襄阳习池与凤林关景区建设初探

史料和历史遗存显示,襄阳习池园林景观"大陂""、小魚池"的布局位置分别位于现在的闫家冲内和闫家冲外以东的汉江边。习池历史建筑奉行"顺应自然,倡导俭约"的文化精神。应引进"整体性保护和复原""、修旧如旧,以求其真"的世界文化遗产保护的理念,保护开发好襄阳习池、谷隐寺与凤林关,形成凤林关景观廊道和荆襄古道旅游线上的旅游精品。

An Autonomous Electric Powered Tractor--Simulation of All Operations on a Swedish Dairy Farmagricultural m machinery. This s study investig gated the feasib bility of an au utonomous batte ery electric tra actor through simulation. The e

For a conventional agricultural tractor the main environmental effects origina ates from the usage phase, more specifically from the diesel use and exhausts. To decre ease the environ nmental effect, it is vital to find a substitute for fossil diesel as a fuel for agricultural machinery. This s study investig gated the feasib bility of an autonomous battery electric tractor through simulation. The simulated farm is an organic dairy farm of 200 ha with five crops in the crop rotation cycle and a traditional plough among the used implements. Based on the res sult from the simulation cost calculations, sensitivity analysi is and a limited life cycle analysis （LCA） was made. The results show that it is in theory possible to replace a conventional tractor （160 kW） with two autonomous battery powered machines （36 kW engine, 113 kWh battery） with 15% lower costs. Energy consumption would be red duced by 58% a and greenhouse gas emissions by 92% compared to diesel when energy consumption and greenhouse gas emissions from battery manufacturing were included. Today the technology for autonom mous control is under fast development, but there are yet no systems on the market that can handle all machinery tasks like assumed in this study. Challenges yet to solve are , among others, legislative, relevant sensors, logistics and fleet management. Further rese earch is needed to verify the results in practical farming.

Studies of community structure and seasonal dynamics of planktonic copepods in saline-alkaline ponds

Species abundance and seasonal succession of copepods in saline-alkaline ponds were studied in Zhaodian Fish Farm, Gaoqing County, Shandong Province, from 5 April 1997 to 1 September 1998. The results indicated that in the conditions of salinity ranging from 1.36 to 20 g/L, total alkalinity changing from 2.4 to 7.2 mmol/L and pH 8–9, zooplankton in saline-alkaline ponds was composed of freshwater salt-tolerated species or halophile species, some of which are halobiont species and usually occurs in freshwater. In our study, copepods were predominant in many fish-culture ponds and all control ponds without fishes in spring, late autumn and early winter. Dominant species of copepods were Sinocalanus tenellus, Cyclops vicinus, Thermocyclops taiho- kuensis. The biomass of copepods in the control ponds without fishes was higher than that of the fish-culture ponds.

Internal Loads and Bioavailability of Phosphorus and Nitrogen in Dianchi Lake,China

Sediments have a significant influence on the cycling of nutrient elements in lake environments. In order to assess the distribution characteristics and estimate the bioavailability of phosphorus and nitrogen in Dianchi Lake, organic and inorganic phosphorus and nitrogen forms were analysed. The 210 Pb radiometric dating method was employed to study temporal changes in the phosphorus and nitrogen pools in Dianchi Lake. The result show that the total phosphorus(TP) and total nitrogen(TN) were both at high concentrations, ranging from 697.5–3210.0 mg/kg and 1263.7–7155.2 mg/kg, respectively. Inorganic phosphorus(IP) and total organic nitrogen(TON) were the main constituents, at percentages of 59%–78% and 74%–95%, respectively, in the sediments. Spatially, there was a decreasing trend in phosphorus and nitrogen contents from the south and north to the lake centre, which is related to the distribution pattern of local economic production. The burial rates of the various phosphorus and nitrogen forms increased in same spatially and over time. Particularly in the past two decades, the burial rates doubled, with that TN reached to 1.287 mg/(cm^2·yr) in 2014. As the most reactive forms, nitrate nitrogen(NO_3-N) and ammonia nitrogen(NH_4-N) were buried more rapidly in the south region, implying that the potential for releasing sedimentary nitrogen increased from north to south. Based on their concentrations and burial rates, the internal loads of phosphorus and nitrogen were analysed for the last century. A TP pool of 71597.6 t and a TN pool of 81191.7 t were estimated for Dianchi Lake. Bioavailable phosphorus and nitrogen pools were also estimated at 44468.0 t and 5429.7 t, respectively, for the last century.

