Displacement Evolution of Reverse-Dip Rock Slope Considering the Change of the Reservoir Level

This paper investigates the toppling deformation characteristics of the displacement evolution in different portions for a reverse-dip rock slope, through a case study of Xiaodongcao slope in Chongqing city, China. Firstly, the elevation, slope angle, and aspect were obtained by the field survey, and then they were adopted in the partitioning process related to geological and geometrical conditions by the ArcGIS packages. Secondly, the spatiotemporal cloud map of the displacement was obtained by discrete monitoring data of surface displacement of the slope. Finally, the topping deformation was determined by superposing the cloud map of the displacement and the geometrical partition, considering the change of the reservoir level. The main findings are summarized as follows: (1) the horizontal displacement is close to the total one, meaning that the slope topping deformation is mainly in the horizontal orientation.(2) In the front and middle edges of the slope, the horizontal displacement is pronounced, which increases with the increase of the reservoir level and vice versa. The vertical displacement mainly occurs in the trailing of the slope, which increases when the reservoir level changes. (3) The area in relation to the strong superposed displacement increases with the variation of the reservoir level. The largest area of superposed displacement is distributed at medium gradient, low elevation and north aspect zones.

Shoulder Muscular Fatigue From Static Posture Concurrently Reduces Cognitive Attentional Resources

Objective The goal of this work is to determine whether muscular fatigue concurrently reduces cognitive attentional resources in technical tasks for healthy adults. Background Muscular fatigue is common in the workplace but often dissociated with cognitive performance. A corpus of literature demonstrates a link between muscular fatigue and cognitive function, but few investigations demonstrate that the instigation of the former degrades the latter in a way that may affect technical task completion. For example, laparoscopic surgery increases muscular fatigue, which may risk attentional capacity reduction and undermine surgical outcomes. Method A total of 26 healthy participants completed a dual-task cognitive assessment of attentional resources while concurrently statically fatiguing their shoulder musculature until volitional failure, in a similar loading pattern observed in laparoscopic procedures. Continuous and discrete monitoring task performance was recorded to reflect attentional resources. Results Electromyography of the anterior deltoid and descending trapezius, as well as self-assessment surveys indicated fatigue occurrence; continuous tracking error, tracking velocity, and response time significantly increased with muscular fatigue. Conclusion Muscular fatigue concurrently degrades cognitive attentional resources. Application Complex tasks that rely on muscular and cognitive performance should consider interventions to reduce muscular fatigue to also preserve cognitive performance.

Study On Correlation Of Data From Yield Monitoring System And Hand Samples

One of the basic tools used in precision agriculture technology is yield monitoring and mapping. Yield maps are used to monitor the efficiency of applied inputs, to assess the variability of field and have potential to be used in farm records and farm management software. The paper deals with comparison of yield maps with information on yield obtained from hand sampling. Analyses are based on five-year data from one field with spring barley, oil seed rape, winter wheat and maize crop rotation. Results show that the correlation coefficient across the time period reached a value of 0.89 (p <0.05), which means that the yield maps show the yield trend of the field. However, looking at the data in more detail and comparing the pairs of data for selected (discrete) monitoring points, the error of estimation was calculated. This error showed that the yield monitor underestimated or overestimated the yield in average by 25 %. Therefore, the data cannot be used to evaluate the absolute yield at selected place of the field.

A Multivariable Grey Model and its Application to Subgrade Settlement Prediction

Subgrade settlement is a complex systematic process. Frequently used single point forecasting models can’t consider the correlation of settlement between the discrete monitoring points, so that it can’t represent the integrated deformation regularity of subgrade. For resolving this problem, this paper extends the single point GM(1,1) model into a multivariable grey model (MGM(1,n)), and completes the programming with MATLAB. Finally, A MGM(1,3) model is established to predict the subgrade settlement, and the result of the model is more precise and effective than the single point GM(1,1) model through a practical application.