Search

Coastal areas often experience high population density and intense human activity owing to the considerable value of the ocean. Therefore, devices for monitoring marine disasters are crucial for ensuring the safety of human life. Herein, we develop hemispherical spring origami (SO) triboelectric nanogenerators (TENGs) (HSO-TENGs) for self-powered ocean wave monitoring. Optimization is performed using two approaches. First, swing machine experiments are conducted to investigate the monitoring performance of the HSO-TENGs regarding wave height and period with satisfactory accuracy. To increase power generation and monitoring accuracy, the internal inertia and centroid of gravity of the HSO-TENGs are optimized with respect to the structural parameters (i.e., magnet weight, hammer height, and external swing arm length). Second, numerical simulations are performed using the smoothed-particle hydrodynamics (SPH) method to determine the most suitable fixed condition for the HSO-TENGs for sensing wave changes. Subsequently, wave tank experiments are conducted on the HSO-TENGs to determine their ability to sense wave height, period, frequency, and direction. Tests related to supplying other sensors are also conducted. Eventually, the ability of the HSO-TENGs to monitor wave direction and spreading parameters is investigated in a numerical SPH circular wave tank. The results prove that the optimized HSO-TENGs can achieve powering and sensing through the same device. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) results in the abnormal regulation of cellular metabolic pathways. Constraint-based modeling approaches can be utilized to dissect metabolic reprogramming, enabling the identification of biomarkers and anticancer targets for diagnosis and treatment. In this study, two genome-scale metabolic models (GSMMs) were reconstructed by employing RNA sequencing expression patterns of hepatocellular carcinoma (HCC) and their healthy counterparts. An anticancer target discovery (ACTD) framework was integrated with the two models to identify HCC targets for anticancer treatment. The ACTD framework encompassed four fuzzy objectives to assess both the suppression of cancer cell growth and the minimization of side effects during treatment. The composition of a nutrient may significantly affect target identification. Within the ACTD framework, ten distinct nutrient media were utilized to assess nutrient uptake for identifying potential anticancer enzymes. The findings revealed the successful identification of target enzymes within the cholesterol biosynthetic pathway using a cholesterol-free cell culture medium. Conversely, target enzymes in the cholesterol biosynthetic pathway were not identified when the nutrient uptake included a cholesterol component. Moreover, the enzymes PGS1 and CRL1 were detected in all ten nutrient media. Additionally, the ACTD framework comprises dual-group representations of target combinations, pairing a single-target enzyme with an additional nutrient uptake reaction. Additionally, the enzymes PGS1 and CRL1 were identified across the ten-nutrient media. Furthermore, the ACTD framework encompasses two-group representations of target combinations involving the pairing of a single-target enzyme with an additional nutrient uptake reaction. Computational analysis unveiled that cell viability for all dual-target combinations exceeded that of their respective single-target enzymes. Consequently, integrating a target enzyme while adjusting an additional exchange reaction could efficiently mitigate cell proliferation rates and ATP production in the treated cancer cells. Nevertheless, most dual-target combinations led to lower side effects in contrast to their single-target counterparts. Additionally, differential expression of metabolites between cancer cells and their healthy counterparts were assessed via parsimonious flux variability analysis employing the GSMMs to pinpoint potential biomarkers. The variabilities of the fluxes and metabolite flow rates in cancer and healthy cells were classified into seven categories. Accordingly, two secretions and thirteen uptakes (including eight essential amino acids and two conditionally essential amino acids) were identified as potential biomarkers. The findings of this study indicated that cancer cells exhibit a higher uptake of amino acids compared with their healthy counterparts. [ABSTRACT FROM AUTHOR]

Simple Summary: In poultry production, fasting can remodel ovarian function and thereby delay the aging process of chickens. However, this approach may induce various stresses on the intestinal health of chickens. So, intestinal injury, the microbiome, and the metabolome were analyzed individually and integrated to elucidate the impact of the intestinal flora on intestinal injury during fasting-induced molting (FIM). The findings revealed that fasting led to intestinal villus atrophy, inflammation in the intestines, and disruption of gut microbiota and metabolites. During the fasting period, intestinal injury is associated with an increased abundance of Escherichia_Shigella and related metabolites Citrulline and Sterobilin, as well as a decreased abundance of Ruminococcaceae_UCG-013 and Lactobacillus and related metabolites Lanthionine and reduced Glutathione. This provides an experimental basis for improving the gut microbiota and reducing intestinal inflammation during the FIM process. Fasting-induced molting (FIM) is a common method used to improve the laying performance of aged laying hens. Nevertheless, this approach may impose various stresses on chickens, such as disruptions in intestinal flora and inflammation issues within the intestines. However, the impact of an imbalance in intestinal flora on intestinal health during the FIM process remains elusive. Therefore, intestinal injury, the microbiome, and the metabolome were analyzed individually and integrated to elucidate the impact of the intestinal flora on intestinal health during the FIM process. The findings indicated that fasting resulted in a notable reduction in villus height and villus/crypt ratio, coupled with elevated levels of intestinal inflammation and permeability. During the fasting period, microbiota compositions changed. The abundance of Escherichia_Shigella increased, while the abundance of Ruminococcaceae_UCG-013 and Lactobacillus decreased. Escherichia_Shigella was positively correlated with Citrinin and Sterobilin, which lead to intestinal inflammation. Ruminococcaceae_UCG-013 and Lactobacillus exhibited positive correlations with Lanthionine and reduced Glutathione, thereby reducing intestinal inflammation. This study screened the intestinal probiotics, Ruminococcaceae UCG-013 and Lactobacillus, that influence gut health during the fasting period, providing an experimental basis for improving gut microbiota and reducing intestinal inflammation during the FIM process. [ABSTRACT FROM AUTHOR]

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system. [ABSTRACT FROM AUTHOR]

Monitoring hydrogen sulfide (H2S) in living organisms is very important because H2S acts as a regulator in many physiological and pathological processes. Upregulation of endogenous H2S concentration has been shown to be closely related to the occurrence and development of tumors, atherosclerosis, neurodegenerative diseases and diabetes. Herin, a novel fluorescent probe HND with aggregation-induced emission was designed. Impressively, HND exhibited a high selectivity, fast response (1 min) and low detection limit (0.61 μM) for H2S in PBS buffer (10 mM, pH = 7.42). Moreover, the reaction mechanism between HND and H2S was conducted by Job's plot, HR-MS, and DFT. In particular, HND was successfully employed to detect H2S in HeLa cells. [ABSTRACT FROM AUTHOR]

Mesoscale eddies are ubiquitous oceanic phenomena and play an important role in ocean circulation, ocean dynamics, and the transport of material energy. Temperature anomalies are a crucial parameter that reflects the state of mesoscale eddies. This study proposes a Gaussian function model to fit the vertical temperature anomaly (TA) profile to facilitate the analysis of variations, and the principle of the model is based on the fact that each TA profile tends to fluctuate around one or more peaks. The model is extracted and validated using Argo profiles within cyclonic and anticyclonic eddies in the Northwest Pacific Ocean spanning over the period from 2002 to 2021. The validation demonstrates that the model can accurately recover the vertical TA profiles with a limited number of parameters. This makes it suitable for analysing the spatial distribution patterns that require a large sample count. The analysis indicates that eddies with different TA profiles have a spatial aggregation effect in geographic distribution. Eddies with lower extreme temperature anomalies, at depths of 200–300 m, are mainly distributed along two bands on the north side of the Kuroshio Extension (KE) and the North Equatorial Current. Eddies with extreme TAs at the deepest depth (500–600 m) are distributed along the KE. [ABSTRACT FROM AUTHOR]

