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Dual-mode electrochemical aptasensor based on nitrogen-doped graphene (NG) doped with the conducting polymer polypyrrole (PPy) nanocomposite is proposed for the determination of acetamiprid. NG/PPy was electrodeposited onto the glassy carbon electrode (GCE) using cyclic voltammetry technique. NG/PPy/GCE showed outstanding electrocatalytic activity for the oxidation of nitrite due to "active region" induced by the charge redistribution of carbon atoms. The ultrasensitive dual-mode biosensor for acetamiprid could be easily developed by coupling acetamiprid aptamers with the NG/PPy hybrid. The specific binding between acetamiprid and the aptamers resulted in the increase of differential pulse voltammetry (DPV) signal change and the decrease of chronoamperometry (CA) signal, and the concentration of acetamiprid could be measured. The working potentials of DPV and CA were - 0.2 ~ 0.4 V and - 0.4 ~ 0.4 V (vs. SCE), respectively. The dual-mode acetamiprid biosensor showed a wide linear range from 10

This paper proposes an exact model for the planning and design problem of fog networks. More precisely, a mathematical model is proposed to simultaneously determine the optimal location, the capacity and the number of fog node(s) as well as the interconnection between the installed fog nodes and the cloud. The goal of the model is to minimize the delay in the network and the amount of traffic sent to the cloud data center. To address this multi-objective optimization problem, three optimization techniques are used: the weighted sum, the hierarchical and the trade-off methods. The weighted sum method aggregates all the lone objective functions into a single objective by applying a weighted vector. The hierarchical method takes a sequential approach by tightly constraining the more important objective function. The trade-off method solves a single objective function and translates all other objective functions into constraints. These methods are then compared in terms of average delay, amount of traffic sent to the cloud and amount of CPU time required to find optimal solution(s). Since we are dealing with a multi-objective optimization problem and that multiple optimal solutions can be found, the fuzzy-based mechanism and the hypervolume indicator have been used. Computational results show that as the problem size increases, the delay and the traffic also increase in a linear form; whereas, the solution time increases in non-polynomial time. The weighted sum method was able to achieve the best trade-off results for the delay and the traffic, whereas the hierarchical method was able to return minimum delay but with worse traffic going to the cloud. As the model considers realistic edge device traffic parameters, constraints, and various topology aspects, it can be helpful for the planning and deployment of fog networks and how they operate within a cloud infrastructure.

Adhering to the fundamental goal of building morality and cultivating people, systematic, all-round, and long-term ideological and political education is the fundamental task of colleges and universities to cultivate new people with faith, sentiment, and responsibility. According to the requirements of educating people and educating talents of the newcomers, this paper constructs an ideological and political SPOC course for the newcomers in the computer-related professional to learn independently, using a blended teaching method based on flipped classrooms, taking advantage of the interaction and growth archive recording functions of the SPOC platform, and carrying out multiple evaluation on students through a mixed teacher team, accurately depicting students’ ideological and political level, academic cognition and skills, and professional accomplishment, it realizes the unity of value shaping, knowledge imparting and ability cultivation.

With the aging problem becoming more and more serious, muscle pain has become a common symptom. In order to help patients with rehabilitation training, it is necessary to monitor their activities in time. We propose a real-time monitoring method based on wearable devices. This method uses a wireless body area network for health care. Specifically, in the first step, we developed a wearable device based on ZigBee with low cost and low weight. Secondly, if only classifying the action at the current time, it will not meet the requirements of real-time monitoring. So, we design an end-to-end neural network model called ATCRNN to infer the actions to be made by users at the next time according to the data of the past few times. This model uses CNN and RNN to extract the spatial and temporal features of data and captures the context characteristics through self-attention. Finally, four volunteers wore equipment to participate in the experiment. The activity categories in the experiment are walking, sitting down, running, and climbing stairs. The accuracy of behavior inference reached 97% with ATCRNN. The compared results demonstrate that the performance of the proposed approach is superior to the result of other deep learning networks.

