Search Results (29)

This study addresses the ’last-mile’ transportation challenges that arise in steep and narrow forest terrain by proposing a novel robotic palanquin system called roCaGo. It is inspired by the mechanical principles of two-wheel-steering and two-wheel-drive (2WS/2WD) bicycles. The roCaGo system integrates front- and rear-wheel-drive mechanisms, as well as a central suspension structure for carrying loads. Unlike conventional forestry machinery, which requires wide, well-maintained roads or permanent rail systems, the roCaGo system enables flexible, operator-assisted transport along narrow, unprepared mountain paths. A dynamic model of the system was developed to design a stabilization control strategy, enabling roCaGo to maintain transport stability and assist the operator during navigation. Numerical simulations and preliminary physical experiments demonstrate its effectiveness in challenging forest environments. Furthermore, the applicability of roCaGo has been extended to include use as a mobile third-person viewpoint platform to support the remote operation of existing forestry equipment; specifically the LV800crawler vehicle equipped with a front-mounted mulcher. Field tests involving LiDAR sensors mounted on roCaGo were conducted to verify its ability to capture the environmental data necessary for non-line-of-sight teleoperation. The results show that roCaGo is a promising solution for improving labor efficiency and ensuring operator safety in forest logistics and remote-controlled forestry operations. Full article

Trajectory tracking is a crucial task for autonomous mobile robots, requiring smooth and safe execution in dynamic environments. This study uses a nonlinear model predictive controller (MPC) to ensure accurate trajectory tracking of a four-wheel drive, four-wheel steer (4WD-4WS) mobile robot. However, the MPC’s performance depends on the optimal tuning of its key parameters, a challenge addressed using the Multivariate Gaussian Mixture Model Continuous Ant Colony Optimization (MGMM-${\mathrm{ACO}}_R$) algorithm. This method improves on the classic ${\mathrm{ACO}}_R$ algorithm by overcoming two major limitations: the lack of consideration for interdependencies between optimized variables, and an inadequate balance between global exploration and local exploitation. The proposed approach is validated by a two-phase evaluation. Firstly, benchmark function evaluations demonstrate its superiority over established optimization algorithms, including ACO, ${\mathrm{ACO}}_R$, and PSO and its variants, in terms of convergence speed and solution accuracy. Secondly, MGMM-${\mathrm{ACO}}_R$ is integrated into the MPC framework and tested in various scenarios, including trajectory tracking with circular and eight trajectories and dynamic obstacle avoidance during trajectory tracking. The results, evaluated based on trajectory error, control effort, and computational latency, confirm the robustness of the proposed method. In particular, the explicit modeling of correlations between variables in MGMM-${\mathrm{ACO}}_R$ guarantees stable, collision-free trajectory tracking, outperforming conventional ${\mathrm{ACO}}_R$-based approaches that optimize variables independently. Full article

To investigate the effects of different processing methods on the characteristic flavor of Undaria pinnatifida, this study systematically compared the volatile flavor compositions of four sample groups, namely fresh U. pinnatifida from Dalian (WD), salted U. pinnatifida from Dalian (WY), dried U. pinnatifida from Dalian (WG), and fresh U. pinnatifida from Shantou (WS), using GC-IMS, combined with relative odor activity value (ROAV) analysis. The results showed that GC-IMS effectively distinguished the volatile profiles of samples subjected to different processing methods, identifying a total of 45 flavor compounds. Aldehydes emerged as the key flavor components, accounting for relative contents of 53.85% (WD), 41.12% (WY), 52.62% (WG), and 45.28% (WS), which were significantly higher than those of other compound classes. The ROAV analysis revealed that 1-octen-3-ol and 1-octen-3-one were the characteristic compounds shared by all four sample groups. Furthermore, distinct processing methods influenced the distribution of saturated aldehydes, esters, and furans, which could serve as key indicators to distinguish between different processing techniques. Multidimensional analysis, including GC-IMS fingerprint visualization and principal component cluster analysis, confirmed significant flavor differences among the samples from different processing methods and origins. This study provides a theoretical basis for the quality control and standardized production of algal-based foods by multidimensionally analyzing flavor evolution in U. pinnatifida during processing. Full article

