralization assay and showed an excellent antiviral effect in vivo. The trispecific antibodies simultaneously recognize the host receptor CD4, host co-receptor CCR5 and HIV-1 envelope glycoprotein, which could mean they have promise as prophylactic and therapeutic agents against HIV-1.

In the original publication [...]

Nowadays, massive photovoltaic power stations are being integrated into grid networks. However, a large number of photovoltaic facilities are located in special areas, which presents difficulties in management. Unmanned Aerial Vehicle (UAV)-assisted data collection will be a prospective solution for photovoltaic systems. In this paper, based on Deep Reinforcement Learning (DRL), we propose a UAV-assisted scheme, which could be used in scenarios without awareness of sensor nodes’ (SNs) precise locations and has better universality. The optimized data collection work was formulated as a Markov Decision Process (MDP), and the approximate optimal policy was found by Deep Q-Learning (DQN). The simulation results show efficiency and convergence and demonstrate the effectiveness of the proposed scheme compared with other benchmarks.

The generation of a strong electromagnetic weapon requires the electromagnetic protection performance of the photoelectric system, including the high shielding and ultra-wideband protection characteristics against strong electromagnetic attacks and superhigh infrared transmittance. This article aims to excite surface plasmons by etching a subwavelength circular structure array run through a metal film. At the same time, the local field enhancement effect based on surface plasmons is used to tune specific wavelengths of light, achieving the goal of enhancing the optical transmission effect. Ulteriorly, the amplitude and position of the infrared response peak are controlled by optimizing the structural geometric parameters to achieve filtering effects in different wavebands. Furthermore, through the inversion calculation of the transmission spectrum of the circle array structure in the visible light band, the different colors of its surface under different parameters can correspond one-to-one to its performance, so as to intuitively identify different filter types and their performance. Meanwhile, the remaining metal film after etching off the circle array structure region constitutes an ultra-wideband shielding layer as a continuous conductor, achieving a shielding efficiency of more than 45 dB in the radar band (1–18 GHz). It is worth noting that the cascaded theory combines ultra-thin metal films with thick substrates to solve the problem of software running for long periods of time and under high loads during the simulation of light propagation. This scheme greatly reduces the error between simulation and practical application.

Pueraria thomsonii Benth. is a perennial leguminous vine with medicinal and nutritional value. However, rapid postharvest physiological deterioration (PPD) reduces its quality and market value. To detect gene expression levels, the quantitative reverse transcription polymerase chain reaction (qRT-PCR) technique requires stable internal reference genes (IRGs). Our findings indicated that an ethephon (C2H6ClO3P) treatment delayed PPD in P. thomsonii tuberous roots and an RNA-seq analysis revealed a significant number of differentially expressed genes (DEGs). To find stable IRGs for the further identification of the genes associated with delayed PPD in P. thomsonii, eight candidate IRGs of the tuberous roots were screened and assessed using qRT-PCR. The expression stability of these genes was determined and ranked using five different algorithms, including NormFinder, BestKeeper, ΔCt, GeNorm, and ReFinder. Consequently, we identified two genes, PtUBC10 and PtACT7, as the best candidate IRGs for qRT-PCR normalization in P. thomsonii, both exposed to ethephon treatment and in different tissues. Moreover, PtUBC10 was found to be the most stably expressed IRG of P. thomsonii during the ethephon treatment. The findings of this investigation furnish significant insights for future gene expression analyses concerning the delay of PPD via ethephon administration, which could also be used in other tuberous plants.

Metal mesh films have been shown to be a promising strategy to effectively mitigate the growing issue of electromagnetic interference (EMI) in optoelectronic systems. To achieve superior shielding effectiveness, it is common to increase the thickness of the mesh film. However, mesh-based shielding materials have frequency-dependent shielding effectiveness that decreases as the frequency increases. Simply increasing the thickness of the mesh cannot effectively enhance the EMI shielding effectiveness at high frequencies. This will further lead to challenges such as increased processing difficulties and higher costs. In this paper, we present an infrared transparent electromagnetic shielding window based on metal mesh with irregular patterns and proper thickness. The mesh coating is fabricated on a sapphire substrate using ultraviolet photolithography technology and exhibits an efficient electromagnetic shielding effectiveness of more than 20 dB over the wide frequency range of 1.7–18 GHz while maintaining high infrared optical transparency. More importantly, there is no distinct variation in shielding effectiveness between low and high frequency ranges, demonstrating a balanced shielding characteristic across a broad frequency band. This work could be crucial in designing cost-effective and efficient EMI shielding windows for optoelectronic systems.

