Search Results (5)

Grassland degradation is a serious ecological issue in the farming–pastoral ecotone of northern China. Utilizing native grasses for the restoration of degraded grasslands is an effective technological approach. Leymus secalinus is a superior indigenous grass species for grassland ecological restoration in northern China. Therefore, the excavation of potential distribution areas of L. secalinus and important ecological factors affecting its distribution is crucial for grassland conservation and restoration of degraded grasslands. Based on 357 data points collected on the natural distribution of L. secalinus, this study employs the jackknife method and Pearson correlation analysis to screen out 23 variables affecting its spatial distribution. The MaxEnt model was used herein to predict the current suitable distribution area of L. secalinus and the suitable distribution of L. secalinus under different SSP scenarios (SSP1-26, SSP2-45, and SSP5-85) for future climate. The results showed the following: (1) Mean diurnal temperature range, annual mean temperature, precipitation of the wettest quarter, and elevation are the major factors impacting the distribution of L. secalinus. (2) Under the current climatic conditions, L. secalinus is mainly distributed in the farming–pastoral ecotone of northern China; in addition, certain suitable areas also exist in parts of Xinjiang, Tibet, Sichuan, Heilongjiang, and Jilin. (3) Under future climate change scenarios, the suitable areas for L. secalinus are generally the same as at present, with slight changes in area under different scenarios, with the largest expansion of 97,222 km² of suitable area in 2021–2040 under the SSP1-26 scenario and the largest shrinkage of potential suitable area in 2061–2080 under the SSP2-45 scenario, with 87,983 km². Notably, the northern boundary of the middle- and high-suitability areas is reduced, while the northeastern boundary and some areas of Heilongjiang and Jilin are expanded. The results of this study revealed the suitable climatic conditions and potential distribution range of L. secalinus, which can provide a reference for the conservation, introduction, and cultivation of L. secalinus in new ecological zones, avoiding the blind introduction of inappropriate habitats, and is also crucial for sustaining the economic benefits associated with L. secalinus ecological services. Full article

Jackknifing refers to the serious situation where a vehicle-trailer system enters a jackknife state and the vehicle and trailer eventually collide if trailer operation is not corrected. This paper considers low speed trailer maneuvering typical of trailer backing. Jackknife state limits can vary due to sideslip caused by physical interaction between the vehicle, trailer, and environment. Analysis of a kinematic model considers sideslip at the vehicle and trailer wheels. Results indicate that vehicle-trailer systems should be divided into three categories based on the ratio of hitch length and trailer tongue length, each with distinct behaviors. The Long Trailer category may have no jackknifing state while the other two categories always have states leading to jackknifing. It is found that jackknife limits, which are the boundaries between the jackknifing state and the recoverable regions, can be divided into safe and unsafe limits. The latter of which must be avoided. Simulations and physical experiments support these results and provide insight about the implications of vehicle and trailer states with slip that lead to jackknifing. Simulations also demonstrate the benefit of considering these new slip-based jackknife limits in trailer backing control. Full article

Low-flow quantiles at ungauged locations are generally estimated based on hydrological methods, such as the drainage area ratio and frequency analysis methods. In practice, the drainage area ratio approach is a popular but simple linear model. When hydrologically nonlinear characteristics govern the runoff process, the linear approach leads to significant bias. This study was conducted to develop an improved nonlinear approach using a canonical correlation analysis and neural network (CCA-NN)-based regional frequency analysis (RFA) for low-flow estimation. The jackknife technique was utilized to validate the two methods. The approaches were applied to 33 river basins in South Korea. In this work, we focused on two-year and five-year return periods. For the two-year return period, the BIAS, RMSE, and R² were 0.013, 0.511, and 0.408 with the RFA, respectively, and −0.042, 1.042, and 0.114 with the drainage area ratio method, respectively; whereas for the five-year return period, the respective indices were −0.018, 0.316, and 0.573 with RFA, respectively, and 0.166, 0.536, and 0.044 with the drainage area ratio method, respectively. RFA outperformed the drainage area ratio method based on its high prediction accuracy and ability to avoid the bias problem. This study indicates that machine learning-based nonlinear techniques have the potential for use in estimating reliable low-flows at ungauged sites. Full article

Voltage-gated K⁺ channel (VKC) plays important roles in biology procession, especially in nervous system. Different subfamilies of VKCs have different biological functions. Thus, knowing VKCs’ subfamilies has become a meaningful job because it can guide the direction for the disease diagnosis and drug design. However, the traditional wet-experimental methods were costly and time-consuming. It is highly desirable to develop an effective and powerful computational tool for identifying different subfamilies of VKCs. In this study, a predictor, called iVKC-OTC, has been developed by incorporating the optimized tripeptide composition (OTC) generated by feature selection technique into the general form of pseudo-amino acid composition to identify six subfamilies of VKCs. One of the remarkable advantages of introducing the optimized tripeptide composition is being able to avoid the notorious dimension disaster or over fitting problems in statistical predictions. It was observed on a benchmark dataset, by using a jackknife test, that the overall accuracy achieved by iVKC-OTC reaches to 96.77% in identifying the six subfamilies of VKCs, indicating that the new predictor is promising or at least may become a complementary tool to the existing methods in this area. It has not escaped our notice that the optimized tripeptide composition can also be used to investigate other protein classification problems. Full article

Driving vehicles with one or more passive trailers has difficulties in both forward and backward motion due to inter-unit collisions, jackknife, and lack of visibility. Consequently, advanced driver assistance systems (ADAS) for multi-trailer combinations can be beneficial to accident avoidance as well as to driver comfort. The ADAS proposed in this paper aims to prevent unsafe steering commands by means of a haptic handwheel. Furthermore, when driving in reverse, the steering-wheel and pedals can be used as if the vehicle was driven from the back of the last trailer with visual aid from a rear-view camera. This solution, which can be implemented in drive-by-wire vehicles with hitch angle sensors, profits from two methods previously developed by the authors: safe steering by applying a curvature limitation to the leading unit, and a virtual tractor concept for backward motion that includes the complex case of set-point propagation through on-axle hitches. The paper addresses system requirements and provides implementation details to tele-operate two different off- and on-axle combinations of a tracked mobile robot pulling and pushing two dissimilar trailers. Full article