The Mongolian Plateau plays a crucial role in global carbon cycling, but the spatiotemporal characteristics of XCO₂ concentration and its driving mechanism remain insufficiently explored. To solve this scientific issue, the synergistic methodology of mathematical statistics—the Pearson correlation and random forest model—was established using the main source of Orbiting Carbon Observatory 2 (OCO-2) satellite data. Results indicate the following: (1) Average XCO₂ concentration of the Mongolian Plateau was 412 ppm, with an annual growth rate of 2.29 ppm/a from 2018 to 2022, along with higher values in the south and lower values in the north. The seasonal change displayed a clear temporal feature, in the order of spring (414.83 ppm) > winter (413.4 ppm) > autumn (411.3 ppm) > summer (409.12 ppm). The spatial distributions in spring, autumn, and winter were relatively consistent, all showing higher XCO₂ concentrations in the east and lower concentrations in the west, whereas summer exhibited the opposite pattern. (2) From the perspective of the natural environment, XCO₂ change was negatively correlated with the normalized difference vegetation index (NDVI), precipitation (PRE), and temperature (TEMP). Temporal analysis further revealed that this negative correlation was most pronounced in the eastern region, in which these three elements were all relatively high. (3) According to the random forest model, the influence of both single and interactive factors on the plateau’s XCO₂ varied significantly. A comparison of driving factors revealed that the NDVI had the highest contribution rate (0.35), followed by fossil fuel combustion emissions (ODIAC), wind direction (WD), and wind speed (WS). As for interaction effects, the combination of NDVI and ODIAC showed the highest contribution rate (over 0.25), indicating a strong joint influence on XCO₂. Other important interactions included WS and WD, ODIAC and WS, and NDVI and WS (all above 0.05). These findings provide valuable insights into the driving mechanisms of XCO₂ on the Mongolian Plateau, offering a reference for regional carbon emission reduction policies. Full article

The presence of oil slicks in the ocean presents significant environmental and regulatory challenges for offshore oil processing operations. During primary oil–water separation, produced water is discharged into the ocean, carrying residual oil, which is measured using the total oil and grease (TOG) method. The formation and spread of oil slicks are influenced by metoceanographic variables, including wind direction (WD), wind speed (WS), current direction (CD), current speed (CS), wind wave direction (WWD), and peak period (PP). In Brazil, regulatory limits impose sanctions on companies when oil slicks exceed 500 m in length, making accurate prediction of their occurrence and extent crucial for offshore operators. This study follows three main stages. First, the performance of five machine learning classification algorithms is evaluated, selecting the most efficient method based on performance metrics from a Brazilian company’s oil slick database. Second, the best-performing model is used to analyze the influence of metoceanographic variables and TOG levels on oil slick occurrence and detection probability. Finally, the third stage examines the extent of detected oil slicks to identify key contributing factors. The prediction results enhance decision-support frameworks, improving monitoring and mitigation strategies for offshore oil discharges. Full article

The soil microbiome plays an important role in wetland ecosystem services and functions. However, the impact of soil hydrological conditions on wetland microorganisms is not well understood. This study investigated the effects of wetted state (WS); wetting–drying state (WDS); and dried state (DS) on the diversity of soil bacteria, fungi, and archaea. The Shannon index of bacterial diversity was not significantly different in various flooding conditions (p > 0.05), however, fungal diversity and archaeal communities were significantly different in different flooding conditions (p < 0.05). Significant differences were found in the beta diversity of bacterial, fungal, and archaeal communities (p < 0.05). Additionally, the composition of bacteria, fungi, and archaea varied. Bacteria were predominantly composed of Proteobacteria and Actinobacteria, fungi mainly consisted of Ascomycota and Mucoromycota, and archaea were primarily represented by Crenarchaeota and Euryarchaeota. Bacteria exhibited correlations with vegetation coverage, fungi with plant diversity, and archaea with aboveground vegetation biomass. The pH influenced bacterial and archaeal communities, while soil bulk density, moisture, soil carbon, soil nitrogen, and plant community diversity impacted fungal communities. This study provides a scientific basis for understanding the effects of different hydrological conditions on microbial communities in the Huihe Nature Reserve; highlighting their relationship with vegetation and soil properties, and offers insights for the ecological protection of the Huihe wetland. Full article