In order to stop and reverse land degradation and curb the loss of biodiversity, the United Nations 2030 Agenda for Sustainable Development proposes to combat desertification. In this paper, a fractional vegetation–water model in an arid flat environment is studied. The pattern behavior of the fractional model is much more complex than that of the integer order. We study the stability and Turing instability of the system, as well as the Hopf bifurcation of fractional order α , and obtain the Turing region in the parameter space. According to the amplitude equation, different types of stationary mode discoveries can be obtained, including point patterns and strip patterns. Finally, the results of the numerical simulation and theoretical analysis are consistent. We find some novel fractal patterns of the fractional vegetation–water model in an arid flat environment. When the diffusion coefficient, d, changes and other parameters remain unchanged, the pattern structure changes from stripes to spots. When the fractional order parameter, β , changes, and other parameters remain unchanged, the pattern structure becomes more stable and is not easy to destroy. The research results can provide new ideas for the prevention and control of desertification vegetation patterns. [ABSTRACT FROM AUTHOR]

The quality of rice, evaluated using multiple quality-related traits, is the main determinant of its market competitiveness. In this study, two japonica rice varieties with significant differences in quality-related traits were used as parents to construct two populations, BC3F2 and BC3F2:3, with Kongyu131 (KY131) as the recurrent parent. A genetic linkage map was constructed using the BC3F2 population based on 151 pairs of SSR/InDel polymorphic markers selected between the parents. Grain-shape-related traits (grain length GL, grain width GW, and length-to-width ratio LWR), chalkiness-related traits (white-core rate WCR, white-belly rate WBR, white-back rate BR, and chalkiness rate CR), and amylose content (AC) were investigated in the two populations in 2017 and 2018. Except for BR and CR, the traits showed similar characteristics with a normal distribution in both populations. Genetic linkage analysis was conducted for these quality-related traits, and a total of 37 QTLs were detected in the two populations. Further validation was performed on the newly identified QTLs with larger effects, and three grain shape QTLs and four chalkiness QTLs were successfully validated in different environments. One repeatedly validated QTL, qWCR3, was selected for fine mapping and was successfully narrowed down to a 100 kb region in which only two genes, LOC_0s03g45210 and LOC_0s03g45320, exhibited sequence variations between the parents. Furthermore, the variation of LOC_Os03g45210 leads to a frameshift mutation and premature protein termination. The results of this study provide a theoretical basis for positional cloning of the qWCR3 gene, thus offering new genetic resources for rice quality improvement. [ABSTRACT FROM AUTHOR]

With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance. [ABSTRACT FROM AUTHOR]

LiDAR has high accuracy and resolution and is widely used in various fields. In particular, phase-modulated continuous-wave (PhMCW) LiDAR has merits such as low power, high precision, and no need for laser frequency modulation. However, with decreasing signal-to-noise ratio (SNR), the noise on the signal waveform becomes so severe that the current methods to extract the time-of-flight are no longer feasible. In this paper, a novel method that uses deep neural networks to measure the pulse width is proposed. The effects of distance resolution and SNR on the performance are explored. Recognition accuracy reaches 81.4% at a 0.1 m distance resolution and the SNR is as low as 2. We simulate a scene that contains a vehicle, a tree, a house, and a background located up to 6 m away. The reconstructed point cloud has good fidelity, the object contours are clear, and the features are restored. More precisely, the three distances are 4.73 cm, 6.00 cm, and 7.19 cm, respectively, showing that the performance of the proposed method is excellent. To the best of our knowledge, this is the first work that employs a neural network to directly process LiDAR signals and to extract their time-of-flight. [ABSTRACT FROM AUTHOR]

Using sodium lignosulfonate as feedstock, ZnCl2 and NaHCO3 co-activated the hierarchical porous carbons (HPCs) were prepared by one-pot pyrolysis with different NaHCO3 dosages (0–4 g) and carbonization temperatures (400–600 °C). Subsequently, phosphotungstate (HPW) was supported with the resulting biochar for the α-pinene hydration reaction to produce α-terpineol. The optimum preparation conditions were determined according to the yield of α-terpineol. The formation mechanism and physicochemical properties of HPCs were analyzed through TG, SEM, XPS, XRD, FT-IR, and N2 adsorption–desorption isotherms. The results demonstrated that NaHCO3 underwent a two-step reaction which liberated a substantial quantity of CO2, thereby enhancing activated carbon's macroporous and mesoporous structures. Simultaneously, NaHCO3 mitigated strong acid gas (HCl) emissions during ZnCl2 activation. Compared with AC450-4:8:0 prepared by ZnCl2 activation alone, the total pore volume of AC450-4:8:2 prepared by co-activation is increased from 0.595 mL/g to 0.754 mL/g and the mesopore rate from 47.7% to 77.8%, which is conducive to reducing the steric hindrance of the hydration reaction and improving the selectivity. Hydration experiments show that the selectivity of α-terpineol is 55.7% under HPW/AC450-4:8:2 catalysis, higher than 31.0% for HPW and 47.4% for HPW/AC450-4:8:0. [ABSTRACT FROM AUTHOR]

The influenza BM2 transmembrane domain (BM2TM), an acid-activated proton channel, is an attractive antiviral target due to its essential roles during influenza virus replication, whereas no effective inhibitors have been reported for BM2. In this study, we draw inspiration from the properties of cyclodextrins (CDs) and hypothesize that CDs of appropriate sizes may possess the potential to act as inhibitors of the B M 2 T M proton channel. To explore this possibility, molecular dynamics simulations were employed to assess their inhibitory capabilities. Our findings reveal that CD4, CD5, and CD6 are capable of binding to the B M 2 T M proton channel, resulting in disrupted water networks and reduced hydrogen bond occupancy between H19 and the solvent within the B M 2 T M channel necessary for proton conduction. Notably, CD4 completely obstructs the B M 2 T M water channel. Based on these observations, we propose that CD4, CD5, and CD6 individually contribute to diminishing the proton transfer efficiency of the BM2 protein, and CD4 demonstrates promising potential as an inhibitor for the BM2 proton channel. [ABSTRACT FROM AUTHOR]

Space infrared dim target recognition is an important applications of space situational awareness (SSA). Due to the weak observability and lack of geometric texture of the target, it may be unreliable to rely only on grayscale features for recognition. In this paper, an intelligent information decision-level fusion method for target recognition which takes full advantage of the ensemble classifier and Dempster–Shafer (DS) theory is proposed. To deal with the problem that DS produces counterintuitive results when evidence conflicts, a contraction–expansion function is introduced to modify the body of evidence to mitigate conflicts between pieces of evidence. In this method, preprocessing and feature extraction are first performed on the multi-frame dual-band infrared images to obtain the features of the target, which include long-wave radiant intensity, medium–long-wave radiant intensity, temperature, emissivity–area product, micromotion period, and velocity. Then, the radiation intensities are fed to the random convolutional kernel transform (ROCKET) architecture for recognition. For the micromotion period feature, a support vector machine (SVM) classifier is used, and the remaining categories of the features are input into the long short-term memory network (LSTM) for recognition, respectively. The posterior probabilities corresponding to each category, which are the result outputs of each classifier, are constructed using the basic probability assignment (BPA) function of the DS. Finally, the discrimination of the space target category is implemented according to improved DS fusion rules and decision rules. Continuous multi-frame infrared images of six flight scenes are used to evaluate the effectiveness of the proposed method. The experimental results indicate that the recognition accuracy of the proposed method in this paper can reach 93% under the strong noise level (signal-to-noise ratio is 5). Its performance outperforms single-feature recognition and other benchmark algorithms based on DS theory, which demonstrates that the proposed method can effectively enhance the recognition accuracy of space infrared dim targets. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype–phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies. [ABSTRACT FROM AUTHOR]

