3,573 research outputs found
Loss analysis of a single phase fast transient VRM converter
This paper analyzes the losses of a stepping inductor converter in the presence of load transients. Stepping inductor converter is a buck VRM topology which only employs a single phase. Stepping inductor converter is very effective in dealing with fast transient and at the same time it can give better steady state efficiency. Occurrences of transient load current changes are measured in a PC and data are used for the comparison to evaluate the real world performance of the stepping inductor converter and the multiphase interleaved buck converter.published_or_final_versio
Development of specific RAPD markers for identifying albino tea cultivars ‘Qiannianxue’ and ‘Xiaoxueya’
Albino tea cultivars grow white leaves at low temperature which are valuable materials for processing green tea, but they develop green leaves in summer and autumn seasons. It is difficult to discriminate albino tea cuttings from the normal tea cuttings by leaf colour and plant morphological characteristics.Specific RAPD markers for identifying albino tea cultivars ‘Qiannianxue’ and ‘Xiaoxueya’ were developed in the present paper and they can be used in the authentication of the two albino tea cultivars. An amplified fragment (about 1500 bp) from Primer (S 12 (Sangon Biological Engineering Technology and Services Co., Ltd.) was identified in the albino teas and not from the widely cultivated cultivar; Fudingdabai
A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application
© 2016 IEEE. A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications
Towards Safer Robot Motion: Using a Qualitative Motion Model to Classify Human-Robot Spatial Interaction
For adoption of Autonomous Mobile Robots (AMR) across a breadth of industries, they must navigate around humans in a way which is safe and which humans perceive as safe, but without greatly compromising efficiency. This work aims to classify the Human-Robot Spatial Interaction (HRSI) situation of an interacting human and robot, to be applied in Human-Aware Navigation (HAN) to account for situational context. We develop qualitative probabilistic models of relative human and robot movements in various HRSI situations to classify situations, and explain our plan to develop per-situation probabilistic models of socially legible HRSI to predict human and robot movement. In future work we aim to use these predictions to generate qualitative constraints in the form of metric cost-maps for local robot motion planners, enforcing more efficient and socially legible trajectories which are both physically safe and perceived as safe
Quantifying Inactive Lithium in Lithium Metal Batteries
Inactive lithium (Li) formation is the immediate cause of capacity loss and
catastrophic failure of Li metal batteries. However, the chemical component and
the atomic level structure of inactive Li have rarely been studied due to the
lack of effective diagnosis tools to accurately differentiate and quantify Li+
in solid electrolyte interphase (SEI) components and the electrically isolated
unreacted metallic Li0, which together comprise the inactive Li. Here, by
introducing a new analytical method, Titration Gas Chromatography (TGC), we can
accurately quantify the contribution from metallic Li0 to the total amount of
inactive Li. We uncover that the Li0, rather than the electrochemically formed
SEI, dominates the inactive Li and capacity loss. Using cryogenic electron
microscopies to further study the microstructure and nanostructure of inactive
Li, we find that the Li0 is surrounded by insulating SEI, losing the electronic
conductive pathway to the bulk electrode. Coupling the measurements of the Li0
global content to observations of its local atomic structure, we reveal the
formation mechanism of inactive Li in different types of electrolytes, and
identify the true underlying cause of low Coulombic efficiency in Li metal
deposition and stripping. We ultimately propose strategies to enable the highly
efficient Li deposition and stripping to enable Li metal anode for next
generation high energy batteries
Template Synthesis of Carbon Nanofibers Containing Linear Mesocage Arrays
Carbon nanofibers containing linear mesocage arrays were prepared via evaporation induced self-assembly method within AAO template with an average channel diameter of about 25 nm. The TEM results show that the mesocages have an elongated shape in the transversal direction. The results of N2 adsorption–desorption analysis indicate that the sample possesses a cage-like mesoporous structure and the average mesopore size of the sample is about 18 nm