This study performs idealized simulations of rainfall in Taiwan in a winter monsoon regime under different wind direction (W_d; every 15° from 0° to 90°), speed (W_s; 12, 8, and 4 m s⁻¹), and relative humidity (RH; 80, 70, and 60%) combinations at low levels, based on a simplified mean sounding profile from observations during the event over 20–24 November 2020. Thus, at a horizontal grid size of 2 km, a total of 7 × 3 × 3 = 63 runs are performed and the aim is to investigate the response in daily rainfall in northern Taiwan to these three parameters. The model results from the closest combination are verified against the observed rainfall both during the reference event and in several historical cases with reasonable agreement, indicating the usefulness of the approach, albeit with some limitations. From the experiments, our main findings can be summarized as below. First and foremost, with W_s = 12 m s⁻¹ and RH = 80%, when the prescribed W_d changes from 0° (northerly) to 90° (easterly) gradually, the main rainfall areas shift from northern to northeastern Taiwan, with local maxima at the northern tip, northeastern tip of Taiwan, and near Suao (at the end of the Central Mountain Range) in response, indicating topographic uplifting for rainfall production. At a larger impinging angle, the Suao area tends to receive the most daily rainfall and can exceed 300 mm at W_d of about 75°–80°. Second, when W_s decreases to 8 m s⁻¹, the general rainfall regions often remain similar but the amounts become lower, especially at local maxima. The peak amount near Suao is only about 100 mm. At weak wind of W_s = 4 m s⁻¹, only moderate rainfall of 20 mm or below can be produced in Taiwan, and the local centers become not discernable. Third, when RH is lowered, the rainfall in northern Taiwan decreases significantly, especially along and near the coast under weaker winds coming from smaller angles. At RH = 70%, a higher accumulation (≥100 mm or so) near Suao is only possible with W_d ≥ about 55° at W_s = 12 m s⁻¹ or when W_d ≥ 70° at W_s = 8 m s⁻¹. At RH = 60%, the rainfall in northern Taiwan (and on the entire island) further decreases, again more evidently in cases with smaller W_d and W_s values. Full article

Offshore wind power resources in the Red Sea waters of Saudi Arabia are yet to be explored. The objective of the present study is to assess offshore wind power resources at 49 locations in the Saudi waters of the Red Sea and prioritize the sites based on wind characteristics. To accomplish the set objective, long-term hourly mean wind speed (WS) and wind direction (WD) at 100 m above mean sea level, temperature, and pressure data near the surface were used at sites L1-L49 over 43 years from 1979 to 2021. The long-term mean WS and wind power density (WPD) varied between 3.83 m/s and 66.6 W/m², and 6.39 m/s and 280.9 W/m² corresponding to sites L44 and L8. However, higher magnitudes of WS >5 m/s were observed at 34 sites and WPD of > 200 W/m² at 21 sites. In general, WS, WPD, annual energy yield, mean windy site identifier, plant capacity factor, etc. were found to be increasing from east to west and from south to north. Similarly, the mean wind variability index and cost of energy were observed to be decreasing as one moves from east to west and south to north in the Saudi waters of the Red Sea. Full article

The Czech Republic has diverse soil conditions, which cause notable differences in crop water balance (WB). To assess the long-term crop WB and crop water stress (CWS) intensity in rainfed conditions, four conventional eight- and ten-year crop rotations (CRs) with perennial forage (alfalfa), cereals, oilseeds, root crops and legumes were proposed for a heterogeneous lowland soil region (six texture classes) in eastern Bohemia. Two of the CRs were selected irrespective of the WB (eight-year, C-8; ten-year, C-10), and the other two were designated according to soil water resources and crop water requirements (CWRs) as water-saving (W-S) and water-demanding (W-D) for this region. All CRs had a negative WB on average (i.e., CWRs exceeded the available water resources), with varying degrees of CWS (categories 1 (low) to 4 (high)). The W-S CR reduced the WB deficit relative to the other CRs by omitting maize, sunflower and sugar beet and including sorghum, and expanded the proportion of the area not affected by CWS (categories 1–2) to 33% for predominantly loamy soils. In contrast, categories 1–2 in the C-8, C-10 and W-D CRs represented only 15%, 14% and 7% of the area, respectively. Other areas were significantly affected by CWS (categories 3–4) and showed a high risk of yield reduction. These results may help in implementing sustainable farming systems that consider environmental perspectives related to agricultural water use in Central Europe. Full article