For derivative function estimation, conventional research only focuses on the derivative estimation of one-dimensional functions. This paper considers partial derivatives estimation of a multivariate variance function in a heteroscedastic model. A wavelet estimator of partial derivatives of a multivariate variance function is proposed. The convergence rates of a wavelet estimator under different estimation errors are discussed. It turns out that the strong convergence rate of the wavelet estimator is the same as the optimal uniform almost sure convergence rate of nonparametric function problems. [ABSTRACT FROM AUTHOR]

Inhibition of the Embryonic Ectoderm Development (EED) subunit in Polycomb Repressive Complex 2 (PRC2) can inhibit tumor growth. In this paper, we selected six experimentally designed EED competitive Inhibitors of the triazolopyrimidine derivatives class. We investigated the difference in the binding mode of the natural substrate to the Inhibitors and the effects of differences in the parent nuclei, heads, and tails of the Inhibitors on the inhibitory capacity. The results showed that the binding free energy of this class of Inhibitors was close to or lower compared to the natural substrate, providing an energetic basis for competitive inhibition. For the Inhibitors, the presence of a strong negatively charged group at the 6-position of the parent nucleus or the 8′-position of the head would make the hydrogen atom on the head imino group prone to flip, resulting in the vertical movement of the parent nucleus, which significantly decreased the inhibitory ability. When the 6-position of the parent nucleus was a nonpolar group, the parent nucleus would move horizontally, slightly decreasing the inhibitory ability. When the 8′-position of the head was methylene, it formed an intramolecular hydrophobic interaction with the benzene ring on the tail, resulting in a significant increase in inhibition ability. [ABSTRACT FROM AUTHOR]

With the deepening of exploration and development of tight sandstone gas reservoirs, the remaining recoverable reservoirs gradually become thinner with the vertical stratigraphic structure. The geomechanical properties become complex, and development based on conventional hydraulic fracturing methods often leads to serious problems, such as difficult control of fracture height, penetrating interlayers, too short fracture length, and inadequate proppant filling. In view of the above problems, we conducted a numerical investigation on a hydraulic fracturing scheme in a multi-layered and thin tight sandstone gas reservoir. According to the dataset from wells in a real gas reservoir in China's Ordos Basin, the relevant geomechanical characteristics of the gas layers, together with the interlayers in the main production interval, were obtained, based on which, a fine numerical model was developed. By using the PL3D fracture propagation algorithm, a 3D hydraulic fracture propagation model was produced, and then using microseismic monitoring and production data matching, a high-precision hydraulic fracture model of the multi-layered and thin tight sandstone gas reservoir was obtained. On this basis, the influence of different geomechanical parameters and fracturing operational parameters on hydraulic fracture propagation was analyzed. Finally, an optimized hydraulic fracturing scheme that fitted the characteristics of the multi-layered and thin tight sandstone gas reservoir was proposed. Using a typical reservoir example, the optimized scheme enabled control of the fracture height in thin layers and the creation of long fractures with better proppant filling, so that the productivity of the fracture was significantly improved. [ABSTRACT FROM AUTHOR]

The detection of small targets within the background of sea clutter is a significant challenge faced in radar signal processing. Small target echoes are weak in energy, and can be submerged by sea clutter and sea spikes, which are caused by overturning waves and breaking waves. This severely affects the radar target detection performance. This paper proposes a smoothed pseudo-Wigner–Ville distribution–singular value decomposition (SPWVD-SVD) method for sea clutter suppression. This method determines the instantaneous frequency range of the target by contrasting the time–frequency characteristics of the sea spike and the target. Subsequently, it employs a singular value difference spectrum to reduce the rank of the Hankel matrix, thereby reducing the computational burden of the instantaneous frequency estimation step in the experiment. Based on the instantaneous frequency range of the target in the time–frequency domain, the singular values of the target signal are retained, while the singular values of clutter are set to zero. This process accomplishes the reconstruction of radar echo signals and effectively achieves the suppression of sea clutter. The suppression effect is verified using simulation data alongside ten sets of Intelligent Pixel processing X-band (IPIX) radar data against the background of sea spikes. By contrasting the clutter amplitudes before and after suppression, the SPWVD-SVD algorithm demonstrated an average clutter suppression of 15.06 dB, which proves the effectiveness of the proposed algorithm in suppressing sea clutter. [ABSTRACT FROM AUTHOR]

In the current investigation, carbon-based solid acid catalysts were synthesized from peanut shells (PSs) and rice straw (RS) using ZnCl2 activation and concentrated sulfuric acid sulfonation. These catalysts were then employed for the hydration of pinene to produce terpineol. The research findings suggest that the natural porous structure of RS is more amenable to ZnCl2 activation compared to PSs. Furthermore, the catalysts prepared from fully activated RS by ZnCl2 (RSA-C-S) had a higher SBET and higher density of oxygen-containing groups (–COOH) in comparison with unactivated RS-based solid acids (RSC-S). The characterization outcomes revealed that RSA-C-S possesses a specific surface area of 527.0 m2/g, significantly outperforming RSC-S, which has a surface area of 420.9 m2/g. Additionally, RSA-C-S registered a higher –COOH density of 1.37 mmol/g, as opposed to RSC-S's, with 1.07 mmol/g, attributable to the partial oxidation of internal –OH groups during activation. Experimental data from hydration tests confirmed that the catalyst's superior performance is largely attributed to its elevated specific surface area and a high density of –COOH functional groups. Under optimal reaction parameters, RSA-C-S demonstrated unparalleled catalytic efficiency in the synthesis of α-terpineol via hydration of α-pinene, achieving conversion and selectivity rates of 87.15% and 54.19%, respectively. [ABSTRACT FROM AUTHOR]

The energy feedback system (EFS) is widely accepted to utilize the regenerative braking energy (RBE) in an urban rail traction power supply system (TPSS). However, the sharing relationship of RBE between EFS, traction trains and on-board braking resistors is not clear. In addition, the impact of EFS operation on the sharing of RBE has been rarely studied. This paper proposed a hierarchical operation optimization method for improving the utilization of shared RBE in TPSS through the EFS. An optimizing model for the dynamic start-up voltage threshold of EFS is established, with the objective of minimizing TPSS power consumption. A fast prediction model of train operation information is developed to analyze the steady-state power flow in advance. The optimal solution is searched using a salp swarm algorithm (SSA) on a per second basis. A microsystem of three traction stations and two trains is analyzed. Compared to the conventional constant voltage operation scheme, the optimal solution achieves a maximum additional energy-saving efficiency improvement of 2.44%. Efficient sharing of RBE is identified as the key to achieving energy savings. Regarding the local control part, system stability analysis is verified. Real-time simulation results indicate that the dynamic operating mode of EFS efficiently distributes RBE. [ABSTRACT FROM AUTHOR]

