In some oilfields with 3D seismic data, the deeper structure cannot be observed due to poor quality deep seismic data. Layer stripping using both seismic and gravity data is a solution for this problem but it cannot g...In some oilfields with 3D seismic data, the deeper structure cannot be observed due to poor quality deep seismic data. Layer stripping using both seismic and gravity data is a solution for this problem but it cannot get satisfactory results because the horizontal variations in formation density are ignored. We present a variable-density formation separation technique to address this problem. Based on 3D seismic depth data and laterallyvariable density derived from 3D seismic velocity data, the upper formation gravity effect is calculated by forward modeling and removed from the Bouguer gravity. The formation-separated gravity anomaly with variable density is obtained, which mainly reflects the deeper geological structure. In block XX of North Africa, the shallow formations seismic data is excellent but the data at the top of basement is poor. The formation-separated gravity anomaly processed under the control of 3D seismic data fits well with the known seismic interpretation and wells. It makes the geological interpretation more reliable.展开更多
To understand the structure of GABAergic neurons in the VMP and ＂barrel＂, the distribution of GABAergic neurons in the two areas were studied through immunohistochemistry and Laser Scanning Confocal Microscope. The ...To understand the structure of GABAergic neurons in the VMP and ＂barrel＂, the distribution of GABAergic neurons in the two areas were studied through immunohistochemistry and Laser Scanning Confocal Microscope. The results show that the distribution of GABAergic neurons in VMP and barrel are different, and the coding of information transmission in the two areas are also dissimilar; GABAergic neurons mainly distribute among the lines asymmetrically in VMP, the somata, dendrite and axon of GABAergic neurons are restricted in the ＂barrel＂, rarely having synaptic connections with other ＂barrel＂ around. Therefore, VMP and barrel may have different roles in transmission and on processing of informatiton.展开更多
Flexible and wearable sensors have drawn ex-tensive concern due to their wide potential applications inwearable electronics and intelligent robots. Flexible sensorswith high sensRivity, good flexibility, and excellent...Flexible and wearable sensors have drawn ex-tensive concern due to their wide potential applications inwearable electronics and intelligent robots. Flexible sensorswith high sensRivity, good flexibility, and excellent stabilityare highly desirable for monitoring human biomedical signals,movements and the environment. The active materials and thedevice structures are the keys to achieve high performance.Carbon nanomaterials, including carbon nanotubes （CNTs）,graphene, carbon black and carbon nanofibers, are one of themost commonly used active materials for the fabrication ofhigh-performance flexible sensors due to their superiorproperties. Especially, CNTs and graphene can be assembledinto various multi-scaled macroscopic structures, includingone dimensional fibers, two dimensional films and three di-mensional architectures, endowing the facile design of flexiblesensors for wide practical applications. In addition, the hybridstructured carbon materials derived from natural bio-mate-rials also showed a bright prospect for applications in flexiblesensors. This review provides a comprehensive presentation offlexible and wearable sensors based on the above variouscarbon materials. Following a brief introduction of flexiblesensors and carbon materials, the fundamentals of typicalflexible sensors, such as strain sensors, pressure sensors,temperature sensors and humidity sensors, are presented.Then, the latest progress of flexible sensors based on carbonmaterials, including the fabrication processes, performanceand applications, are summarized. Finally, the remainingmajor challenges of carbon-based flexible electronics are dis-cussed and the future research directions are proposed.展开更多
文摘In some oilfields with 3D seismic data, the deeper structure cannot be observed due to poor quality deep seismic data. Layer stripping using both seismic and gravity data is a solution for this problem but it cannot get satisfactory results because the horizontal variations in formation density are ignored. We present a variable-density formation separation technique to address this problem. Based on 3D seismic depth data and laterallyvariable density derived from 3D seismic velocity data, the upper formation gravity effect is calculated by forward modeling and removed from the Bouguer gravity. The formation-separated gravity anomaly with variable density is obtained, which mainly reflects the deeper geological structure. In block XX of North Africa, the shallow formations seismic data is excellent but the data at the top of basement is poor. The formation-separated gravity anomaly processed under the control of 3D seismic data fits well with the known seismic interpretation and wells. It makes the geological interpretation more reliable.
基金Supported by National Natural Science Fund(30670230)~~
文摘To understand the structure of GABAergic neurons in the VMP and ＂barrel＂, the distribution of GABAergic neurons in the two areas were studied through immunohistochemistry and Laser Scanning Confocal Microscope. The results show that the distribution of GABAergic neurons in VMP and barrel are different, and the coding of information transmission in the two areas are also dissimilar; GABAergic neurons mainly distribute among the lines asymmetrically in VMP, the somata, dendrite and axon of GABAergic neurons are restricted in the ＂barrel＂, rarely having synaptic connections with other ＂barrel＂ around. Therefore, VMP and barrel may have different roles in transmission and on processing of informatiton.
基金supported by the National Natural Science Foundation of China(51672153,51422204 and 51372132)National Key Basic Research and Development Program(2016YFA0200103 and 2013CB228506)
文摘Flexible and wearable sensors have drawn ex-tensive concern due to their wide potential applications inwearable electronics and intelligent robots. Flexible sensorswith high sensRivity, good flexibility, and excellent stabilityare highly desirable for monitoring human biomedical signals,movements and the environment. The active materials and thedevice structures are the keys to achieve high performance.Carbon nanomaterials, including carbon nanotubes （CNTs）,graphene, carbon black and carbon nanofibers, are one of themost commonly used active materials for the fabrication ofhigh-performance flexible sensors due to their superiorproperties. Especially, CNTs and graphene can be assembledinto various multi-scaled macroscopic structures, includingone dimensional fibers, two dimensional films and three di-mensional architectures, endowing the facile design of flexiblesensors for wide practical applications. In addition, the hybridstructured carbon materials derived from natural bio-mate-rials also showed a bright prospect for applications in flexiblesensors. This review provides a comprehensive presentation offlexible and wearable sensors based on the above variouscarbon materials. Following a brief introduction of flexiblesensors and carbon materials, the fundamentals of typicalflexible sensors, such as strain sensors, pressure sensors,temperature sensors and humidity sensors, are presented.Then, the latest progress of flexible sensors based on carbonmaterials, including the fabrication processes, performanceand applications, are summarized. Finally, the remainingmajor challenges of carbon-based flexible electronics are dis-cussed and the future research directions are proposed.
