We study the number of triangles $T_n$ in the sparse $\beta$-model on n vertices, a random graph model that captures degree heterogeneity in real-world networks. Using the norms of the heterogeneity parameter vector, we first determine the asymptotic mean and variance of $T_n$. Next, by applying the Malliavin–Stein method, we derive a non-asymptotic upper bound on the Kolmogorov distance between the normalized $T_n$ and the standard normal distribution. Under an additional assumption on degree heterogeneity, we further prove the asymptotic normality for $T_n$ as $n\to\infty$.

Isoproturon is widely used to control Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] in wheat (Triticum aestivum L.) fields across China. Here, we identified a highly resistant population (HR) from 87 populations collected from wheat fields; it showed 4.6-fold resistance to isoproturon compared with a susceptible control (HS). DNA sequencing of the full-length psbA gene revealed no sequence differences between HR and HS plants. However, psbA expression in the HR population was significantly higher than in the HS population, both before and after isoproturon application. Transgenic assays confirmed that psbA gene overexpression in rice (Oryza sativa L.) plants confers resistance to photosystem II (PSII) inhibitors, including isoproturon. Under isoproturon application, the HR population also demonstrated elevated antioxidant enzyme activities and maintained higher chlorophyll and carotenoid levels. Furthermore, the HR population remained susceptible to pyroxsulam and pinoxaden, suggesting that these herbicides are practical alternatives for control. These findings indicate that psbA gene overexpression contributes to isoproturon resistance in L. perenne ssp. multiflorum, likely through the overproduction of the D1 protein to mitigate herbicide-induced PSII dysfunction. Our study provides the first confirmation and mechanistic explanation of isoproturon resistance in L. perenne ssp. multiflorum, revealing psbA gene overexpression as the key driver.

The traditional design of laser drivers for inertial confinement fusion (ICF) is highly dependent on coherent laser light fields, which have significant advantages in achieving harmonic conversion and enhancing amplification efficiency. However, they also bring the core challenge of achieving uniform irradiation. This paper investigates the dynamic evolution process of uniform irradiation of multi-mode spatiotemporal light fields and analyzes the influence mechanism of spatiotemporal coherence on irradiation uniformity with different integration times. By balancing the relationship between the spatiotemporal coherence of the light field and uniform irradiation, we explore a possible scheme to alleviate the beam smoothing problem while satisfying the basic requirements of laser amplification and high-efficiency harmonic conversion. Based on this scheme, the overall architecture of the ICF laser driver is constructed.

To investigate how polymers influence energy transfer in three-dimensional turbulence, we conduct experiments in homogeneous bulk turbulence generated by a von Kármán swirling flow, using tomographic particle image velocimetry. A filtering approach is applied to the measured three-dimensional velocity fields to extract subgrid-scale (SGS) statistics, focusing on the filtered strain-rate tensor and SGS stress tensor. We find that polymer additives induce significant changes in the tensorial geometry: the strain-rate tensor shows a tendency towards an eigenvalue ratio of $1 : 0 : -1$, while the SGS stress tensor favours a $2 : -1 : -1$ configuration. The local energy flux – quantified by the inner product of the strain-rate and SGS stress tensors – is systematically suppressed by polymers and becomes increasingly intermittent. This suppression is linked to a reduced energy transfer efficiency, associated with the misalignment between the principal eigendirections of the two tensors. Anisotropic effects are also observed in the energy flux components, indicating that polymers affect vertical and horizontal energy transfer differently. Finally, the obtained SGS statistics allow for an a priori assessment of SGS models. Our results reveal that the nonlinear gradient model significantly outperforms the Smagorinsky model, particularly in polymer-laden turbulence. The diminished alignment between the strain-rate and SGS stress tensors may underlie the limitations of the Smagorinsky model, which assumes a scalar eddy-viscosity closure. These results provide new experimental insights into the SGS dynamics of polymeric turbulence and highlight the potential of nonlinear models for large-eddy simulations of viscoelastic flows.

To address the limitations of existing external pipeline inspection robots, including a narrow range of adaptable pipe diameters and difficulty traversing obstacles like cross-pipelines, a novel wheel-clamping robot capable of circumferential rotation was designed. The composite drive mechanism of the robot adopts a dual-slider multi-link mechanism to realize the rapid switching of the two motion modes of the robot axis: forward and circumferential rotation. Following clarification of the robotic mechanism and component dimensions, a geometric model of key points was established, determining an adaptable pipeline diameter range of 74–203 mm. The force analysis was carried out to analyze the working state of the robot axis forward and circumferential rotation, and the minimum driving torque required to complete the above two motions is 0.84 and 1.23 N·m, respectively. Finally, the robot prototype was made, and the experiments of the prototype running on the pipeline were carried out. The experimental results show that the average speed of the robot is 0.195 m/s when it is moving along the axis on the pipeline, and it stably navigates obstacles through circumferential rotation, smoothly crossing T-shaped pipelines of different diameters, which is adaptable to the complex pipeline working conditions.

