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Glasses have been used as the most versatile engineering materials for more than five decades. Chalcos is a Greek word which means ore former and glasses prepared by particular chalcogenide of group VI element of the periodic table or by their compounds have been known for more than 50 years as an optical material. The primary objective is to provide up to date description of the development in the field of optical and electrical properties of MWCNTs additive chalcogenide glasses. An extensive survey of relevant literature was carried out using sophisticated libraries, virtual media, different research laboratories, internet and also by personal contact with the senior researcher of this field. The exponential increase in D.C. conductivity was observed on increasing the CNT concentration. Inter nanotube connections increase which results in modification of chemical bond formation with increased CNT concentration. It has been observed that the optical band gap of CNT doped chalcogenide glass increases which may be attributed to the fact that CNT added to to the glasses retards the motion of charge carriers and may raise the optical bandgap. The electrical and optical properties of CNT additives chalcogenide glasses have been reviewed. Several applications based on CNT doped glasses have also been discussed, including the development of ionic memories, sensors, optical waveguides, holography, solid-state batteries, optical, and non-linear optical devices.

Forest trees use various water sources to adapt to environmental conditions in mountainous regions. However, water resources variances along elevational gradients are not clearly understood. This limits the assessment of the ecosystem responses to climate change. In this study, stable oxygen and hydrogen isotopes were used to investigate the spatiotemporal patterns of water sources for Faber's fir in a humid high-altitude elevational gradient (ranging between 2800 m.a.s.l. and 3700 m.a.s.l.) on the southeastern Tibetan Plateau. The results indicated that 27 ± 8.3 % of the xylem water was from previous winter snowmelt between May and June. In contrast, almost all xylem water was from current summer precipitation between July and October. Faber's fir at the lower elevation (2800 m.a.s.l.) primarily relied on water derived from winter precipitation during May and June. Yet, trees located near the tree line (3700 m.a.s.l.) were mostly dependent on current precipitation over the entire growing season. However, when statistically analyzing data from all seven different elevation gradients in this study, the contribution of winter precipitation to xylem water was not elevation dependent. Precipitation contributed to a large proportion (59.86 % ± 33.43 %) of xylem water between May and October. Meanwhile, no linear contribution ratio of precipitation to trees was identified in this high-altitude elevational gradient. The replenishment of soil water and the soil water storage determine the spatiotemporal patterns of water sources. Climate change has the possibility of reducing winter precipitation at high altitudes on the Tibetan Plateau. Thus, tree water use at different altitude gradients will play varied roles in influencing the evolution of forest composition under ongoing climate change.

There is a lack of knowledge about how to quantify runoff generation and the hydrological processes operating in permafrost catchments on semi-arid plateaus. To understand how freeze-thaw cycles affect runoff generation processes in permafrost catchments, a typical headwater catchment with continuous permafrost on the Tibetan Plateau was measured. A new approach is presented in this study to account for runoff processes on the spring thawing period and autumn freezing period, when runoff generation clearly differs from that of non-permafrost catchments. This approach introduces a soil temperature-based water saturation function and modifies the soil water storage curve with a soil temperature threshold. The results show that surface soil thawing induced saturation excess runoff and subsurface interflow account for approximately 66–86% and 14–34% of total spring runoff, respectively, and the soil temperature significantly affects the runoff generation pattern, the runoff composition and the runoff coefficient with the enlargement of the active layer. The suprapermafrost groundwater discharge decreases exponentially with active layer frozen processes during autumn runoff recession, whereas the ratio of groundwater discharge to total runoff and the direct surface runoff coefficient simultaneously increase. The bidirectional freezing of the active layer controls and changes the autumn runoff processes and runoff composition. The new approach could be used to further develop hydrological models of cold regions dominated by permafrost.

γ-Al2O3 membranes were successfully deposited on the top of porous α-Al2O3 support by sol-gel process and characterized by means of XRD, SEM, N2 adsorption and gas permeation. The γ-Al2O3 membranes, free of pin-holes and cracks, adhere tightly to the supports and have a thickness of about 7 μm. When sintered at 400°C, γ-Al2O3 membranes have a narrow pore size distribution, with a pore diameter of 3.6nm, and the transport of both H2 and CO2 in supported γ-Al2O3 membrane is governed by Knudsen mechanism, with H2 permeance of 3.3×10−6 molm−2 Pa−1 s−1 and H2/CO2 permselectivity close to the ideal Knudsen value at 50°C. The γ-Al2O3 membranes are suitable for being used as the substrates of microporous membranes.

Data acquisition based on existing drawings is an important part of basin modeling.But the digital acquisition faces the trade-off between efficiency and accuracy.Combining the target detection and Particle Swarm Optimization (PSO) technique,an improved Snake curve extraction algorithm based on particle density was proposed.The algorithm maintained a certain distance between particles to avoid the premature of PSO algorithm,and optimized convergence speed by modifying the model parameters.Compared with the traditional PSO algorithm,the experimental results show that the proposed algorithm is efficient,and has been applied in practical project.

Drifting learning (DL) is an effective method to solve the regression problem in the field of data mining. The approach is established based on the combination of Local Weighted Learning (LWL) algorithm and statistical learning theory (SLT). It is shown from the theoretic analysis and simulation that better performance on estimation precision and generalization ability than the traditional methods can be achieved. And this method is suitable for modeling complex industrial process with multiple work modes. In the algorithm, the optimized bandwidth selection is a key factor on the generalization performance and real-time performance. This paper first analyzes the effect of the optimized bandwidth on drifting learning method based on theoretic analysis and simulation, and then provides a novel optimized bandwidth selection algorithm. The simulation results show that the proposed approach can achieves performance superior to the existed methods