Moiré superlattices are formed when overlaying two materials with a slight mismatch in twist angle or lattice constant. They provide a novel platform for the study of strong electronic correlations and non-trivial band topology, where emergent phenomena such as correlated insulating states, unconventional superconductivity, and quantum anomalous Hall effect are discovered. In this review, we focus on the semiconducting transition metal dichalcogenides (TMDs) based moiré systems that host intriguing flat-band physics. We first review the exfoliation methods of two-dimensional materials and the fabrication technique of their moiré structures. Secondly, we overview the progress of the optically excited moiré excitons, which render the main discovery in the early experiments on TMD moiré systems. We then introduce the formation mechanism of flat bands and their potential in the quantum simulation of the Hubbard model with tunable doping, degeneracies, and correlation strength. Finally, we briefly discuss the challenges and future perspectives of this field.

"A picture is worth a thousand words". Internet plus has brought people into the era of picture reading. Pictures and videos are everywhere. And dynamic video has the characteristics of sound, sound and documentary. It has become a popular media form for the public. Therefore, mobile phone video shooting and production are convenient, and the popularization of video production and dissemination has become inevitable. However, the creation of artistic and innovative video works requires producers to master certain visual thinking methods in addition to film montage theories and techniques. The article briefly outlines the forming process of the concept of visual thinking, and proposes advanced methods of visual thinking: intuitive method, selection method, discovery method, and inquiry method. In the process of video production, some methods of visual thinking are analyzed through a case, such as the visualization of textual information, the figuration of image, the logic of concreteness, and the systematization of logic. We have studied practical visual thinking training methods, from the three stages of video production: script creation, shooting practice, and video packaging

Professor Howard Gardner's theory of multiple intelligences believes that human intelligence is composed of at least eight abilities such as language intelligence, mathematical logic intelligence, and introspective intelligence. Introspective intelligence is the individual's recognition of self's behavior and psychological state. It is very important for personal self-understanding and constructing a correct self. It plays a significant role in human learning, employment and development The development level of self-cognition is different at different stages. The article compiles a questionnaire based on the characteristics of Campbell's self-cognition.By collating and analyzing the data collected in the questionnaire, the basic status of self-knowledge of Chinese college students in the emerging stage can be obtained: College students' self-awareness is maturing, but self-awareness is high; College students have average emotional management skills, poor emotional expression, and emotional fluctuations; Undergraduates have clear learning goals, but their self-fulfilling channels are confused; College students have their own value system, but the values are immature; Career ideals are seriously ahead of schedule, not in line with professional abilities. The countermeasures to improve college students' self-cognition are: Educate students to build good interpersonal relationships; Strengthen the education of college students' self-awareness and strengthen career guidance; Create a good and positive mood; Educate students to strengthen self-improvement strategies in multiple ways and promote the healthy and harmonious development of college students.

The transport properties of complex fracture networks are of great significance to predicting the subsurface flow. Tree-like fracture networks were generated according to the fractal theory, and the roughness of fracture surfaces was created by using the Weierstrass–Mandelbrot function. The forward and reverse flows were numerically investigated via the lattice Boltzmann method by employing positive and negative pressure differences respectively. The results indicate that the bifurcation angle θ, fractal dimension D and flow direction have significant influences on the transport properties of fracture networks. The maximum velocity increases quaveringly from the entrance or the last bifurcation point but suddenly decreases at the next bifurcation point, which is mainly due to the variation of local roughness. Both the energy loss ratio and the local pressure loss coefficient increase with the bifurcation angle. The cavity vortex can form within the concave of rough surface for fractal dimensions larger than 1.2 which result in the reduction of the hydraulic aperture and the alteration of the streamline from being parallel with the surface to a favorable flow path. The ratio of fracture hydraulic width to physical width decreases with the fractal dimension and fracture level. The flow rate of reverse flow is higher than that of forward flow under the same driven pressure because the flow convergence has lower local resistance than the flow diversion at the bifurcations. The theoretical solution of the flow rate through the rough-walled tree-like fracture networks was derived and verified by the modelling results.

In Wireless Sensor Networks (WSNs), clustering techniques are often used to optimize energy consumption and increase Packet Delivery Rate (PDR). To date, most of the proposed clustering protocols assume that there is a Line of Sight (LOS) between all the sensors. In fact, most of the available WSN simulators assume the use of optimistic path loss models that neglect the effect of obstacles on the PDR. However, in real situations such as in 3D terrains, obstacles can interfere this LOS. Moreover, while clustering, it is also important to maintain the coverage of a given Region of Interest (ROI). Therefore, finding an integrated solution for both clustering and coverage problems in an irregular 3D field becomes a pressing concern. In this paper, we first adopt an obstacle-aware path loss model to reflect the effect of obstacles on the communication between any pair of sensors. To that end, the Castalia simulator is adapted to use this proposed path loss model. Then, we introduce a Coverage and Obstacle-Aware Cluster Head Selection (COACHS) protocol to solve the cluster heads selection problem while maintaining a good coverage of a WSN deployed in an irregular 3D field. Simulation results demonstrate that the effect of obstacles on the PDR cannot be neglected. Moreover, comparative evaluation results show that COACHS outperforms other competent protocols in terms of PDR while simultaneously maintaining an acceptable energy consumption and a good coverage of the ROI.