In this work, we prepared a green, cheap material by chelating humic acid with ferric ions (HA-Fe) and used it as an anode material in LIBs for the first time. From the SEM, TEM, XPS, XRD, and nitrogen adsorption–desorption experimental results, it was found that the ferric ion can chelate with humic acid successfully under mild conditions and can increase the surface area of materials. Taking advantage of the chelation between the ferric ions and HA, the capacity of HA-Fe is 586 mAh·g−1 at 0.1 A·g−1 after 1000 cycles. Moreover, benefitting from the chelation effect, the activation degree of HA-Fe (about 8 times) is seriously improved compared with pure HA material (about 2 times) during the change–discharge process. The capacity retention ratio of HA-Fe is 55.63% when the current density increased from 0.05 A·g−1 to 1 A·g−1, which is higher than that of HA (32.55%) and Fe (24.85%). In the end, the storage mechanism of HA-Fe was investigated with ex-situ XPS measurements, and it was found that the C=O and C=C bonds are the activation sites for storage Li ions but have different redox voltages. [ABSTRACT FROM AUTHOR]

Water vapor is a crucial component of the atmosphere. Its absorption significantly influences remote sensing by impacting radiation signals transmitted through the atmosphere. Determining columnar water vapor (CWV) from hyperspectral remote sensing data is essential during the imagery atmospheric correction process. Over the past 40 years, numerous CWV inversion algorithms have been developed, with refinements to enhance retrieval accuracy and reliability. In this study, we proposed an enhanced atmospheric pre-corrected differential absorption (APDA) algorithm. This enhancement was achieved by thoroughly analyzing water vapor absorption in relation to elevation and aerosol optical depth and extending look up tables (LUTs). The enhanced method utilizes a pre-built MODTRAN lookup table and is applied to ZY1-02D hyperspectral data from a satellite launched in 2020. We compared the inversion results of 10 ZY1-02D scenes obtained using the improved method with AERONET measurements and inversion results from commonly used atmospheric correction software, namely, FLAASH and ATCOR. The updated algorithm demonstrated a lower average error (0.0568 g·cm−2) and relative average error (10.49%) compared to the ATCOR software (0.17 g·cm−2 and 40.78%, respectively) and the FLAASH module (0.13 g·cm−2 and 30.82%, respectively). Consequently, the enhanced method outperforms traditional CWV inversion algorithms, especially at high altitudes. [ABSTRACT FROM AUTHOR]

Generation Z employees in the workplace cause a management challenge that enterprises have recently faced. The unique characteristics of Generation Z employees necessitate an urgent update to the knowledge of organizational management. However, few studies of the literature focus on the workplace behaviors of Generation Z. This study proposes that illegitimate tasks may lead to work withdrawal behavior among Generation Z employees. Based on the equity theory model, this study constructed a moderated mediation model to explore the impact of illegitimate tasks on the work withdrawal behavior of Generation Z employees, as well as the mediating role of perceived insider status and the moderating role of perceived overqualification. The analysis of survey data from 283 Generation Z employees in China at two time points found that illegitimate tasks are positively correlated with work withdrawal behavior. At the same time, the mediating role of perceived insider status was successfully confirmed. The results also showed that perceived overqualification strengthened the effect of illegitimate tasks on work withdrawal behavior and the mediating effect of perceived insider status. This study offers new insights into the management and development of Generation Z employees and the sustainable evolution of workplace relationships from both theoretical and practical perspectives. [ABSTRACT FROM AUTHOR]

MXenes-based materials are considered to be one of the most promising electrode materials in the field of sodium-ion batteries due to their excellent flexibility, high conductivity and tuneable surface functional groups. However, MXenes often have severe self-agglomeration, low capacity and unsatisfactory durability, which affects their practical value. The design and synthesis of advanced heterostructures with advanced chemical structures and excellent electrochemical performance for sodium-ion batteries have been widely studied and developed in the field of energy storage devices. In this review, the design and synthesis strategies of MXenes-based sodium-ion battery anode materials and the influence of various synthesis strategies on the structure and properties of MXenes-based materials are comprehensively summarized. Then, the first-principles research progress of MXenes-based sodium-ion battery anode materials is summarized, and the relationship between the storage mechanism and structure of sodium-ion batteries and the electrochemical performance is revealed. Finally, the key challenges and future research directions of the current design and synthesis strategies and first principles of these MXenes-based sodium-ion battery anode materials are introduced. [ABSTRACT FROM AUTHOR]

SWEET proteins play important roles in plant growth and development, sugar loading in phloem and resistance to abiotic stress through sugar transport. In this study, 13 BpSWEET genes were identified from birch genome. Collinearity analysis showed that there were one tandem repeating gene pair (BpSWEET1b/BpSWEET1c) and two duplicative gene pairs (BpSWEET17a/BpSWEET17b) in the BpSWEET gene family. The BpSWEET gene promoter regions contained several cis-acting elements related to stress resistance, for example: hormone-responsive and low-temperature-responsive cis-elements. Analysis of transcriptome data showed that BpSWEET genes were highly expressed in several sink organs, and the most BpSWEET genes were rapidly up-regulated under cold stress. BpSWEET1c, which was highly expressed in cold stress, was selected for further analysis. It was found that BpSWEET1c was located on the cell membrane. After 6 h of 4 °C stress, sucrose content in the leaves and roots of transient overexpressed BpSWEET1c was significantly higher than that of the control. MDA content in roots was significantly lower than that of the control. These results indicate that BpSWEET1c may play a positive role in the response to cold stress by promoting the metabolism and transport of sucrose. In conclusion, 13 BpSWEET genes were identified from the whole genome level. Most of the SWEET genes of birch were expressed in the sink organs and could respond to cold stress. Transient overexpression of BpSWEET1c changed the soluble sugar content and improved the cold tolerance of birch. [ABSTRACT FROM AUTHOR]

Compared with high-pressure water and reagent washing decontamination, foam decontamination has a promising application due to its ability to significantly reduce the volume of radioactive waste liquids and effectively decontaminate the inner surface of the pipes, the interior of the large cavities, and the vertical walls. However, the foam is less stable, leading to a low decontamination rate. Currently, three main types of stabilizers with different stabilizing mechanisms, namely nanoparticles, polymers, and cosurfactants, are used to improve foam stability and thus increase the decontamination rate. Nanosilica (NS), xanthan gum (XG), and n-tetradecanol (TD) were used as typical representatives of nanoparticles, polymers, and cosurfactants, respectively, to improve the stability of the foam detergent with pH < 2 and chelating agents. The differences in the effects of these three types of stabilizers on foam properties were investigated. Although NS, XG, and TD all increase the half-life of the foam from 7.2 min to about 40 min, the concentration of TD is much lower than that of NS and XG in the foaming solution, and TD foaming solution has the highest foaming ratio. Moreover, TD can markedly lower the surface tension, resulting in a significant reduction of the wetting contact angle on the surfaces of glass, ceramic tile, stainless steel, and paint, while NS and XG cannot signally change the surface tension and have no obvious effect on the wetting contact angle. At low shear rates, TD can increase the apparent viscosity of foam by two orders of magnitude, and the wall-hanging time of the foam on the vertical wall is more than 30 min. In contrast, NS and XG cause a limited increase in the apparent viscosity of the foam, and the wall-hanging times are both less than 5 min. In addition, TD foaming solution has excellent storage stability, and the storage time has no obvious effect on the performance of the foam. And after only three days of storage, NS undergoes severe agglomeration and precipitation in the foaming solution, resulting in a complete loss of the stabilizing effect. After 90 days of storage, the half-life of XG foam decreases by 26%. For simulated radioactive uranium contamination on both horizontal and vertical surfaces, TD can significantly improve the decontamination rate, especially for vertical surfaces, where TD can increase the single decontamination rate by more than 50%. [ABSTRACT FROM AUTHOR]

