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In atmospheric modeling, sub-grid parameterization is an important method for studying the topographic effects of solar radiation using high-resolution Digital Elevation Model (DEM) data. For reducing the amount of computation, some approximate methods that can lead to errors are used in existing sub-grid parameterization schemes for clear-sky direct solar radiation (SPS-CSDSR). The lack of a high-precision fast terrain occlusion algorithm (HPFTOA) remains one of the biggest constraints in this field. This study proposed an HPFTOA. It mainly uses two kinds of acceleration algorithms. One method is to use a dynamic, lossless, and fast occlusion search radius. Another way is to use the rectangular grid for calculations within the accuracy of DEM data to avoid coordinate projection conversions. The test results indicate that the HPFTOA can carry out large-scale computation based on DEM data with a resolution of 90 m. Because it rarely uses approximation algorithms and considers the curvature of the Earth, SPS-CSDSR can achieve unprecedented precision. The HPFTOA can also be used in the fields of mountain solar energy assessment, remote sensing, and telemetry, including terrain-obscuring the probe. As computer performance improves and algorithms and execution code are optimized, the application prospects will be very broad.

Existing sub-grid parameterization schemes for clear-sky direct solar radiation (SPS-CSDSR) assume that the sub-grid cells have the same atmospheric transparency. This study shows that in undulating terrain, significant errors can occur when the sub-grid is in turbid weather or partly above the cloud top. A correction factor was proposed. It can effectively eliminate errors under a cloudless sky and can reduce some errors when part of the sub-grid is above the cloud or fog top. For atmospheric models with high horizontal resolution, example test verification shows that the cast shadowless coverage method can lead to large errors. It should no longer be used based on current computing power. These improvements and the high-precision fast terrain occlusion algorithm in Part I will allow SPS-CSDSR to achieve unprecedented high accuracy. Based on the proposed daily interpolation method, the high-precision SPS-CSDSR is also feasible for regional climate simulation. The analysis pointed out that the sub-grid terrain radiative effect (STRE) is distributed over inclined surfaces with larger areas and at different heights. Existing methods of coupling STRE on one flat surface have certain physical drawbacks. This paper suggests introducing parameterization of STRE at different altitudes and improving the coupling of land–air.

The bacterial invasions and inflammatory responses after implant placement often affect osseointegration; the increased secretion of pro-inflammatory cytokines can lead to poor formation of bone and bone absorption. Previous research has shown that the antimicrobial peptide 6K-F17 has antibacterial and immunomodulatory properties. The objective of this study was to optimize KR−1 and KR−2, based on 6K-F17, to apply to the tissue around the oral implant. Our first objective is to study its antibacterial properties, and then we intend to further study its osteogenic ability to osteoblasts by modulating the immune response of macrophages. In this research, KR−1 and KR−2 can inhibit the formation of bacterial biofilm, and further kill bacteria S. gordonii and F. nucleatum by destroying the cell wall and cell membrane of bacteria. The novel peptides restrained the activation of the NF-κB signaling pathway by reducing the phosphorylation levels of IκBα and p65, inhibiting the degradation of IκBα and the nuclear translocation of p65, and increasing the percentage of M2 phenotype in macrophages. This suppressed the inflammatory response induced by lipopolysaccharides and enhanced the osteogenic activity of osteoblasts; this, in turn, promoted osteogenesis. The antimicrobial peptide KR−1 showed better performance. Our results demonstrate that KR−1 and KR−2 have antibacterial and bone immunomodulatory effects, and further promote osteogenesis by modulating the immune microenvironment, which provides the possibility for the adjuvant treatment of peri-implant diseases.

Peri-implantitis, an infectious disease originating from dental biofilm that forms around dental implants, which causes the loss of both osseointegration and bone tissue. KN-17, a truncated cecropin B peptide, demonstrated efficacy against certain bacterial strains associated with peri-implantitis. This study aimed to assess the antibacterial and anti-inflammatory properties and mechanisms of KN-17. The effects of KN-17 on oral pathogenic bacteria were assessed by measuring its minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Moreover, the cytotoxicity and anti-inflammatory effects of KN-17 were evaluated. KN-17 inhibited the growth of Streptococcus gordonii and Fusobacterium nucleatum during in vitro biofilm formation and possessed low toxicity to hBMSCs cells. KN-17 also caused RAW264.7 macrophages to transform from M1 to M2 by downregulating pro-inflammatory and upregulating anti-inflammatory factors. It inhibited the NF-κB signaling pathway by reducing IκBα and P65 protein phosphorylation while promoting IκBα degradation and nuclear P65 translocation. KN-17 might be an efficacious prophylaxis against peri-implant inflammation.