The use of foam-based fracturing fluids for hydraulic fracturing has been identified as a promising technique to extract unconventional natural gases. However, lack of knowledge of foam properties and the two-phase flow behaviour of foam under high pressure makes it challenging to use in field conditions. Therefore, this comprehensive study was conducted to investigate (1) the properties and flow behaviour of foams, under relatively high-pressure (7 MPa) conditions using a newly-developed high-pressure viewing window and (2) two-phase flow behaviour through fractured rock using the high-pressure triaxial test apparatus. Fracture permeability tests were conducted for a series of confining and injection pressures, to evaluate the relative permeability coefficients. The experimental results show that foam flow can have bubble, plug, slug or disperse flow patterns, based on the gas flow rate, at a constant pressure. Moreover, the results show that, at pressures above 1 MPa, the foam flow is almost homogeneous with a fine texture, which is favourable for proppant transport. The findings of this study reveal that, during foam injection into a fractured rock mass under two-phase conditions, the nitrogen phase dominates the flow rate while having higher relative permeability coefficients than the water phase, irrespective of the confining pressure.

Fog computing has risen as a promising technology for augmenting the computational and storage capability of the end devices and edge networks. The urging issues in this networking paradigm are fog nodes planning, resources allocation, and offloading strategies. This paper aims to formulate a mathematical model which jointly tackles these issues. The goal of the model is to optimize the tradeoff (Pareto front) between the capital expenditure and the network delay. To solve this multiobjective optimization problem and obtain benchmark values, we first use the weighted sum method and two existing evolutionary algorithms (EAs), nondominated sorting genetic algorithm II and speed-constrained multiobjective particle swarm optimization. Then, inspired by those EAs, this paper proposes a new EAs, named particle swarm optimized nondominated sorting genetic algorithm, which combines the convergence and searching efficiency of the existing EAs. The effectiveness of the proposed algorithm is evaluated by the hypervolume and inverted generational distance indicators. The performance evaluation results show that the proposed model and algorithms can help the network planners in the deployment of fog networks to complement their existing computation and storage infrastructure.

Teacher learning is characterized by informal learning and lifelong learning. Mobile devices and personal space in the information environment provide convenient conditions for the professional development of teachers. China's WeChat uses smart phone terminals as a platform to realize fast and two-way communication of voice, video, pictures, text, location and other information through the network. WeChat friends circle function, users can publish text, pictures and videos at any time, and become a record of life, A handy tool for sharing information with friends. This study uses case study methods, using Python and third-party library jieba, to analyze the text information of a primary school Chinese teacher WeChat friends circle, and assist in interviews and other methods to study the impact of fragmented learning on the professional growth of primary school Chinese teachers. Teachers can consciously improve their moral cultivation, establish a lifelong learning conviction, focus on their own professional development, be good at reflection, and actively carry out teaching reform. This leads to the general conclusion that teachers have a high degree of professional development consciousness and are practitioners of lifelong learning; fragmented and mixed learning is the most important form of learning for teachers; reflection is the best way for teachers to grow; innovative practice To be a smart teacher is the goal of the teacher.

Widespread dam construction has reduced the hydrological connectivity of catchments of various sizes. Nutrients lost from upper catchments can be intercepted by dams and deposited in reservoir sediments, and this reduces downstream nutrient transportation. Few previous studies have assessed historical nutrient deposition rates (NDRs) in man-made reservoirs. Using 137Cs and 210Pbex deposition chronologies, this paper examines the total nitrogen (TN), total phosphate (TP), and organic matter (OM) concentrations in six sediment cores recovered from Xujiaya reservoir (catchment area 580 km2), provides estimates of historical NDRs by referencing the original capacity curve, and explores temporal changes to the NDR since dam construction. The results show that anthropogenic sources resulted in the increase in nutrient concentrations in the upper parts of the cores, whereas natural sources were the main contributors to nutrient deposition across the whole reservoir. In addition, sediment supply from the catchment was the main source of the nutrients deposited in the reservoir, and the changing patterns of NDRs were overall regulated by sediment yields. The TN, TP, and OM profiles in the six cores, together with the historical NDRs, reflect the pattern of nutrient deposition in the reservoir derived from this agricultural catchment over the past 60 years. The results provide new insight into the effect of dam construction on nutrient deposition at a medium-sized catchment scale against a background of recent environmental change influenced by human activity.