A novel tumor suppressor gene ECRG4 interacts directly with TMPRSS11A (ECRG1) to inhibit cancer cell growth in esophageal carcinoma
<p>Abstract</p> <p>Background</p> <p>The esophageal carcinoma related gene 4 (ECRG4) was initially identified and cloned from human normal esophageal epithelium in our laboratory (GenBank accession no.<ext-link ext-link-id="AF325503" ext-link-type="gen">AF325503</ext-link>). ECRG4 has been described as a novel tumor suppressor gene associated with prognosis in esophageal squamous cell carcinoma (ESCC).</p> <p>Methods</p> <p>In this study, binding affinity assay in vitro and co-immunoprecipitation experiment in vivo were utilized to verify the physical interaction between ECRG4 and transmembrane protease, serine 11A (TMPRSS11A, also known as ECRG1, GenBank accession no. <ext-link ext-link-id="AF 071882" ext-link-type="gen">AF 071882</ext-link>). Then, p21 protein expression, cell cycle and cell proliferation regulations were examined after ECRG4 and ECRG1 co-transfection in ESCC cells.</p> <p>Results</p> <p>We revealed for the first time that ECRG4 interacted directly with ECRG1 to inhibit cancer cell proliferation and induce cell cycle G1 phase block in ESCC. Binding affinity and co-immunoprecipitation assays demonstrated that ECRG4 interacted directly with ECRG1 in ESCC cells. Furthermore, the ECRG4 and ECRG1 co-expression remarkably upregulatd p21 protein level by Western blot (P < 0.001), induced cell cycle G1 phase block by flow cytometric analysis (P < 0.001) and suppressed cell proliferation by MTT and BrdU assay (both P < 0.01) in ESCC cells.</p> <p>Conclusions</p> <p>ECRG4 interacts directly with ECRG1 to upregulate p21 protein expression, induce cell cycle G1 phase block and inhibit cancer cells proliferation in ESCC.</p
Soil-water interacting use patterns driven by Ziziphus jujuba on the Chenier Island in the Yellow River Delta, China
The determination of water use patterns of plants in a coastal ecosystem is critical to our understanding of local eco-hydrological processes and predicting trends in ecological succession under the background of global climate change. The water use patterns of Ziziphus jujuba, the dominant species on the Chenier Island in the Yellow River Delta, were examined following summer rainfall events. Stable oxygen isotope analysis was employed to analyze the effects of rainfall on the stable isotopic composition in potential water sources in Z. jujuba. The IsoSource model was used to estimate the contributions of potential water sources for xylem water in Z. jujuba. The results showed heavy rainfall could recharge both soil and groundwater but contributed little to the O-18 values in deep soil water (60-100cm) and groundwater. Light rainfall had an effect only on surface soil water (0-40cm). Z. jujuba mainly absorbed deep soil water on non-rainy days. Rainwater became the predominant water source for Z. jujuba during and immediately after heavy rainfall. Switching the plant's main water source between deep soil water and rainwater provided Z. jujuba with a competitive advantage and improved the water use efficiency of Z. jujuba in this coastal ecosystem
BDNF Facilitates L-LTP Maintenance in the Absence of Protein Synthesis through PKMζ
Late-phase long term potentiation (L-LTP) is thought to be the cellular basis for long-term memory (LTM). While LTM as well as L-LTP is known to depend on transcription and translation, it is unclear why brain-derived neurotrophic factor (BDNF) could sustain L-LTP when protein synthesis is inhibited. The persistently active protein kinase ζ (PKMζ) is the only molecule implicated in perpetuating L-LTP maintenance. Here, in mouse acute brain slices, we show that inhibition of PKMζ reversed BDNF-dependent form of L-LTP. While BDNF did not alter the steady-state level of PKMζ, BDNF together with the L-LTP inducing theta-burst stimulation (TBS) increased PKMζ level even without protein synthesis. Finally, in the absence of de novo protein synthesis, BDNF maintained TBS-induced PKMζ at a sufficient level. These results suggest that BDNF sustains L-LTP through PKMζ in a protein synthesis-independent manner, revealing an unexpected link between BDNF and PKMζ
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