Radio recombination line (RRL) maser is a useful tool to study massive star formation regions with ionised gas close to new born massive stars. Masers often show sharp line profiles and/or extreme narrow widths, and high brightness temperatures. However, RRL masers were rarely detected only in several sources. Here we report the detection of sharp line profiles of the RRL H29$\alpha$, which can be interpreted as maser candidates, in two sources within W49A, a mini-starburst region in our Galaxy. These observations, conducted with high resolution ($\sim0.03''$) using the Atacama Large Millimeter/sub-millimeter Array (ALMA), reveal high brightness temperatures up to $\sim$9 000 K for H29$\alpha$ emission in another two sources, which might also be regarded as maser candidates. Additionally, suggestions for efficiently identifying RRL maser candidates are also provided.

This study investigated effects of fermented feed from broccoli stems and leaves (FBSL) on the growth performance, gut microbiota and carcass quality of Jinhua pigs. A total of 36 Jinhua pigs (54.50 ± 1.76 kg) were divided into two groups: control group fed basal diet, FBSL group fed basal diet containing 10% FBSL. The results showed that compared with the CON group, the average daily weight gain, lean meat percentage, loin eye area, pork redness, myoglobin content and inosine monophosphate content in FBSL group were increased by 7.31%, 5.69%, 11.03%, 18.88%, 26.50% and 30.32%, respectively (P < 0.05). Compared to the CON groups, the three-point backfat thickness, and the drip loss were decreased in FBSL group by 14.37% and 18.84%, respectively (P < 0.05). In the dorsal subcutaneous fat, the mRNA expression levels of DGAT1, DGAT2, FADS1 and PPARG were significantly decreased (P < 0.05), while INSIG1, CPT1A and CPT2 were significantly increased (P < 0.05); the contents of acetic acid, propionic acid and butyric acid in colon were significantly increased (P < 0.05). High-throughput sequencing results indicated that at the phylum level, the relative abundance of Bacteroidetes in the FBSL group was significantly increased, while the relative abundance of Proteobacteria was decreased significantly (P < 0.05); at the genus level, the relative abundances of Lactobacillus, Prevotella-9 and Treponema were significantly increased, while Escherichia was decreased significantly (P < 0.05). Quantitative real-time PCR results showed that the relative abundances of Lactobacillus and Bifidobacterium were significantly increased, while Escherichia coli was decreased significantly (P < 0.05). Results suggest FBSL improves the growth performance and carcass quality of Jinhua pigs by optimizing gut microbiota structure, increasing the content of gut short-chain fatty acids, and affecting the expression of lipid metabolism-related genes.

Power scaling of neodymium (Nd)-doped single-frequency fiber lasers (SFFLs) operating at approximately 900 nm has been fundamentally constrained by dominant emission of approximately 1060 nm, with previous demonstrations limited to below 3 W. Here, we demonstrate a 910 nm single-mode Nd-doped SFFL system that achieves a record output power of over 30 W employing homemade Nd-doped silica fiber (NDF), while preserving exceptional 49 dB suppression of competing emission of approximately 1060 nm. The laser system originates from a distributed Bragg reflector single-frequency (SF) oscillator with 11 mW output power, which is subsequently amplified to 31.1 W through three polarization-maintaining (PM) amplification stages utilizing PM 10/125 μm NDF. To the best of our knowledge, this represents the highest power achieved for Nd-doped SFFLs in this spectral region. The output exhibits excellent beam quality (Mx2 = 1.03, My2 = 1.05) and narrow linewidth (10.2 kHz). These results validate that the homemade PM 10/125 μm NDF can be employed in intermediate and main amplifiers in all-fiber SF master oscillator power amplifier systems at approximately 900 nm.