The effects of face immersion and concurrent exercise on the diving reflex evoked by breath-hold (BH) differ, yet little is known about the combined effects of different BH conditions on aerobic fitness in elite athletes. This study aimed to assess the acute effects of various BH conditions on 18 male elite rugby players (age: 23.5 ± 1.8 years; height: 183.3 ± 3.4 cm; body mass: 84.8 ± 8.5 kg) and identify the BH condition eliciting the greatest aerobic fitness activation. Participants underwent five warm-up conditions: baseline regular breathing, dynamic dry BH (DD), static dry BH (SD), wet dynamic BH (WD), and wet static BH (WS). Significant differences (p < 0.05) were found in red blood cells (RBCs), red blood cell volume (RGB), and hematocrit (HCT) pre- and post-warm-up. Peak oxygen uptake (VO₂peak) and relative oxygen uptake (VO₂/kgpeak) varied significantly across conditions, with BH groups showing notably higher values than the regular breathing group (p < 0.05). Interaction effects of facial immersion and movement conditions were significant for VO₂peak, VO₂/kgpeak, and the cardiopulmonary optimal point (p < 0.05). Specifically, VO₂peak and peak stroke volume (SVpeak) were significantly higher in the DD group compared to that in other conditions. Increases in VO₂peak were strongly correlated with changes in RBCs and HCT induced by DD warm-up (r∆RBC = 0.84, r∆HCT = 0.77, p < 0.01). In conclusion, DD BH warm-up appears to optimize subsequent aerobic performance in elite athletes. Full article

Large-scale mortality events have occurred during the winter in Atlantic salmon sea cages in Eastern Canada and Iceland. Thus, in salmon held at 3 °C that were apparently healthy (i.e., asymptomatic) and that had ‘early’ and ‘advanced’ symptoms of ‘winter syndrome’/’winter disease’ (WS/WD), we measured hepatic lipid classes and fatty acid levels, and the transcript expression of 34 molecular markers of fatty liver disease (FLD; a clinical sign of WS/WD). In addition, we correlated our results with previously reported characteristics associated with this disease’s progression in these same individuals. Total lipid and triacylglycerol (TAG) levels increased by ~50%, and the expression of 32 of the 34 genes was dysregulated, in fish with symptoms of FLD. TAG was positively correlated with markers of inflammation (5loxa, saa5), hepatosomatic index (HSI), and plasma aspartate aminotransferase levels, but negatively correlated with genes related to lipid metabolism (elovl5b, fabp3a, cd36c), oxidative stress (catc), and growth (igf1). Multivariate analyses clearly showed that the three groups of fish were different, and that saa5 was the largest contributor to differences. Our results provide a number of biomarkers for FLD in salmon, and very strong evidence that prolonged cold exposure can trigger FLD in this ecologically and economically important species. Full article

In the context of green and low-carbon development, energy saving, and emission reduction, hot recycling technology (RT) has been researched, which is divided into hot central plant RT and hot in-place RT. However, due to the aged asphalt binders, the shortcomings of hot recycled asphalt mixtures have become apparent, as in comparison to new asphalt mixtures, their resistance to cracking was inferior and the cracking resistance deteriorated more rapidly. Therefore, it was very necessary to focus on the improvement of crack resistance of hot recycled asphalt mixtures. Basalt fiber has been proved to be able to effectively improve the comprehensive road performance of new asphalt mixtures. Therefore, this paper introduced basalt fiber to hot central plant recycled and hot in-place recycled asphalt mixtures, in order to improve the crack resistance of asphalt as a new type of fiber stabilizer. Firstly, six types of SMA-13 fiber asphalt mixtures were designed and prepared, i.e., hot mixtures with basalt fiber or lignin fiber, hot central plant recycled mixtures with basalt fiber or lignin fiber, and hot in-place recycled mixtures with basalt fiber or lignin fiber. Secondly, the trabecular bending test, low-temperature creep test, semi-circular bending test, and IDEAL-CT were used to comparatively study the changing patterns of low and intermediate temperature cracking resistance of hot recycled mixtures with conventional lignin fibers or basalt fibers. Finally, Pearson’s correlation coefficient was used to analyze the correlation of the different cracking resistance indicators. The results show that the low and intermediate temperature cracking resistance of hot central plant recycled mixtures increased by 45.6% (dissipative energy ratio, W_d/W_s) and 74.8% (flexibility index, FI), respectively. And the corresponding cracking resistance of hot in-place recycled mixture increased by 105.4% (W_d/W_s) and 55.7% (FI). The trabecular bending test was more suitable for testing the low-temperature cracking resistance of hot recycled asphalt mixtures, while the IDEAL-CT was more suitable for testing the intermediate-temperature cracking resistance. The results can provide useful references for the utilization of basalt fiber in the hot recycling of SMA-13 asphalt mixtures. Full article

