中美草原区露天煤矿土地复垦技术对比案例研究

中国露天煤矿多处于生态环境脆弱区,煤炭开采不可避免导致矿区生态环境的进一步恶化,草原区露天煤矿土地复垦已成为焦点。以美国的北安特洛浦/罗切尔矿区和中国内蒙古某露天煤矿为代表,系统对比两国草原区露天煤矿土地复垦在地貌重塑、土壤重构、植被重建等过程中的主要技术措施。研究发现,中国较美国在露天煤矿土地复垦技术上存在一定差异,美国比较注重近似原始地形的地貌重塑、本土植物的调查与保护、土地复垦后期的监测管护。研究认为,中国在草原区露天煤矿土地复垦过程中应该注重地貌重塑的区域协调性、提倡本土植物的利用和种植、减少抚育管理工作量、强化土地复垦后期监管,以保障矿区土地可持续利用。     

A new method to extract gate coupling ratio and oxide trapped charge in flash memory cell

A new method to obtain the gate coupling ratio (α_g) and oxide trapped charge (Q_ox) as a result of cycling in flash memory cells is described here. Three cells with an equivalent physical structure but different erase characteristics are measured. The threshold changes versus erase times are fitted to the charge removal rate calculated based on Fowler-Nordheim (FN) tunneling and the capacitive relations among all nodes. The extracted α_g is independent of technologies and this method is particular useful when the profile of the floating gate is not traditionally rectangular owing to advanced processes such as trapezoidal poly etch or a poly-spacer addition on the floating gate sidewall. The Q_ox can also be determined once α_g is extracted.     

Wound care pain management

Undertreatment of all types of acute and chronic pain is common, both in the United States and around the world. Moreover, a literature review of pressure ulcer pain and its management suggests that this area of pain medicine is truly in its infancy. This article includes a discussion of current literature, anatomy and physiology of pain related to pressure and ischemic ulcers and assessment methods. It also describes treatment modalities, including conservative measures, medication management and invasive procedures. Special emphasis is placed on the use of opioid analgesics in the management of severe acute and chronic wound pain.     

A shell of an onboard online advisory expert system for typical flight situation “Introduction of a group into an air fight”

The following knowledge base is presented: a hierarchical two-level knowledge base of onboard online advisory expert system for the subject area “Introduction of a group into an air fight”, in which mechanisms of inference mechanisms by precedent and multicriteria choice are used along with production rules. Examples of partial filling the knowledge base for the general problem “Patrol Escort of Strike Air Forces” are given.     

Calibration of SWAT models using the cloud

This paper evaluates a recently created Soil and Water Assessment Tool (SWAT) calibration tool built using the Windows Azure Cloud environment and a parallel version of the Dynamically Dimensioned Search (DDS) calibration method modified to run in Azure. The calibration tool was tested for six model scenarios constructed for three watersheds of increasing size each for a 2 year and 10 year simulation duration. Results show significant speedup in calibration time and, for up to 64 cores, minimal losses in speedup for all watershed sizes and simulation durations. An empirical relationship is presented for estimating the time needed to calibration a SWAT model using the cloud calibration tool as a function of the number of Hydrologic Response Units (HRUs), time steps, and cores used for the calibration.     

Using digital terrain analysis modeling techniques for the parameterization of a hydrologic model

This paper discusses the application of digital terrain analysis modeling techniques to the parameterization of a semi-distributed hydrologic model. Most current techniques for deriving physiographic parameters in watershed analyses, including those using commercial geographic information systems (GIS), are tedious, costly and time consuming. The demands of these techniques result in them usually being limited in practical application to deriving parameters at only one level of detail or for only one set of sub-basins. This paper presents a computerized interface (SLURPAZ) that was developed to combine the output of an established digital terrain analysis model (TOPAZ) with digital land cover data to derive all the necessary physiographic parameters required as input by a widely used semi-distributed hydrological model (SLURP). This interface makes it possible to derive physiographic parameters rapidly and accurately, at several different levels of detail and for varying numbers of sub-basins. This paper describes the methods by which the SLURPAZ interface integrates land cover data with the topographic parameters derived by TOPAZ from a digital elevation model (DEM). It also presents an example application of the interface to an intermediate-sized alpine basin in Yukon, Canada. Hydrological model outputs obtained using the computerized interface are compared with those obtained using manual techniques.     