The infrared band is one of the important communication windows. Most of the detectors and sensors working in this band are designed and manufactured based on micro- and nano-lithography technology. In this article, we cut the giant-sized thickness of the transparent substrate and the metal film was uniformly sliced. Then, we used the CST software to simulate the sliced substrate and the metal film to obtain the optical response parameters for each slice. Finally, the combination of metal film and substrate was realized by cascading calculation of the two port transmission line theory, which solves problems such as overlong simulation time and cumbersome running load caused by huge grid divisions due to the difference between the substrate thickness and the response wavelength in the process of simulating light propagation. On the other hand, the cascade analysis method was experimentally verified by constructing a surface plasmon filter in the medium infrared band, which provides an effective idea and solution for bridging the gap between simulation and engineering application.

As an inhibitor of ethylene receptors, 1-methylcyclopropene (1-MCP) can delay the ripening of papaya. However, improper 1-MCP treatment will cause a rubbery texture in papaya. Understanding of the underlying mechanism is still lacking. In the present work, a comparative sRNA analysis was conducted after different 1-MCP treatments and identified a total of 213 miRNAs, of which 44 were known miRNAs and 169 were novel miRNAs in papaya. Comprehensive functional enrichment analysis indicated that plant hormone signal pathways play an important role in fruit ripening. Through the comparative analysis of sRNAs and transcriptome sequencing, a total of 11 miRNAs and 12 target genes were associated with the ethylene and auxin signaling pathways. A total of 1741 target genes of miRNAs were identified by degradome sequencing, and nine miRNAs and eight miRNAs were differentially expressed under the ethylene and auxin signaling pathways, respectively. The network regulation diagram of miRNAs and target genes during fruit ripening was drawn. The expression of 11 miRNAs and 12 target genes was verified by RT-qPCR. The target gene verification showed that cpa-miR390a and cpa-miR396 target CpARF19-like and CpERF RAP2-12-like, respectively, affecting the ethylene and auxin signaling pathways and, therefore, papaya ripening.

To satisfy the demands of wireless communication systems for tunable shielding materials, in this work, a graphene/ion gel/graphene sandwich structure is proposed, based on graphene and a solid ionic material ion gel. After modelling, preparing and testing, it was found that the structure could achieve more than 10 dB shielding effectiveness tuning in GHz and THz bands. Meanwhile, the adjusting speed of the structure was also studied, displaying effective dynamic tuning in the second order. Furthermore, the fabricated samples have the advantages of a low profile, easily conformable, and convenient processing, which are of great potential in emerging electronic devices.

Long non-coding RNAs (lncRNAs) are pervasive transcripts of longer than 200 nucleotides and indiscernible coding potential. lncRNAs are implicated as key regulatory molecules in various fundamental biological processes at transcriptional, post-transcriptional, and epigenetic levels. Advances in computational and experimental approaches have identified numerous lncRNAs in plants. lncRNAs have been found to act as prime mediators in plant growth, development, and tolerance to stresses. This review summarizes the current research status of lncRNAs in planta, their classification based on genomic context, their mechanism of action, and specific bioinformatics tools and resources for their identification and characterization. Our overarching goal is to summarize recent progress on understanding the regulatory role of lncRNAs in plant developmental processes such as flowering time, reproductive growth, and abiotic stresses. We also review the role of lncRNA in nutrient stress and the ability to improve biotic stress tolerance in plants. Given the pivotal role of lncRNAs in various biological processes, their functional characterization in agriculturally essential crop plants is crucial for bridging the gap between phenotype and genotype.

Objectives: This study examined the reliability of two objective measurement tools in assessing children’s physical activity (PA) levels in an exergaming setting. Methods: A total of 377 children (190 girls, Mage = 8.39, SD = 1.55) attended the 30-min exergaming class every other day for 18 weeks. Children’s PA levels were concurrently measured by NL-1000 pedometer and ActiGraph GT3X accelerometer, while children’s steps per min and time engaged in sedentary, light, and moderate-to-vigorous PA were estimated, respectively. Results: The results of intraclass correlation coefficient (ICC) indicated a low degree of reliability (single measures ICC = 0.03) in accelerometers. ANOVA did detect a possible learning effect for 27 classes (p < 0.01), and the single measures ICC was 0.20 for pedometers. Moreover, there was no significant positive relationship between steps per min and time spent in moderate-to-vigorous physical activity (MVPA). Finally, only 1.3% variance was explained by pedometer as a predictor using Hierarchical Linear Modeling to further explore the relationship between pedometer and accelerometer data. Conclusions: The NL-1000 pedometers and ActiGraph GT3X accelerometers have low reliability in assessing elementary school children’s PA levels during exergaming. More research is warranted in determining the reliable and accurate measurement information regarding the use of modern devices in exergaming setting.