Bemisia tabaci is one of the most important agricultural pests worldwide, and the combined application of multiple natural enemies such as predators and parasitoids can potentially control B. tabaci. The study examined whether the predator Orius similis and the parasitoid Encarsia formosa can synergistically control B. tabaci (crop: kidney bean). The greenhouse cage method was used to release O. similis and E. formosa alone or in combination in different ratios. The combined release of O. similis and E. formosa synergistically decreased the B. tabaci population when compared with O. similis or E. formosa alone. Additionally, O. similis + E. formosa decreased the number of E. formosa black pupae and adults in each crop stage. However, the niche overlap index of E. formosa with B. tabaci nymphs in the O. similis + E. formosa group was higher than in the E. formosa group. Grey correlation analysis revealed that the correlation degree between natural enemies and B. tabaci was the highest when the O. similis and E. formosa release ratio was 1:3. These findings indicate that the combined release of O. similis and E. formosa synergistically controlled B. tabaci with the release ratio 1:3 being optimal for field application.

In this paper, a novel series–parallel stable platform is proposed, and its kinematic and dynamic models are established. The relationship between the length, speed, and acceleration of rolling and pitching electric push rods is analyzed. The workspace of the series–parallel stable platform is determined, and the singularity and interference are analyzed. The state-machine-based control system of the stable platform is designed. An experimental environment of the principle of the real-time control system based on dSPACE was built. A position–speed double closed-loop experiment, simulating mounting carrier of the random signal tracking, and system comprehensive performance experiment were conducted to verify the accuracy of the kinematics and dynamics model of the series–parallel stable platform and the rationality and stability of the control system.

Sugar beet production demands sustainable intensification approaches to enhance both yield and quality. This study examined the effects of foliar nano-ammonium nitrate (NH4NO3) applications on five sugar beet cultivars – JAMPOL, BTS 9830, DEL 1135, ASEEL and Raspoly – over two growing seasons in Egypt’s Nile Delta, using a split-plot randomized complete block design. Three nano-NH4NO3 concentrations (0, 50 and 100 ppm) were sprayed twice each season to assess impacts on growth, yield and quality parameters. The results indicated limited influence of treatments on primary yield metrics; taproot yields remained unaffected across all cultivars and seasons. Nonetheless, the 50 ppm treatment preserved optimal sugar quality, with sucrose content reaching 19.4 %, compared to 18 % in the controls. Carotenoid levels increased by 12 % under the 100 ppm treatment, reflecting enhanced nutritional quality. Among cultivars, ASEEL yielded the best results with taproot outputs of 34 t/ha and sugar yields of 6.1 t/ha under optimal conditions, demonstrating significant cultivar-dependent variation. Multivariate analysis revealed distinct response patterns among cultivars and treatments, with three-way interactions (Season × Cultivar × Nanoparticle) affecting several traits. Clustering identified four trait groups and three treatment clusters, highlighting sugar beet’s complex response to nanoparticles. Economic analysis shows limited benefits, with no significant increase in taproot yield, despite a rise in secondary metabolites. While nano-NH4NO3 can modify biochemical parameters, the lack of yield improvements casts doubt on its economic feasibility. Cultivar choice primarily influences sugar beet performance, with environmental conditions also affecting treatment efficacy.

In the fields of meal-assisting robotics and human–robot interaction (HRI), real-time and accurate mouth pose estimation is critical for ensuring interaction safety and improving user experience. The complexity arises from the diverse opening degrees of mouths, variations in orientation, and external factors such as lighting conditions and occlusions, which pose significant challenges for real-time and accurate posture estimation of mouths. In response to the above-mentioned issues, this paper proposes a novel method for point cloud fitting and posture estimation of mouth opening degrees (FP-MODs). The proposed method leverages both RGB and depth images captured from a single viewpoint, integrating geometric modeling with advanced point cloud processing techniques to achieve robust and accurate mouth posture estimation. The innovation of this work lies in the hypothesis that different states of mouth openings can be effectively described by distinct geometric shapes: closed mouths are modeled by spatial quadratic surfaces, half-open mouths by spatial ellipses, and fully open mouths by spatial circles. Then, based on these hypotheses, we developed algorithms for fitting geometric models to point clouds obtained from mouth regions, respectively. Specifically, for the closed mouth state, we employ an algorithm based on least squares optimization to fit a spatial quadratic surface to the point cloud data. For the half-open or fully open mouth states, we combine inverse projection methods with least squares fitting to model the contour as a spatial ellipse and circle, respectively. Finally, to evaluate the effectiveness of the proposed FP-MODs method, extensive actual experiments were conducted under varying conditions, including different orientations and various types of mouths. The results demonstrate that the proposed FP-MODs method achieves high accuracy and robustness. This study can provide a theoretical foundation and technical support for improving HRI and food delivery safety in the field of robotics.