Iterative learning control of SOFC based on ARX identification model

This paper presents an application of iterative learning control (ILC) technique to the voltage control of solid oxide fuel cell (SOFC) stack. To meet the demands of the control system design, an autoregressive model with exogenous input (ARX) is established. Firstly, by regulating the variation of the hydrogen flow rate proportional to that of the current, the fuel utilization of the SOFC is kept within its admissible range. Then, based on the ARX model, three kinds of ILC controllers, i.e. P-, PI- and PD-type are designed to keep the voltage at a desired level. Simulation results demonstrate the potential of the ARX model applied to the control of the SOFC, and prove the excellence of the ILC controllers for the voltage control of the SOFC.

Identification and novel adaptive fuzzy control of nonlinear system for PEMFC stack

The operating temperature of a proton exchange membrane fuel cell stack is a very important control parameter. It should be controlled within a specific range, however, most of existing PEMFC mathematical models are too complicated to be effectively applied to on-line control. In this paper, input-output data and operating experiences will be used to establish PEMFC stack model and operating temperature control system. An adaptive learning algorithm and a nearest-neighbor clustering algorithm are applied to regulate the parameters and fuzzy rules so that the model and the control system are able to obtain higher accuracy. In the end, the simulation and the experimental results are presented and compared with traditional PID and fuzzy control algorithms.

Emotional Costs and Self-efficacy as Predictors of Coping Among the Reemployed and Professional Interns

The main goal of the study was to investigate the emotional costs experienced by the organizational newcomers during the first period of reemployment and its relation to general self-efficacy CGSE} and coping. The study was conducted among 123 previous unemployed, involving 88 reemployed and 35 interns. Questionnaires battery was administered in two waves {T1 and T2~ in the first month of reemployment and after three months. In this article, the data from T2 were analyzed, which allows observing the final results and interactions between research variables. The results showed emotional costs and GSE as significant predictors of coping in the work re-entry phase. Additionally, emotional costs partially mediate the effect of GSE on coping. The differences between both groups, the reemployed and interns were also analyzed.

Deep Learning Hybrid Model for Lithium-Ion Battery Aging Estimation and Prediction

The degradation process of lithium-ion batteries is intricately linked to their entire lifecycle as power sources and energy storage devices,encompassing aspects such as performance delivery and cycling utilization.Consequently,the accurate and expedient estimation or prediction of the aging state of lithium-ion batteries has garnered extensive attention.Nonetheless,prevailing research predominantly concentrates on either aging estimation or prediction,neglecting the dynamic fusion of both facets.This paper proposes a hybrid model for capacity aging estimation and prediction based on deep learning,wherein salient features highly pertinent to aging are extracted from charge and discharge relaxation processes.By amalgamating historical capacity decay data,the model dynamically furnishes estimations of the present capacity and forecasts of future capacity for lithium-ion batteries.Our approach is validated against a novel dataset involving charge and discharge cycles at varying rates.Specifically,under a charging condition of 0.25 C,a mean absolute percentage error(MAPE)of 0.29%is achieved.This outcome underscores the model's adeptness in harnessing relaxation processes commonly encountered in the real world and synergizing with historical capacity records within battery management systems(BMS),thereby affording estimations and prognostications of capacity decline with heightened precision.