Voltage control on an uninhabited autonomous vehicle electrical distribution system

More-electric vehicle technology is becoming prevalent in a number of transportation systems because of its ability to improve efficiency and reduce costs. This paper examines the specific case of an Uninhabited Autonomous Vehicle (UAV), and the system topology and control elements required to achieve adequate dc distribution voltage bus regulation. Voltage control methods are investigated and a droop control scheme is implemented on the system. Simulation results are also presented.

Redox signalling and detection of protein oxidation by mass spectrometry

It is now recognised that redox control of proteins plays an important role in many signalling pathways both in health and disease. Proteins can undergo a wide variety of oxidative post-translational modifications (oxPTM); while the reversible modifications are thought to be most important in physiological processes, non-reversible oxPTM may contribute to pathological situations and disease. The oxidant is also important in determining the type of oxPTM (chlorination, nitration, etc.), and the susceptibilities of residues vary depending on their structural location. The best characterized oxPTMs involved in signalling modulation are partial oxidations of cysteine to the disulfide, glutathionylated or sulfenic acid forms, but there is increasing evidence that specific oxidations of methionine and tyrosine may have some biological roles. Well understood examples of oxidative regulation include protein tyrosine phosphatases, e.g. PTP1B/C, and members of the MAPK pathways such as MEKK1 and ASK1. Transcription factors such as NFkB and Nrf-2 are also regulated by redox-active cysteines. Improved methods for analysing specific oxPTMs in biological samples are critical for understanding the physiological and pathological roles of these changes, and tandem or MS3 mass spectrometry techniques interfaced with nano-LC separation are being now used. MS3 fragmentation markers for a variety of oxidized residues including tyrosine, tryptophan and proline have been identified, and a precursor ion scanning method that allows the selective identification of these oxPTMs in complex samples has been developed. Such advances in technology offer potential for biomarker development, disease diagnosis and understanding pathology.

Identification and molecular mechanisms of the rapid tonicity-induced relocalization of the aquaporin 4 channel

The aquaporin family of integral membrane proteins is comprised of channels that mediate cellular water flow. Aquaporin 4 (AQP4) is highly expressed in the glial cells of the central nervous system and facilitates the osmotically-driven pathological brain swelling associated with stroke and traumatic brain injury. Here we show that AQP4 cell surface expression can be rapidly and reversibly regulated in response to changes of tonicity in primary cortical rat astrocytes and in transfected HEK293 cells. The translocation mechanism involves protein kinase A (PKA) activation, influx of extracellular calcium and activation of calmodulin. We identify five putative PKA phosphorylation sites and use site-directed mutagenesis to show that only phosphorylation at one of these sites, serine- 276, is necessary for the translocation response. We discuss our findings in the context of the identification of new therapeutic approaches to treating brain oedema.

Identification and relative quantification of tyrosine nitration in a model peptide using two-dimensional infrared spectroscopy

Nitration of tyrosine in proteins and peptides is a post-translational modification that occurs under conditions of oxidative stress. It is implicated in a variety of medical conditions, including neurodegenerative and cardiovascular diseases. However, monitoring tyrosine nitration and understanding its role in modifying biological function remains a major challenge. In this work, we investigate the use of electron-vibration-vibration (EVV) two-dimensional infrared (2DIR) spectroscopy for the study of tyrosine nitration in model peptides. We demonstrate the ability of EVV 2DIR spectroscopy to differentiate between the neutral and deprotonated states of 3-nitrotyrosine, and we characterize their spectral signatures using information obtained from quantum chemistry calculations and simulated EVV 2DIR spectra. To test the sensitivity of the technique, we use mixed-peptide samples containing various levels of tyrosine nitration, and we use mass spectrometry to independently verify the level of nitration. We conclude that EVV 2DIR spectroscopy is able to provide detailed spectroscopic information on peptide side-chain modifications and to detect nitration levels down to 1%. We further propose that lower nitration levels could be detected by introducing a resonant Raman probe step to increase the detection sensitivity of EVV 2DIR spectroscopy. (Graph Presented).

Slow-phase onset influence on waveform identification and foveation time measure in congenital nystagmus

Congenital nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations and its pathogenesis is still under investigation. This kind of nystagmus is termed congenital (or infantile) since it could be present at birth or it can arise in the first months of life. Most of CN patients show a considerable decrease of their visual acuity: image fixation on the retina is disturbed by nystagmus continuous oscillations, mainly horizontal. However, the image of a given target can still be stable during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals). To quantify the extent of nystagmus, eye movement recording are routinely employed, allowing physicians to extract and analyse nystagmus main features such as waveform shape, amplitude and frequency. Using eye movement recording, it is also possible to compute estimated visual acuity predictors: analytical functions which estimates expected visual acuity using signal features such as foveation time and foveation position variability. Use of those functions extend the information from typical visual acuity measurement (e.g. Landolt C test) and could be a support for therapy planning or monitoring. This study focuses on detection of CN patients' waveform type and on foveation time measure. Specifically, it proposes a robust method to recognize cycles corresponding to the specific CN waveform in the eye movement pattern and, for those cycles, evaluate the exact signal tracts in which a subject foveates. About 40 eyemovement recordings, either infrared-oculographic or electrooculographic, were acquired from 16 CN subjects. Results suggest that the use of an adaptive threshold applied to the eye velocity signal could improve the estimation of slow phase start point. This can enhance foveation time computing and reduce influence of repositioning saccades and data noise on the waveform type identification.

Probabilistic multiple model neural network based leak detection system:experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.

Radio frequency identification and its application in e-commerce

This chapter presents Radio Frequency Identification (RFID), which is one of the Automatic Identification and Data Capture (AIDC) technologies (Wamba and Boeck, 2008) and discusses the application of RFID in E-Commerce. Firstly RFID is defined and the tag and reader components of the RFID system are explained. Then historical context of RFID is briefly discussed. Next, RFID is contrasted with other AIDC technologies, especially the use of barcodes which are commonly applied in E-Commerce. Lastly, RFID applications in E-Commerce are discussed with the focus on achievable benefits and obstacles to successful applications of RFID in E-Commerce, and ways to alleviate them.