Location information is the core data in IoT applications, which is the essential foundation for scene interpretation and interconnection of everything, and thus high-precision positioning is becoming an immediate need. However, the non-line-of-sight (NLOS) effect of indoor complex environment on UWB signal occlusion has been a major factor limiting the improvement in ultra-wideband (UWB) positioning accuracy, and the optimization of NLOS error has not yet been studied in a targeted manner. To this end, this paper deeply analyzes indoor scenes, divides NLOS into two forms of spatial occlusion and human occlusion, and proposes a particle filtering algorithm based on LOS/NLOS mapping and NLOS error optimization. This algorithm is targeted to optimize the influence of two different forms of NLOS, using spatial a priori information to accurately judge the LOS/NLOS situation of the anchor, optimizing the NLOS anchor ranging using IMU to project the virtual position, judging whether the LOS anchor is affected by human occlusion, and correcting the affected LOS anchor using the established human occlusion error model. Through experimental verification, the algorithm can effectively suppress two different NLOS errors of spatial structure and human occlusion and can achieve continuous and reliable high-precision positioning and tracking in complex indoor environments. [ABSTRACT FROM AUTHOR]

Intense thermoacoustic oscillations may lead to severe deterioration due to the induced intolerable damage to combustors. A better understanding of unstable behaviors is important to prevent or suppress these oscillations. Active thermoacoustic coupling in practical combustors is caused primarily by two approaches: inherent turbulent fluctuations and the flame response to acoustic waves. Turbulent fluctuations are generally characterized by random noise. This paper experimentally expands on previous analytic studies regarding the influence of colored disturbances on the thermoacoustic response near the supercritical bifurcation point. Therein, a laboratory-scale Rijke-type thermoacoustic system is established, and both supercritical and subcritical bifurcations are observed. Then, Ornstein–Uhlenbeck (OU)-type external colored noise is introduced near the supercritical bifurcation point, and the effects of the corresponding correlation time τ c and noise intensity D are studied. The experimental results show that these variables of the colored noise significantly influence the dynamics of thermoacoustic oscillations in terms of the most probable amplitude and autocorrelation properties. A resonance-like behavior is observed as the noise intensity or the autocorrelation time of the colored noise is continuously varied, which means that the coherent resonance occurs in the thermoacoustic system. Finally, when the system is configured closer to the stability boundary, the extent of the coherence motion is intensified in the stochastic system response. Meanwhile, the signal-to-noise ratios (SNRs) of the colored-noise-induced response are found to become more distinguished, the optimal colored noise intensity decreases, and the optimal autocorrelation time increases. These findings provide valuable guidance to predict the onset of thermoacoustic instabilities. [ABSTRACT FROM AUTHOR]

Spectral imaging detection using acousto-optical tunable filters (AOTFs) faces a significant challenge of low throughput due to the traditional design that only receives a single polarization light. To overcome this issue, we propose a novel polarization multiplexing design and eliminate the need for crossed polarizers in the system. Our design allows for simultaneous collection of ±1 order light from the AOTF device, resulting in a more than two-fold increase in system throughput. Our analysis and experimental results validate the effectiveness of our design in improving system throughput and enhancing the imaging signal-to-noise ratio (SNR) by approximately 8 dB. In addition, AOTF devices used in polarization multiplexing applications require optimized crystal geometry parameter design that does not follow the parallel tangent principle. This paper proposes an optimization strategy for arbitrary AOTF devices which can achieve similar spectral effects. The implications of this work are significant for target detection applications. [ABSTRACT FROM AUTHOR]

Thermodynamic modeling of the Si–P and Si–Fe–P systems was performed using the CALculation of PHAse Diagram (CALPHAD) method based on critical evaluation of available experimental data in the literature. The liquid and solid solutions were described using the Modified Quasichemical Model accounting for the short-range ordering and Compound Energy Formalism considering the crystallographic structure, respectively. In the present study, the phase boundaries for the liquidus and solid Si phases of the Si–P system were reoptimized. Furthermore, the Gibbs energies of the liquid solution, (Fe)3(P,Si)1, (Fe)2(P,Si)1, and (Fe)1(P,Si)1 solid solutions and FeSi4P4 compound were carefully determined to resolve the discrepancies in previously assessed vertical sections, isothermal sections of phase diagrams, and liquid surface projection of the Si–Fe–P system. These thermodynamic data are of great necessity for a sound description of the entire Si–Fe–P system. The optimized model parameters from the present study can be used to predict any unexplored phase diagrams and thermodynamic properties within the Si–Fe–P alloys. [ABSTRACT FROM AUTHOR]

A selective laser-melted Al–Mn–Sc alloy with 99.9% relative density has been obtained in this work through systematic process optimization. The as-fabricated specimen had the lowest hardness and strength, but the highest ductility. The aging response has shown that 300 °C/5 h is the peak aged condition, and it had the highest hardness, yield strength, ultimate tensile strength, and elongation at fracture. Such a high strength was attributed to the uniformly distributed nano-sized secondary Al3Sc precipitates. A further increase in aging temperature to 400 °C resulted in an over-aged condition, which contained a reduced volume fraction of secondary Al3Sc precipitates and resulted in a reduced strength. [ABSTRACT FROM AUTHOR]

For effective removal and utilization of fluorine resources from industrial wastewater, stepwise removal and recovery of fluorine were accomplished by seeding crystallization and flotation. The effects of seedings on the growth and morphology of CaF2 crystals were investigated by comparing the processes of chemical precipitation and seeding crystallization. The morphologies of the precipitates were analyzed by X-ray diffraction (XRD) and scanning electron microscope (SEM) measurements. The seed crystal, fluorite, helps improve the growth of perfect CaF2 crystals. The solution and interfacial behaviors of the ions were calculated by molecular simulations. The existing perfect surface of fluorite was proven to provide the active sites for ion adhesion and formed a more ordered attachment layer than the precipitation procedure. The precipitates were then floated to recover calcium fluoride. By stepwise seeding crystallization and flotation, the products with a CaF2 purity of 64.42% can be used to replace parts of metallurgical-grade fluorite. Both removal of fluorine from wastewater and the reutilization of the fluorine resource were realized. [ABSTRACT FROM AUTHOR]