Water deficit and soil salinization are the primary abiotic stress factors hindering maize growth. To assess the effect of water and salt stress on xylem embolism in maize and investigate the relationship between drought resistance and xylem vulnerability, a greenhouse experiment was designed using two maize cultivars, Zhengdan 958 (drought-resistant) and Denghai 605 (drought-sensitive). Four treatments were included: control (CK), water deficit (WD), salt stress (SS), and combined water and salt stress (WS). Various hydraulic characteristic indicators, such as stem xylem water potential, leaf xylem water potential, the specific hydraulic conductivity ($K_s$) and percentage loss of conductivity (PLC), were analyzed. Specific hydraulic conductivity curves and vulnerability curves were constructed, and the hydraulic safety margin (HSM) of the xylem was determined based on stomatal conductance ($G_s$). The results indicated that the hydraulic conductivity and embolism resistance of maize xylem were not correlated. Compared to Denghai 605, Zhengdan 958 had lower maximum specific hydraulic conductivity $K_{\mathrm{s}\mathrm{m}\mathrm{a}\mathrm{x}}$ and $P_{50}$ values (xylem water potential at 50% PLC) in all treatments, indicating lower water transport capacity but stronger resistance to embolism. Under single-cultivar conditions, salt stress had a greater inhibitory effect on $K_{\mathrm{s}\mathrm{m}\mathrm{a}\mathrm{x}}$ and HSM in maize xylem compared to water deficit; thus, more severe embolism was found under salt stress. Under different treatment conditions, Zhengdan 958 had a larger HSM than Denghai 605, showing a wider water transport safety range and overall superior water transport security. To summarize, water and salt stress inhibited the water transport efficiency of the xylem in maize stems, and stronger drought-resistant cultivars showed greater resistance to embolism and larger hydraulic safety margins. Full article

Advanced driving algorithms, control strategies, and their optimization in self-driving vehicles in various scenarios are hotspots in current research; 4WS-4WD (four-wheel steering and four-wheel drive) is another hotspot in the study of new concept models; and the nonlinear dynamic characteristics of self-driving vehicles (AVs) are prominent in the fast cornering mode, which leads to a significant reduction in the accuracy and stability of trajectory tracking. Based on these research backgrounds, this paper proposes a control strategy optimization idea based on the 4WS4WD vehicle and its optimization model. The main content includes the establishment of a 3D vehicle model that takes into account vehicle load transfer and position change, and the establishment of a hierarchical control strategy based on the optimized NMPC and 4WS4WD models. The controller consists of two parts: an upper tracking controller based on the new vehicle model and NMPC, and a lower decoupled controller. The tracking control effect of the algorithmic control strategy based on the model and controller is validated in the high-speed serpentine motion mode and double-shift linear motion mode on the joint simulation platform of Car Sim and Simulink. Full article

The Christiansen Uniformity Coefficient (CUC) describes the distribution of water in a sprinkler system. In this study, two types of models were developed to predict the Christiansen Uniformity Coefficient (CUC) of sprinkler irrigation systems: Artificial Neural Network (ANN), specifically the feed-forward neural networks, and multiple linear regression (MLR) models. The models were trained on a dataset of published research on the CUC of sprinkler irrigation systems, which included data on a variety of design, operating, and meteorological condition variables. In order to build the predictive model of CUC, 10 input parameters were used including sprinkler height (H), working pressure (P), nozzle diameter (D and d_a), sprinkler line spacing (S_L), sprinkler spacing (S_S), wind speed (WS), wind direction (WD), temperature (T), and relative humidity (RH). Fifty percent (50%) of the data was used to train ANN models and the remaining data for cross-validation (25%) and for testing (25%). Multiple linear regression models were built using the training data. Four statistical criteria were used to evaluate the model’s predictive quality: the correlation coefficient (R), the index of agreement (d), the root mean square error (RMSE), and the mean absolute error (MAE). Statistical analysis demonstrated that the best predictive ability was obtained when the models (ANN and MLR) utilized all the input variables. The results demonstrated that the accuracy of ANN models, predicting the CUC of sprinkler irrigation systems, is higher than that of the MLR ones. During the training stage, the ANN models were more accurate in predicting CUC than MLR, with higher R (0.999) and d (0.999) values and lower MAE (0.167) and RMSE (0.456) values. The R values of the MLR model fluctuated between 0.226 and 0.960, the d values oscillated from 0.174 to 0.979, the MAE values were in the range of 2.458% and 10.792%, and the RMSE values fluctuated from 2.923% to 13.393%. Furthermore, the study revealed that WS and WD are the most influential climatic parameters. The ANN model can be used to develop more accurate tools for predicting the CUC of sprinkler irrigation systems. This can help farmers to design and operate their irrigation systems more efficiently, which can save them time and money. Full article