Hydraulic fracturing is a promising technique to enhance gas production from deep geological formations by enhancing reservoir rock permeability. However, permeability enhancement may vary with reservoir conditions and fracturing fluid. The main objective of this study is to investigate the effect of fracturing fluid on the fracture pattern and permeability of fractured rock. Fracturing experiments were conducted on siltstone specimens with water and foam (N2 + water) as the fracturing fluids, using a high-pressure triaxial apparatus. CT scanning and 3-D scanning technology were used to examine the fracture pattern and the fracture surface of the fractured specimens. The fractured specimens were then used to conduct permeability experiments for five different confining pressures (5 – 25 MPa) and six different injection pressures (1 – 6 MPa) with N2, and fracture permeability values were compared, based on the fracturing fluid type as well as the intact rock permeability. The results indicate that foam fracturing can induce a complex twisted fracture with greater surface area and the fracture is throughout the specimen. Moreover, foam fracturing emits more energy than water fracturing during the fracturing process, which is favourable for secondary fracture development. According to the measured permeability values, the fracture permeability of foam fractured specimens is about 5 × 105 times greater than that of intact and water-fractured specimens. With increasing confining pressure, N2 permeability decreases, regardless of the specimen (intact or fractured), and interestingly permeability decreases with increasing injection pressure. These observations are related to the effective stress principle and the Klinkenberg effect.

Fluid flow in a rock fracture bounded by two rock surfaces with surface asperities is a complex phenomenon to study. However, precise knowledge of the flow characteristics through a real rock fracture is essential in order to design and estimate the efficiency and production of unconventional oil and gas exploration and geothermal energy extraction projects. The aim of this numerical study, is therefore to incorporate a rock fracture in the modelling platform using a pre-processing procedure and to couple it with the flow parameters. 3-D scanning technology was used to obtain the rock fracture surfaces and to generate the fracture profile in a grid matrix form. In addition, the generated fracture profile was imported in to the COMSOL Multiphysics software package to simulate the flow characteristics of the rock fracture. The COMSOL model was validated using experimental permeability results conducted under triaxial conditions. According to the results, the COMSOL numerical model can simulate the flow characteristics through the rock fracture with more than 90% accuracy compared to the experimental data. The numerical results also reveal that the pressure gradient through a rock fracture is nonlinear and depends on the fracture profile. Furthermore, the nonlinearity of pressure gradient varies on different sections of the fracture, confirming the heterogeneity nature of the fracture. In addition, the results illustrate that the entire fracture width does not contribute to the final flowrate and that it is essential to consider the effective fracture width in flow calculations.

As a commonly used structural material, the separation quality of thick glass has always been concerned. The current mechanical cutting methods used for thick glass not only are inefficient but also require subsequent polishing. A laser three-focus scheme (LTFS) was proposed in this paper to achieve high-quality and efficient separation. A confirmatory experiment and optical simulations have been carried out to confirm the correctness of the scheme. A finite element simulation model for LTFS separating low-iron glass was established, which analyzes the temperature and stress distributions. The fracture mechanism of glass was revealed by combining the crack morphology and thermal stress distribution. The experimental results demonstrate that the LTFS can perform high-quality separation of low-iron glass with a thickness of 20 mm, the width of kerfs is less than 25 µm, and the rms roughness is less than 5.5 nm. The separated sidewall is smooth and flat, without any unexpected defects, such as damage and cracks, and the subsequent polishing is not required.

In this work, the effect of particle size (0.25, 1.0, 1.5 mm) on the electrochemical corrosion behavior of X70 pipeline steel in a 1.5 wt% NaCl sandy soil corrosion system was investigated by electrochemical techniques including linear polarization resistance, potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) in combination with SEM-EDS surface analysis, and X-ray diffraction characterization. The laboratory experiments indicated that the corrosion rate of X70 pipeline steel increased with decreasing soil particle size to less than 1.0 mm and was mainly determined by a cathodic reaction. Whereas when the soil particle size increased beyond 1.0 mm, the corrosion rate of X70 steel decreased as the soil particle size decreased and the dominant reaction was metal dissolution in the bulk zone, and the corrosion rate was determined by anodic reaction. Additionally, the results of analysis of the metal surface morphologies agreed with the electrochemical measurements results. Corrosion of X70 pipe steel is affected by particle-sizes in a corrosive soil environment.