Promoters play a crucial role in controlling the spatial and temporal expression of genes at transcriptional levels in the process of higher plant growth and development. The spatial, efficient, and correct regulation of exogenous genes expression, as desired, is the key point in plant genetic engineering research. Constitutive promoters widely used in plant genetic transformation are limited because, sometimes, they may cause potential negative effects. This issue can be solved, to a certain extent, by using tissue-specific promoters. Compared with constitutive promoters, a few tissue-specific promoters have been isolated and applied. In this study, based on the transcriptome data, a total of 288 tissue-specific genes were collected, expressed in seven tissues, including the leaves, stems, flowers, pods, seeds, roots, and nodules of soybean (Glycine max). KEGG pathway enrichment analysis was carried out, and 52 metabolites were annotated. A total of 12 tissue-specific genes were selected via the transcription expression level and validated through real-time quantitative PCR, of which 10 genes showed tissue-specific expression. The 3-kb 5′ upstream regions of ten genes were obtained as putative promoters. Further analysis showed that all the 10 promoters contained many tissue-specific cis-elements. These results demonstrate that high-throughput transcriptional data can be used as effective tools, providing a guide for high-throughput novel tissue-specific promoter discovery. [ABSTRACT FROM AUTHOR]

As global inflation escalates and geopolitical conflicts exacerbate, the world's economy confronts an intensified degree of instability. In this volatile environment, blockchain currencies emerge as a potential bulwark, offering both value preservation and liquidity benefits. However, the conventional "mining" process introduces significant challenges, such as high energy consumption, data security risks, and detachment from the real economy, which potentially facilitate financial capital manipulation. This research endeavors to mitigate these issues, constructing an innovative blockchain cryptocurrency framework that integrates mining and distribution with intelligent big data. It also incorporates social contributions from individuals in domains such as health, knowledge, and ecological conservation. Consequently, the efficiency of cryptocurrency production and distribution correlates with the individual's societal contribution. The more substantial the contribution, the higher the intrinsic value of the individual and the more efficient the access. Utilizing a comprehensive framework of mathematical modeling, computer numerical simulation, and fuzzy integrated evaluation, we propose a novel endogenous-value blockchain cryptocurrency system. We quantify and optimize variables such as individual intrinsic value, community efficiency, redistribution weights, and total monetary potential. We introduce an innovative method for accumulating time-decaying values such as knowledge contribution and establish an anti-cheating framework. Our results indicate that this pioneering approach can significantly enhance mining efficiency and optimize cryptocurrency distribution. This counters traditional criticisms of blockchain currencies and paves the way for a more sustainable, fair, and efficient model for future blockchain currency systems. [ABSTRACT FROM AUTHOR]

Acousto-optic interaction geometry determines the spectral and spatial response of an acousto-optic tunable filter (AOTF). The precise calibration of the acousto-optic interaction geometry of the device is a necessary process before designing and optimizing optical systems. In this paper, we develop a novel calibration method based on the polar angular performance of an AOTF. A commercial AOTF device with unknown geometry parameters was experimentally calibrated. The experimental results show high precision, in some cases falling within 0.01°. In addition, we analyzed the parameter sensitivity and Monte Carlo tolerance of the calibration method. The results of the parameter sensitivity analysis show that the principal refractive index has a large influence on the calibration results, while other factors have little influence. The results of the Monte Carlo tolerance analysis show that the probability of the results falling 0.1° using this method is greater than 99.7%. This work provides an accurate and easy-to-perform method for AOTF crystal calibration and can contribute to the characteristic analysis of AOTFs and the optical design of spectral imaging systems. [ABSTRACT FROM AUTHOR]

Low-frequency oscillation (LFO) of the synchronous generators in power systems by wind power is boring. To improve the robustness of the damping control scheme, this paper applies the sliding mode control (SMC) at the doubly fed induction generator (DFIG), with the parameter of the SMC optimized by the eigen-sensitivity. The originalities lie in, (1) the states strongly associated with the critical modes are newly applied to design the sliding surface, (2) the closed-loop model of the power system with the improved equivalent control is derived to analyze the damping effect on the critical modes and the undesirable effect on the noncritical modes, (3) the gain in the improved equivalent control is optimized to damp the critical and noncritical modes, and (4) the eigenvector sensitivity is improved to derive the second-order eigen- sensitivity to solve the nonlinear optimization. Numerical results show that the proposed model damps the critical modes effectively for different wind speeds, while the undesirable effect on the noncritical modes is avoided. [ABSTRACT FROM AUTHOR]

Salt interpretation using seismic data is essential for structural interpretation and oil and gas exploration. Although deep learning has made great progress in automatic salt image segmentation, it is often difficult to obtain satisfactory results in complex situations. Thus, interactive segmentation with human intervention can effectively replace the fully automatic method. However, the current interactive segmentation cannot be directly applied to 3D seismic data and requires a lot of human interaction. Because it is difficult to collect 3D seismic data containing salt, we propose a workflow to simulate salt data and use a large amount of 3D synthetic salt data for training and testing. We use a 3D U-net model with skip connections to improve the accuracy and efficiency of salt interpretation. This model takes 3D seismic data volume with a specific size as an input and generates a salt probability volume of the same size as an output. To obtain more detailed salt results, we utilize a 3D graph-cut to ameliorate the results predicted by the 3D U-net model. The experimental results indicate that our method can achieve more efficient and accurate segmentation of 3D salt bodies than fully automatic methods. [ABSTRACT FROM AUTHOR]

Consider that the sound dipole source in the flow field is composed of multiple micro-spherical oscillating sources. An aerodynamic sound source identification method is established by the relationship among the oscillating source, the radiated sound pressure, and the pressure gradient of flow in the near-wall flow field, and the formula for calculating the sound power of the sound dipole source in unsteady flow is derived. It shows that the power of sound dipole sources is proportional to the square of the oscillating force or pressure gradient. The combination of the formula and CFD method is further applied to the flow around the cylinder, which clearly presents the sound power and location characteristics of sound dipole sources. Further, the relationship between the sound source and the flow separation, or flow vortex shedding, is analyzed. The corresponding correlation analysis is also carried out, which indicates that the sound dipole source exists in a finite area of the attached wall. The front end of the area is at the separation point along the circumferential direction of the wall, and the end is at the location where the separation vortex completely falls off and a trailing vortex begins to form. In addition, the thickness of the area exists along the radial direction and gradually increases backward. [ABSTRACT FROM AUTHOR]

Particulate matter-bound polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs (NPAHs) were first systematically studied in downtown (XT), suburban (GL) and rural (DA) sites in winter and summer in Hanoi, Vietnam, from 2019 to 2022. The mean concentrations of PAHs and NPAHs ranged from 0.76 ng m−3 to 50.2 ng m−3 and 6.07 pg m−3 to 1.95 ng m−3, respectively. The concentrations of PAHs and NPAHs in winter were higher than in summer, except for NPAHs in XT. We found the benzo[a]pyrene (BaP)/benzo[ghi]perylene (BgPe) ratio could effectively identify biomass burning in this study, in which a higher [BaP]/[BgPe] value indicates a greater effect of biomass burning on PAHs and NPAHs. The results indicated that atmospheric PAHs and NPAHs were mainly affected by motor vehicles (especially the unique motorcycles in Southeast Asia) in the summer in Hanoi. In winter, all sites were affected by the burning of rice straw to varying degrees, especially DA. The incremental lifetime cancer risk (ILCR) in Hanoi was first determined through ingestion, inhalation and dermal absorption. The results showed that residents in Hanoi faced high health risks, while females experienced higher health risks than males. The ingestion and dermal pathways indicated higher exposure risks than the usually considered inhalation pathway. [ABSTRACT FROM AUTHOR]