Three-phase unbalanced and nonlinear loads aggravate harmonic problems in low-voltage distribution networks. In this paper, a hybrid inductive and active filter (HIAF) system with a Ddy converter transformer is proposed. By establishing the circuit and corresponding mathematical models, the working mechanism of the HIAF system in harmonic suppression is analyzed. In the designed HIAF system, we install the detection point on the grid-side winding and the compensation point on the filtering winding. Since both windings have the same connection, no phase compensation between the harmonic detection point and compensation point is demanded. Eventually, we apply a harmonic damping control and zero-value impedance control strategy to realize harmonic suppression under both balanced and unbalanced loads. The simulation results show that the HIAF system can effectively suppress harmonics under various load conditions.

To improve the safety and reliability of robotic manipulators during high-speed precision movements, this paper proposes a method for smooth and time-optimal trajectory planning incorporating kinodynamic constraints. The primary objective is to use an evolutionary algorithm to determine a trajectory by considering time and jerk within the feasible path-pseudo-velocity phase plane region. Firstly, the path parameterization theory extracted the maximum pseudo-velocity projection curve from the kinodynamic constraints. Subsequently, the feasible region in the phase plane was defined through reachability analysis of discrete linear systems. Thereafter, we constructed the trajectory function using a cubic B-spline curve, optimizing its control points with an improved carnivorous plant optimization algorithm. Finally, the effectiveness and practicality of this method were verified through simulations on a 6-DOF manipulator.

To gain insights into the prevalence and antimicrobial resistance patterns of major bacterial pathogens affecting largemouth bass (Micropterus salmoides) in the Pearl River Delta (PRD) region, Guangdong, China, a study was conducted from August 2021 to July 2022. During this period, bacteria were isolated and identified from the internal organs of diseased largemouth bass within the PRD region. The antimicrobial resistance patterns of 11 antibiotics approved for use in aquaculture in China were analyzed in 80 strains of Edwardsiella piscicida using the microbroth dilution method. The results showed that 151 bacterial isolates were obtained from 532 samples, with E. piscicida (17.29%, 92/532), Aeromonas veronii (4.70%, 25/532), and Nocardia seriolae (2.26%, 12/532) being the main pathogens. Notably, E. piscicida accounted for the highest proportion of all isolated bacteria, reaching 60.92% (92/151), and mainly occurred from November to April, accounting for 68.48% (63/92) of the cases. The symptoms in largemouth bass infected with E. piscicida included ascites, enteritis, and hemorrhaging of tissues and organs. The drug sensitivity results showed that the resistance rates of all E. piscicida strains to ciprofloxacin, all sulfonamides, thiamphenicol, florfenicol, enrofloxacin, doxycycline, flumequine, and neomycin were 96.25%, 60–63%, 56.25%, 43.75%, 40%, 32.5%, 16.25%, and 1.25%, respectively. In addition, 76.25% (61/80) of these strains demonstrated resistance to more than two types of antibiotics. Cluster analysis revealed 23 antibiotic types (A–W) among the 80 isolates, which were clustered into two groups. Therefore, tailored antibiotic treatment based on regional antimicrobial resistance patterns is essential for effective disease management. The findings indicate that in the event of an Edwardsiella infection in largemouth bass, neomycin, doxycycline, and flumequine are viable treatment options. Alternatively, one may choose drugs that are effective as determined by clinical drug sensitivity testing.