Underground coal mining usually develops vertical stresses and reduces the horizontal stress in front of the coal face, which may trigger the occurrence of coal ruptures and gas outburst hazards. According to the stress change characteristics of the working face using different mining methods, different loading paths (constant confining pressure path and unloading confining pressure path) were selected in this study. Methane permeability tests of coal samples under different loading and unloading paths were conducted. Based on these tests, the effects of the unloading rate on the mechanical behaviour and permeability evolution (including energy evolution and fractal dimension) of the coal was investigated quantitatively. The tests revealed that the higher confining pressure unloading rates yielded a lower compressive strength and ductile strain. The increase in the unloading rate reduced the elastic energy and dissipation energy of the samples. Moreover, the higher unloading rate corresponded to more complex failure structures of coal and a greater fractal dimension, which resulted in greater permeability after the rupture of the coal samples. Furthermore, the higher unloading rates accelerated the rock damage rate and the permeability increase rate, which had a notable effect on the emergence of gas outburst hazards.

Since the secure storage of CO2 in any geological sink is largely dependent on its caprock and reservoir rock flow properties, it is necessary to check the permeability of both in assessing geological reservoirs for CO2 storage. Siltstone is a common rock type in both. On the other hand, the highly complicated thermodynamic properties of CO2 cause its flow behaviour through any rock mass to become highly complex. This intention of this study is to understand this complexity and to propose an accurate technique to evaluate the apparent permeability of CO2 through siltstone under laboratory conditions, considering the possible phase transitions of CO2 inside the rock mass. A series of tri-axial drained experiments on siltstones at room temperature was therefore performed. According to the results, the proposed method accurately predicts permeability through siltstone in tri-axial drained tests, because it more precisely considers the influence of CO2 phase transition on its flow performance, and the permeability in the sample is separately evaluated for the liquid and gas CO2 regions. The new approach shows that the actual CO2 pressure distribution along the sample has a curvilinear shape. Consideration of the possible phase transition between the sample inlet and the outlet is particularly important for liquid CO2 injection in tri-axial drained tests, due to the certainty of the occurrence of phase transition under this liquid inlet and gas outlet condition. According to the test results, the apparent permeability calculated for liquid CO2 injection using the proposed method is around 50% lower than that evaluated using the traditional method. This suggests the importance of the use of more accurate approaches such as that proposed under such situations. In addition, CO2 permeability in siltstone is found to be significantly increased with increasing injection pressure, and increasing the injection pressure from 3 to 6 MPa (in the gas CO2 region) caused the CO2 permeability in the tested siltstone to be increased from 0.00102 to 0.00228 mD at 15 MPa confining pressure, which is related to the related pore structure modification in siltstone.

Brittleness is commonly used to characterize the possible failure features in rocks, quantified by the brittleness index (BI(26)BIs, the applicability of each BI should be well understood to enable the selection of the most suitable for each application. This study reports on a detailed review of existing BI definitions in the rock mechanics field, the transition from brittle to ductile and the application of BIs to shale fracturing. The success of shale gas recovery using hydraulic fracking is greatly dependent on the shale's brittleness, since brittle shales have many pre-existing fractures and are easy to fracture in tensile and shear modes. A combination of laboratory and geophysical approaches are recommended for shale brittleness quantification. Precise quantification of brittleness is important, both in the laboratory and the field. Brittleness indices based on the elastic moduli (Young's modulus and Poisson's ratio) and mineral composition are common in field applications, and can be derived from both laboratory tests and field log data.

In the field of inspection and testing, it is necessary to manually fill a large number of test record forms, and the digital information accounts for a large proportion in the record forms. For the purpose of automatic and accurate recognition of handwritten form data, this paper proposes a handwritten digit recognition method based on Harris corner detection algorithm and convolutional neural network(CNN). The Harris corner detection algorithm is used to identify the positioning marks in the form image, which determine the possible fill-in positions of handwritten digits. Through a 14-layer CNN model, and using the ReLu function as the excitation function, the handwritten digit features of the target area in the image are recognized. The experimental results show that the average recognition accuracy rate of this method on the test set can reach 98.14%. So a technical solution for intelligent recognition of record forms is thus provided.