In order to study the stability control mechanism of deep soft rock roadway and the active support technology of the anchor-grouting flexible bolt, this paper takes the west wing transportation roadway of Yuandian No. 2 Coal Mine of Huaibei Mining Co., Ltd., Huaibei, China as the research background. By analyzing the occurrence conditions and failure characteristics of the surrounding rock of the west wing transportation roadway and the structural characteristics and mechanical properties of the anchor-grouting flexible bolt, combined with the elastic–plastic and superimposed arch theory analysis, the superposition community theoretical model and the superposition joint support scheme of "bolt (cable) + anchor net + anchor-grouting flexible bolt + shotcrete support" are proposed. The reliability of the combined support scheme is analyzed by FLAC 3D numerical simulation software and field experiment. The results show that the maximum roof-to-floor convergence and two-side convergence of the west wing transportation roadway are only 30.7 mm and 27.1 mm after adopting the combined support scheme, and the deep displacement variation is within 7 mm, which can effectively maintain the stability of the roadway. The combined support scheme has a certain reference value for other similar roadways. [ABSTRACT FROM AUTHOR]

In the field of object detection, deep learning models have achieved great success in recent years. Despite these advances, detecting small objects remains difficult. Most objects in aerial images have features that are a challenge for traditional object detection techniques, including small size, high density, high variability, and varying orientation. Previous approaches have used slicing methods on high-resolution images or feature maps to improve performance. However, existing slicing methods inevitably lead to redundant computation. Therefore, in this article we present a novel adaptive slicing method named ASAHI (Adaptive Slicing Aided Hyper Inference), which can dramatically reduce redundant computation using an adaptive slicing size. Specifically, ASAHI focuses on the number of slices rather than the slicing size, that is, it adaptively adjusts the slicing size to control the number of slices according to the image resolution. Additionally, we replace the standard non-maximum suppression technique with Cluster-DIoU-NMS due to its improved accuracy and inference speed in the post-processing stage. In extensive experiments, ASAHI achieves competitive performance on the VisDrone and xView datasets. The results show that the mAP50 is increased by 0.9% and the computation time is reduced by 20–25% compared with state-of-the-art slicing methods on the TPH-YOLOV5 pretrained model. On the VisDrone2019-DET-val dataset, our mAP50 result is 56.4% higher, demonstrating the superiority of our approach. [ABSTRACT FROM AUTHOR]

To clarify the effect of tillage methods on saline–alkali land improvement and maize growth in cropland salinized to different degrees, we set up two treatments (shallow rotation (15 cm depth; CK) and deep straw return (35 cm depth; DPR)) in land characterized by three different salinization degrees and analyzed the effects of the two treatments on soil nutrient content, salinity index, chlorophyll fluorescence, growth status, and yield at three salinization levels. The results show that (1) compared with CK, alkaline N, total N, Olsen P, exchangeable K, and organic matter in saline soils were all significantly improved, and total salt and pH values were reduced by 34.01–50.79% and 2.56–7.54%, respectively, under deep straw return conditions, representing the largest values in moderately saline–alkali land. (2) Compared with CK, chlorophyll fluorescence was significantly improved, and maximum photochemical efficiency (Fv/Fm), photochemical quenching (qP), and effective quantum yield of PSII (ΦPSII) were significantly increased by 8.09–15.41%, 9.13–17.93%, and 38.79–70.83% following deep straw return treatment; these increases were the largest ones observed in moderately saline–alkali land. (3) Deep straw return promoted the growth of maize and significantly increased the yield of maize. Plant height, leaf area index, and yield increased the most in moderately saline–alkali land and increased by 6.84–21.79%, 0.59–2.28 units, and 12.78–28.07%, respectively. The yield increased by 33.89 %, which was mainly due to the increase in 1000-grain weight. The results provide a theoretical basis for taking straw return measures to improve soil and increase maize yield in saline–alkali land. [ABSTRACT FROM AUTHOR]

In yeast, Atg22 functions as a vacuolar efflux transporter to release the nutrients from the vacuole to the cytosol after the degradation of autophagic bodies. There are more than one Atg22 domain-containing proteins in filamentous fungi, but their physiological roles are largely unknown. In this study, four Atg22-like proteins (BbAtg22A through D) were functionally characterized in the filamentous entomopathogenic fungus Beauveria bassiana. These Atg22-like proteins exhibit different sub-cellular distributions. BbAtg22A localizes in lipid droplets. BbAtg22B and BbAtg22C are completely distributed in the vacuole, and BbAtg22D has an additional association with the cytomembrane. The ablation of Atg22-like proteins did not block autophagy. Four Atg22-like proteins systematically contribute to the fungal response to starvation and virulence in B. bassiana. With the exception of ∆Bbatg22C, the other three proteins contribute to dimorphic transmission. Additionally, BbAtg22A and BbAtg22D are required for cytomembrane integrity. Meanwhile, four Atg22-like proteins contribute to conidiation. Therefore, Atg22-like proteins link distinct sub-cellular structures for the development and virulence in B. bassiana. Our findings provide a novel insight into the non-autophagic roles of autophagy-related genes in filamentous fungi. [ABSTRACT FROM AUTHOR]

The ablative properties of epoxy-modified vinyl silicone rubber (EMVSR) composites containing hexaphenoxycyclotriphosphonitrile (HPCTP) have been systematically studied. The strength of the ablation char layer was greatly enhanced with the addition of HPCTP, which induced the formation of a more complete, denser, and thicker char during oxyacetylene ablation tests. Moreover, the HPCTP-containing EMVSR composites demonstrated lower thermal conductivity and pyrolysis rate when compared with those without HPTCP. At the same time, the thermal insulation properties of HPCTP-filled composites were improved under low heat flow ablation scenarios. The reduction of graphitic carbon content, the formation of phosphate-like crystals as well as the increase of SiC content contributed to strengthening the char layer, which was critical for improving the ablation properties. The optimum char layer strength and thermal insulation properties were achieved when the content of HPCTP was 15 phr, whereas an optimum ablation resistance was achieved at 25 phr HPCTP. This suggests that HPCTP-modified EMVSR composites can be used for thermal protection purposes, especially in the fields of aerospace and aeronautics. [ABSTRACT FROM AUTHOR]

It is of great technological importance in the field of plasmonic color generation to establish and understand the relationship between optical responses and the reflectance of metallic nanoparticles. Previously, a series of indium nanoparticle ensembles were fabricated using electron beam evaporation and inspected using spectroscopic ellipsometry (SE). The multi-oscillator Lorentz–Drude model demonstrated the optical responses of indium nanoparticles with different sizes and size distributions. The reflectance spectra and colorimetry characteristics of indium nanoparticles with unimodal and bimodal size distributions were interpreted based on the SE analysis. The trends of reflectance spectra were explained by the transfer matrix method. The effects of optical constants n and k of indium on the reflectance were demonstrated by mapping the reflectance contour lines on the n-k plane. Using oscillator decomposition, the influence of different electron behaviors in various indium structures on the reflectance spectra was revealed intuitively. The contribution of each oscillator on the colorimetry characteristics, including hue, lightness and saturation, were determined and discussed from the reflectance spectral analysis. [ABSTRACT FROM AUTHOR]

