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| 1 | Effect of interface on mid-infrared photothermal response of MoS2 thin film grown by pulsed laser deposition显示文摘这研究报导在上中间红外线(中间 -- 红外) 多层的瞬间 2 的 photothermal 反应在上成年的薄电影水晶(p 类型硅和 c-axis-oriented 单身者水晶蓝宝石) 并且非结晶(Si/SiO 2 和 Si/SiN ) 由搏动的激光免职(PLD ) 的底层。当照耀与时,瞬间 2 电影的 photothermal 反应在瞬间 2 电影的抵抗作为变化被测量一中间 -- 红外(7 ~ 8.2 m ) 来源。我们显示出那提高瞬间 2 的抵抗(TCR ) 的温度系数薄电影由通过底层和生长条件的一种合适的选择控制电影底层接口是可能的。PLD 种的薄电影用 X 光检查衍射,拉曼,原子力量显微镜学, X 光检查光电子显微镜学,和传播电子被描绘显微镜学。高分辨率的传播电子显微镜学(HRTEM ) 图象证明瞬间 2 电影与不合身的衣服脱臼以一种 layer-by-layer 方式在蓝宝石底层上成长。当这些电影在有一颗钻石的底层上是成年的时,层生长形态学被破坏立方的结构(例如,硅) 因为成双的生长形成。非结晶的底层上的生长形态学例如 Si/SiO 2 或 Si/SiN,是很不同的。硅上的 PLD-grown 瞬间 2 电影显示出更高的 TCR (在 296 K 的 2.9% K 1) ,更高中间 -- 红外敏感(R/R =5.2%) ,并且更高的 responsivity (8.7 V 湡杯湥牥瑡牯吗?? | Ankur Goswami Priyesh Dhandaria Soupitak Pal Ryan McGee Faheem Khan Zeljka Antic Ravi Gaikwad Kovur Prashanthi Thomas Thundat | 2017 | Nano Research2017，10，10： | 2 |
| 2 | The Morning Blood Pressure Surge: Therapeutic Implications显示文摘 | Priyesh V.Patel Justin L.Wong RohitArora | 2008 | The Journal of Clinical Hypertension2008，，2： | 1 |
| 3 | Spectrum Sensing Using Optimized Deep Learning Techniquesin Reconfigurable Embedded Systems显示文摘The exponential growth of Internet of Things(IoT)and 5G networks has resulted in maximum users,and the role of cognitive radio has become pivotal in handling the crowded users.In this scenario,cognitive radio techniques such as spectrum sensing,spectrum sharing and dynamic spectrum access will become essential components in Wireless IoT communication.IoT devices must learn adaptively to the environment and extract the spectrum knowledge and inferred spectrum knowledge by appropriately changing communication parameters such as modulation index,frequency bands,coding rate etc.,to accommodate the above characteristics.Implementing the above learning methods on the embedded chip leads to high latency,high power consumption and more chip area utilisation.To overcome the problems mentioned above,we present DEEP HOLE Radio sys-tems,the intelligent system enabling the spectrum knowledge extraction from the unprocessed samples by the optimized deep learning models directly from the Radio Frequency(RF)environment.DEEP HOLE Radio provides(i)an opti-mized deep learning framework with a good trade-off between latency,power and utilization.(ii)Complete Hardware-Software architecture where the SoC’s coupled with radio transceivers for maximum performance.The experimentation has been carried out using GNURADIO software interfaced with Zynq-7000 devices mounting on ESP8266 radio transceivers with inbuilt Omni direc-tional antennas.The whole spectrum of knowledge has been extracted using GNU radio.These extracted features are used to train the proposed optimized deep learning models,which run parallel on Zynq-SoC 7000,consuming less area,power,latency and less utilization area.The proposed framework has been evaluated and compared with the existing frameworks such as RFLearn,Long Term Short Memory(LSTM),Convolutional Neural Networks(CNN)and Deep Neural Networks(DNN).The outcome shows that the proposed framework has outperformed the existing framework regarding the area,power and time.More-over,the experimental results show that the proposed framework decreases the delay,power and area by 15%,20%25%concerning the existing RFlearn and other hardware constraint frameworks. | Priyesh Kumar PonniyinSelvan | 2023 | Intelligent Automation & Soft Computing2023，，5： | 0 |
| 4 | Eolian versus fluvial supply to the northern Arabian Sea during the Holocene based on Nd isotope and geochemical records显示文摘The north-eastern Arabian Sea(NE-AS)comes under a strong influence of land–ocean–climate interactions and regulates biogeochemical processes through the supply of huge amounts of dissolved and particulate materials and nutrients via eolian and fluvial supply.These processes underwent dramatic changes in the coastal regions due to sea-level rise and climate change during the Holocene;however,their relative roles remain elusive.The NE-AS receives large amounts of dissolved and particulate fluxes,and therefore,reconstruction of the past surface water Nd isotope composition(eNd)and tracing the provenance of sediment using detrital eNd and geochemical records would enable us to assess the role of various processes controlling these fluxes to the northern Arabian Sea.In this study,we have generated authigenic and detrital eNd records and geochemical records in a sediment core from the coastal region of the NE-AS,offshore Saurashtra.We found that the authigenic eNd profile closely followed the Holocene sea-level records;early Holocene less radiogenic values(-8)were sharply shifted to more radiogenic values(-5.5)during the mid-Holocene(6–7 ka)and thereafter remained stable,close to the modern surface water eNd value.The detrital eNd record broadly followed the authigenic eNd record,however,they differ in magnitude.The geochemical records based on major and trace elemental abundances show a similar trend to the authigenic eNd record and concomitant changes with the Holocene sea-level.Our investigation reveals that lower sea-level stand combined with a stronger monsoon during the early Holocene resulted in enhanced fluvial weathering fluxes from the west-flowing rivers and contributed to less radiogenic Nd.This situation changed dramatically during the mid-Holocene due to the weakening of the south-west monsoon and rapid sea level rise,which caused enhanced influence of open ocean water characterised by more radiogenic eNd(-6)derived from the dissolution of dust from Arabia and African desserts.This dramatic shift in eNd profile indicates the enhanced influence of eolian over the fluvial supply of chemical weathering and erosion fluxes during the mid-Holocene.This observation is also consistent with the higher sedimentation rates with more radiogenic detrital supply.The finding of enhanced influence of eolian over fluvial mode of weathering and erosional inputs to the northern Arabian Sea has important implications for past nutrient supply(fluxes and compositions)and its impact on biogeochemical processes in the Arabian Sea. | Waliur Rahaman N.Lathika Priyesh Prabhat Mohd.Tarique K.S.Arya Ravi Mishra Meloth Thamban | 2023 | Geoscience Frontiers2023，14，5： | 0 |
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