Finance infrastructure through blockchain-based tokenization

The infrastructure finance gap has long-standing implications for economic and social development. Owing to low efficiency, high transaction costs, and long transaction time, conventional infrastructure financing instruments are considered to be major contributors to the increasing mismatch between the need for infrastructure development and available financing. Implemented through smart contracts, blockchain tokenization has shown characteristics that are poised to change the capital stack of infrastructure investment. This study analyzed the first SEC-compliant energy asset security token, ZiyenCoin, from the perspective of the key participants, relevant regulations, and token offering procedures. Results show that tokenization can improve infrastructure assets liquidity, transaction efficiency, and transparency across intermediaries. Conventional infrastructure financing instruments were compared with blockchain tokenization by reviewing the literature on infrastructure finance. The benefits and barriers of tokenizing infrastructure assets were thoroughly discussed to devise ways of improving infrastructure financing. The study also found that the potential of tokenization has not yet been fully realized because of the limited technical infrastructures, regulation uncertainties, volatilities in the token market, and absence of the public sector. This study contributes to the present understanding of how blockchain technology can be implemented in infrastructure finance and the role of tokenization in the structure of public–private partnership and project finance.     

Manipulations that influence stereotypes of the weight-gain potential of foods

The present study examined the impact of two manipulations on beliefs of the weight-gain potential of foods. Respondents (n = 230) compared foods that are often perceived to be unhealthy to similar- or higher-calorie foods that are often perceived to be healthy in terms of their capacity to promote weight gain. A portion of the respondents were provided information about energy amounts of the foods while the remaining respondents were not. Also, an experimental manipulation examined whether holding the total daily energy intake at 2000 kcal had any impact on the findings. The caloric information presented had at best a modest effect on respondents’ ratings of the foods. However, generally regardless of the information provided the respondents viewed “unhealthy” foods as weight promoters (compared to “healthy” foods) and only fat content (not energy density or kcal, fiber and sugar content) predicted which foods would be judged to promote weight gain. A simple and handy stereotype appears to be the most convenient method for most people to evaluate the weight-gain potential of food names even when more accurate information (energy content) is available.     

Investigation of the implanted phosphorus in a boron doped SiGe epitaxial layer

Phosphorus diffusion into strained SiGe layers was studied by different methods. Doping profiles and carrier concentration profiles N(x), depth of pn junction, Ge content in SiGe and thickness of epitaxial layer were measured and simulated. Several experimental methods such as secondary ion mass spectroscopy, spreading resistance method, Raman spectroscopy—and process simulator ISE TCAD have been used. The results obtained by different methods and at different places of work have been compared and analysed.     

Quantifying characteristic growth dynamics in a semi-arid grassland ecosystem by predicting short-term NDVI phenology from daily rainfall: a simple four parameter coupled-reservoir model

Predicting impacts on phenology of the magnitude and seasonal timing of rainfall pulses in water-limited grassland ecosystems concerns ecologists, climate scientists, hydrologists, and a variety of stakeholders. This report describes a simple, effective procedure to emulate the seasonal response of grassland biomass, represented by the satellite-based normalized difference vegetation index (NDVI), to daily rainfall. The application is a straightforward adaptation of a staged linear reservoir that simulates the pulse-like entry of rainwater into the soil and its redistribution as soil moisture, the uptake of water by plant roots, short-term biomass development, followed by the subsequent transpiration of water through foliage. The algorithm precludes the need for detailed, site specific information on soil moisture dynamics, plant species, and the local hydroclimate, while providing a direct link between discrete rainfall events and consequential biomass responses throughout the growing season. We applied the algorithm using rainfall data from the Central Plains Experimental Range to predict vegetation growth dynamics in the semi-arid shortgrass steppe of North America. The mean annual rainfall is 342 mm, which is strongly bifurcated into a dominantly ‘wet’ season, where during the three wettest months (May, June and July) the mean monthly rainfall is approximately 55 mm month^?1; and a ‘dry’ season, where during the three driest months (December, January and February), the mean monthly rainfall is approximately 7 mm month^?1. NDVI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 16 day, 250 m × 250 m product were used as a proxy for grassland phenology for the period-of-record 2000–2013. Allowing for temporal changes in basic parameters of the response function over the growing season, the predicted response of the model tracks the observed NDVI metric with correlation coefficients exceeding 0.92. A two-stage series reservoir is preferred, whereby the characteristic time for transfer of a rainfall event to the peak response of NDVI decreases from 24 days (early growing season) to 12 days (late growing season), while the efficiency of a given volume of rainfall to produce a correspondingly similar amount of aboveground biomass decreases by a factor of 40% from April to October. Behaviours of the characteristic time of greenup and loss of rainfall efficiency with progression of the growing season are consistent with physiological traits of cool-season C₃ grasses versus warm-season C₄ grasses, and with prior research suggesting that early season production by C₃ grasses is more responsive to a given amount of precipitation than mid-summer growth of C₄ shortgrasses. Our model explains >90% of seasonal biomass dynamics. We ascribe a systematic underprediction of observed early season greenup following drought years to a lagged or ‘legacy’ effect, as soil inorganic nitrogen, accumulated during drought, becomes available for future plant uptake.