The upper reaches of the Yellow River are critical ecological barriers within the Yellow River Basin (YRB) that are crucial for source conservation. However, environmental challenges in this area, from Longyangxia to Lijiaxia, have emerged in recent years. To assess the ecological environment quality (EEQ) evolution from 1991 to 2021, we utilized remote sensing ecological indices (RSEIs) on the Google Earth Engine (GEE) platform. Spatial autocorrelation and heterogeneity impacting EEQ changes were examined. The results of this study show that the mean value of the RSEIs fluctuated over time (1991: 0.70, 1996: 0.77, 2001: 0.67, 2006: 0.71, 2011: 0.68, 2016: 0.65, and 2021: 0.66) showing an upward, downward, and then upward trend. The mean values of the overall RSEI are all at 0.65 and above. Most regions showed no significant EEQ change during 1991–2021 (68.59%, 59.23%, and 55.78%, respectively). Global Moran’s I values (1991–2021) ranged from 0.627 to 0.412, indicating significant positive correlation between EEQ and spatial clustering, and the LISA clustering map (1991–2021) shows that the area near Longyangxia Reservoir shows a pattern of aggregation, dispersion, and then aggregation again. The factor detection results showed that heat was the most influential factor, and the interaction detection results showed that greenness and heat had a significant effect on regional ecosystem distribution. Our study integrates spatial autocorrelation and spatial heterogeneity and combines them with reality to provide an in-depth discussion and analysis of the Longyangxia to Lijiaxia Basin. These findings offer guidance for ecological governance, vegetation restoration, monitoring, and safeguarding the upper Yellow River’s ecological integrity.

The rapid mutation of SARS-CoV-2 has led to multiple rounds of large-scale breakthrough infection and reinfection worldwide. However, the dynamic changes of humoral and cellular immunity responses to several subvariants after infection remain unclear. In our study, a 6-month longitudinal immune response evaluation was conducted on 118 sera and 50 PBMC samples from 49 healthy individuals who experienced BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection. By studying antibody response, memory B cell, and IFN-γ secreting CD4+/CD8+ T cell response to several SARS-CoV-2 variants, we observed that each component of immune response exhibited distinct kinetics. Either BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection induces relatively high level of binding and neutralizing antibody titers against Omicron subvariants at an early time point, which rapidly decreases over time. Most of the individuals at 6 months post-breakthrough infection completely lost their neutralizing activities against BQ.1.1, CH.1.1, BA.2.86, JN.1 and XBB subvariants. Individuals with BA.5/BF.7-XBB reinfection exhibit immune imprinting shifting and recall pre-existing BA.5/BF.7 neutralization antibodies. In the BA.5 breakthrough infection group, the frequency of BA.5 and XBB.1.16-RBD specific memory B cells, resting memory B cells, and intermediate memory B cells gradually increased over time. On the other hand, the frequency of IFN-γ secreting CD4+/CD8+ T cells induced by WT/BA.5/XBB.1.16 spike trimer remains stable over time. Overall, our research indicates that individuals with breakthrough infection have rapidly declining antibody levels but have a relatively stable cellular immunity that can provide some degree of protection from future exposure to new antigens.

Legged agricultural transportation robots are efficient tools that can autonomously transport goods over agricultural terrain, and their introduction helps to improve the efficiency and quality of agricultural production. Their effectiveness depends on their adaptability to different environmental conditions, which is especially true for heavy-duty robots that exert ground forces. Therefore, this study proposes a motion-control strategy for a heavy-duty transport hexapod robot. Two critical tasks were accomplished in this paper: (1) estimating the support surface angle based on the robot’s foot position and body posture, and accordingly determining the motion constraint conditions on this support surface and the body posture based on energy optimization; (2) proposing an adaptive fuzzy impedance algorithm for real-time force–position composite control for adjusting foot position, in order to reduce the steady-state force tracking error caused by terrain stiffness, thus ensuring body stability through tracking of variable foot-end forces. An element of hardware in the loop control platform for a 3.55-ton device was designed and compared with the current popular force-control methods under different external contact terrains. The results show that the proposed control method can effectively reduce force errors, establish support forces faster on less-stiff environments, and reduce the torso tilt during phase switching.

The motion process of legged robots contains not only rigid-body motion but also flexible motion with elastic deformation of the legs, especially for heavy loads. Hence, the characteristics of the flexible components and their interactions with the rigid components need to be considered. In this paper, a hierarchical control strategy for robots with rigid–flexible coupling characteristics is proposed. This strategy involves (1) leg force prediction based on real-time motion trajectories and feedforward compensation for the error caused by flexible components; (2) building upon the centroid dynamics model of the rigid-body chassis, the centroid trajectories (centroid angular momentum (CAM) and centroid linear momentum (CLM)) and the body trajectory are taken into account to derive the optimal drive torque for maintaining body stability; (3) finally, the precise force control of the hydraulic drive units is achieved through the sliding mode control algorithm, integrating the dynamic model of the flexible legs. The proposed methods are validated on a giant hexapod robot weighing 3.5 tons, demonstrating that the introduced approach can reduce the robot’s vibrations.