Satellite image time series (SITS) classification is a challenging application concurrently driven by long-term, large-scale, and high spatial-resolution observations acquired by remote sensing satellites. The focus of current SITS classification research is to exploit the richness of temporal information in SITS data. In the literature, self-attention mechanism-based networks, which are capable of capturing global temporal attention, have achieved state-of-the-art results in SITS classification. However, these methods lack attention to local temporal information, which is also significant for SITS classification tasks. To explore the potential of different scales of temporal information in SITS data, a global–local temporal attention encoder (GL-TAE) is proposed in this paper. GL-TAE has two submodules set up in parallel, one of which is a lightweight temporal attention encoder (LTAE) for extracting global temporal attention and the other is lightweight convolution (LConv) for extracting local temporal attention. Compared with methods exploring global-only or local-only temporal features, the proposed GL-TAE can achieve better performance on two public SITS datasets, which proves the effectiveness of hybrid global–local temporal attention features. The experiments also demonstrate that GL-TAE is a lightweight model, which achieves the same performance as other models but with fewer parameters. [ABSTRACT FROM AUTHOR]

Simple Summary: In recent years, the shortage of cow stocks and the reduction of cow breeders in China have caused a shortage of cattle resources and a high price of calves, which has become a bottleneck restricting the further development of China's beef cattle industry. At present, there are few studies on the decision-making behavior of cow breeding in China. In order to explore the factors that affect the decision-making behavior on cow breeding by beef cattle farmers, this paper uses field survey data to make an empirical analysis through the Logit ISM model. The results show that the age of the breeder, the breeding year, the planting area of forage, market expectations, the loan amount, the breeding method policy publicity and policy subsidies are significant factors affecting the decision-making behavior of beef cattle farmers on cow breeding. The beef cattle industry is an important part of herbivorous animal husbandry and an important industry to enrich the dietary structure of residents and promote the income of farmers and herdsmen. The cow is an important foundation to support the healthy development of the beef cattle industry, which is related to the stability of cattle sources and the sustainable development of the industry. However, in recent years, the shortage of cows in our country has led to the shortage of cattle resources and the high price of calves, which has restricted the further development of our beef cattle industry. In order to explore the factors that affect the decision-making behavior behind cow breeding and to find the right policy to mobilize the enthusiasm for cow breeding, based on the field survey of five provinces (cities and regions), including Inner Mongolia Autonomous Region and Ningxia Hui Autonomous Region, this paper conducts an empirical analysis through the Logit ISM model. The results show that market expectation is the surface factor that directly affects the decision-making behavior of cow breeding. The influencing factors of the middle layer are policy propaganda, policy subsidies, breeding years, and feeding methods. The deep root factors are the age of the breeder, the amount of loan, and whether to plant feed crops. Based on this, this paper proposes that we should actively promote the importance of cow breeding, strengthen policy support for cow breeding, formulate scientific and reasonable subsidy policies for cows, innovate financial support methods to solve the problem of fund shortage of farmers, and develop forage resources and reduce the breeding cost of cows. [ABSTRACT FROM AUTHOR]

Given the complexity of the application scenarios of rolling bearing and the severe scarcity of fault samples, a solution to the issue of fault diagnosis under varying working conditions along with the absence of fault samples is required. A numerical model-driven cross-domain fault diagnosis method targeting variable working conditions is proposed based on the cross-Domain Nuisance Attribute Projection (cDNAP). Firstly, the simulation datasets consisting of multiple fault types under variable working conditions are constructed to solve the problem of incomplete fault samples. Secondly, the simulation datasets are expanded by means of generating adversarial network to ensure sufficient samples for subsequent model training. Finally, cDNAP is used to obtain the cross-domain simulation projection matrix, which eliminates the variance in the distribution of measured and simulated sample features under varying working conditions. The experimental results of cross-domain for variable working conditions show that the diagnostic accuracy reaches up to 99%. Compared with DANN, DSAN, and DAAN domain adversarial neural networks, the proposed method performs better in bearing fault diagnosis. [ABSTRACT FROM AUTHOR]

Proteomic profiling of extracellular vesicles (EVs) represents a promising approach for early detection and therapeutic monitoring of diseases such as cancer. The focus of this study was to apply robust EV isolation and subsequent data-independent acquisition mass spectrometry (DIA-MS) for urinary EV proteomics of prostate cancer and prostate inflammation patients. Urinary EVs were isolated by functionalized magnetic beads through chemical affinity on an automatic station, and EV proteins were analyzed by integrating three library-base analyses (Direct-DIA, GPF-DIA, and Fractionated DDA-base DIA) to improve the coverage and quantitation. We assessed the levels of urinary EV-associated proteins based on 40 samples consisting of 20 cases and 20 controls, where 18 EV proteins were identified to be differentiated in prostate cancer outcome, of which three (i.e., SERPINA3, LRG1, and SCGB3A1) were shown to be consistently upregulated. We also observed 6 out of the 18 (33%) EV proteins that had been developed as drug targets, while some of them showed protein-protein interactions. Moreover, the potential mechanistic pathways of 18 significantly different EV proteins were enriched in metabolic, immune, and inflammatory activities. These results showed consistency in an independent cohort with 20 participants. Using a random forest algorithm for classification assessment, including the identified EV proteins, we found that SERPINA3, LRG1, or SCGB3A1 add predictable value in addition to age, prostate size, body mass index (BMI), and prostate-specific antigen (PSA). In summary, the current study demonstrates a translational workflow to identify EV proteins as molecular markers to improve the clinical diagnosis of prostate cancer. [ABSTRACT FROM AUTHOR]

In order to accurately characterize and evaluate dust particle diffusion in the dynamic tunneling process of a boring machine, this study considers the 31,116 main transport chute heaving face of the Lijiahao coal mine as a case study. A dynamic tunneling model is developed considering the real dynamic tunneling state of the header, to carry out an in-depth analysis of the spatial and temporal evolution of wind flow and dust dispersion in the tunnel under dynamic excavation. In addition, the results were compared against the calculations of a static standard excavation model of a conventional header. Employing CFD analysis accompanied by field measurements, it was highlighted that the dynamic tunneling of the header leads to an increase in the pressure difference and the turbulent kinetic energy at the working face. Moreover, an increase in the number of vortices was reported, and a higher concentration of dust spreads more quickly along the return wind side wall to the return flow area. On the other hand, the high concentration of dust under the standard tunneling model was found to accumulate a lot on the return wind side. Simultaneously, as the distance between the pressurized air outlet and the working face increases, the average wind speed in the vortex-type wind flow area at the front of the tunnel decreases. When t = 60 s, the return flow area expands to a space of 8 m~24 m from the head, and the dust accumulated above the header spreads to the back of the header to form a high concentration dust region of more than 500 mg/m³. It was shown that the range of high-concentration dust clouds in the breathing zone decreases compared to the results of the standard tunneling model. Moreover, the dust concentration in the breathing zone of the driver is significantly lower than that reported by the standard tunneling model. Based on the results of the field test, the average error between the simulated and measured data of the dynamic tunneling model was calculated to be around 6.46%, thus demonstrating the model's capability in describing the real working conditions of the heave tunnel. [ABSTRACT FROM AUTHOR]