Absolute and water saturation dependent gas flow under reservoir conditions is important for the exploration of deep energy resources. Steady-state and various unsteady-state argon permeability tests were conducted on dry Niutitang shale during the confinement loading and unloading cycles, then different gases were used for steady-state permeability tests at the final confinement of 20 MPa. Permeability decreased by 36% with the confinement increasing from 5 MPa to 60 MPa, and around 66% of the permeability reductions was recovered after the unloading cycles. The apparent steady-state permeabilities were 38% higher than those derived by unsteady-state methods due to the enhanced slip flow. Two cycles of water imbibition and gas drainage tests were conducted with the long water evaporation process completed in the second gas drainage process. Argon to carbon dioxide permeability ratio ranged from 1.2 to 2.1, while the water permeability was 30–45% of the gas intrinsic permeability. The argon breakthrough pressure of water-saturated Niutitang shale sample was 8 MPa, and the permeability increased by 10 times after the long-term evaporation process. Argon permeability decreased by 90% and increased by 21.6%–29.6% respectively after the first and second gas drainage processes compared with that under dry condition with the residual water saturation being 29.7% and 11.3% respectively, which were caused by the water blockage and cracking respectively. Influences of carbon dioxide adsorption and induced swelling reached a minimum at residual water saturation.

Steady-state and unsteady-state (downstream pressure build-up) gas permeability tests were conducted on low permeability siltstone at a series of upstream pressures during the loading and unloading processes. The characteristics of downstream pressure build-up curves are analysed in detail, and the permeability is calculated based on the data in the stabilization stage. Analysing approaches with and without consideration of the sample pore volume are used to obtain the unsteady-state permeability for both the real pressure and the pseudo pressure. Findings suggest that the permeability based on the pseudo pressure is generally lower than that based on the real pressure, with their ratio ranging from 0.75 to 0.98. The sample pore volume corrected permeability is 1.42–1.51 times of that without the consideration of sample pore volume. The apparent steady-state gas permeability is higher than the sample pore volume corrected permeability due to slip flow, while its intrinsic permeability is lower as the pore pressure is smaller in the steady-state test. The permeabilities decrease with the confining pressure in the loading path especially at lower confinements, while only part of the reductions is recovered during the unloading process. Increase of pore pressure enhances permeability under low confinement conditions. Water permeability is lower than gas permeability in steady-state test due to the water-rock interaction and the residual gas inside the sample.

Water-based hydraulic fracturing is usually used for the stimulation of low-permeability unconventional oil and gas reservoirs. However, large amounts of water is trapped in tight reservoirs after treatment which induces the water-rock interactions. The mechanical and flow properties of unconventional reservoir rocks and influences of water on them are investigated through a series of strength, water imbibition, permeability and fracturing laboratory tests for different reservoir conditions. The gas flow through unconventional reservoir rocks are modelled by using COMSOL. Water retention in micro pores after hydraulic fracturing is found to have significant effects on initial gas production from tight rocks.

The industrial waste like steel-slag, coal gangue and limestone were used to prepare high-strength aggregates with a composition like cement clinker in the present investigation, and the concrete were prepared by this aggregates rather than natural aggregates. The experimental results showed that this kind of concrete can be completely regenerated to be cement and used for building project again, so any construction waste were not produced, and the recycling of concrete can be truly realized. A tentative study of preparing a kind of recycled concrete was carried out, and the results showed that the aggregates with about 7% steel slag, 12% coal gangue, 80% limestone and calcined at 1400 °C had the best performance. The water absorption (about 0.82%), the crushing index (about 6.78%) and the apparent density (2672 kg/m3) of the aggregates meet the requirements of national standards (GB/T14685-2001). The concrete was prepared using these aggregates with the water-cement ratio of 0.45, the compressive strength of the concrete in 28 days is 58.7 MPa, higher than that of ordinary concrete. The waste of concrete after hardened of 90days were grinded and calcined at temperature of 1420 °C and the cenment clinker was prepared. After hydrated for 3 days, 7 days and 28 days, the compressive strength is 29.8 MPa, 45.1 Mpa, 51.3 Mpa, respectively, which reach the requirements of 42.5 ordinary Portland cement.