Vibration harvesting is a promising method for walnut production owing to its low cost and high efficiency. However, current research focuses on simulation analysis and lacks a theoretical model explaining the walnuts’ specific vibration response. This affects the design of the input vibration parameters during harvesting and thus reduces the harvesting efficiency. In this paper, a novel theoretical model of walnuts during vibration harvesting was established to analyze the vibration response, including the motion morphology (motion trajectory and dropping position) and detachment force. A field test was then carried out to verify the theoretical model. The theoretical and experimental results showed that the motion trajectory of the walnuts during vibration harvesting is similar to an ellipse, and the dropping position is at either of the two end points of the trajectory. The detachment force was found to be proportional to the vibration amplitude and the square of the vibration frequency theoretically. This paper provides a theoretical reference for designing the optimal input vibration parameters of a harvesting device to improve the harvesting rate of walnuts.

To improve the obstacle avoidance ability of agricultural unmanned aerial vehicles (UAV) in farmland settings, a three-dimensional space path planning model based on the R5DOS model is proposed in this paper. The direction layer of the R5DOS intersection model is improved, and the RJA-star algorithm is constructed with the improved jump point search A-star algorithm in our paper. The R5DOS model is simulated in MATLAB. The simulation results show that this model can reduce the computational complexity, computation time, the number of corners and the maximum angles of the A-star algorithm. Compared with the traditional algorithm, the model can avoid obstacles effectively and reduce the reaction times of the UAV. The final fitting results show that compared with A-star algorithm, the RJA-star algorithm reduced the total distance by 2.53%, the computation time by 97.65%, the number of nodes by 99.96% and the number of corners by 96.08% with the maximum corners reduced by approximately 63.30%. Compared with the geometric A-star algorithm, the running time of the RJA-star algorithm is reduced by 95.84%, the number of nodes is reduced by 99.95%, and the number of turns is reduced by 67.28%. In general, the experimental results confirm the effectiveness and feasibility of RJA star algorithm in three-dimensional space obstacle avoidance.

In order to solve the problems of large amounts of calculation and long calculation times of the A-star algorithm in three-dimensional space, based on the R5DOS model, this paper proposes a three-dimensional space UAV path planning model. The improved R5DOS intersection model is combined with the improved A-star algorithm. Together, they construct a local search process, and the R5DOS path planning model is established by reducing the number of search nodes. The path planning model is simulated through MATLAB software and the model can greatly reduce the number of nodes and computational complexity of the A-star algorithm in three-dimensional spaces, while also reducing the calculation time of the UAV. Finally, we compare the improved A-star algorithm with the original A-star algorithm and the geometric A-star algorithm. The final fitting result proves that the improved A-star algorithm has a shorter computation time and fewer node visits. Overall, the simulation results confirm the effectiveness of the improved A-star algorithm and they can be used as a reference for future research on path planning algorithms.

The industrial sector dominates the global energy consumption and carbon emissions in end use sectors, and it faces challenges in emission reductions to reach the Paris Agreement goals. This paper analyzes and quantifies the relationship between industrialization, energy systems, and carbon emissions. Firstly, it forecasts the global and regional industrialization trends under Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway2 (SSP2) scenarios. Then, it projects the global and regional energy consumption that aligns with the industrialization trend, and optimizes the global energy supply system using the Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE) model for the industrial sector. Moreover, it develops an expanded Kaya identity to comprehensively investigate the drivers of industrial carbon emissions. In addition, it employs a Logarithmic Mean Divisia Index (LMDI) approach to track the historical contributions of various drivers of carbon emissions, as well as predictions into the future. This paper finds that economic development and population growth are the two largest drivers for historical industrial CO2 emissions, and that carbon intensity and industry energy intensity are the top two drivers for the decrease of future industrial CO2 emissions. Finally, it proposes three modes, i.e., clean supply, electrification, and energy efficiency for industrial emission reduction.