Lithium Phthalocyanine: A Probe for Electron Paramagnetic Resonance Oximetry in Viable Biological Systems.

Lithium phthalocyanine (LiPc) is a prototype of another generation of synthetic, metallic-organic, paramagnetic crystallites that appear very useful for in vitro and in vivo electron paramagnetic resonance oximetry. The peak-to-peak line width of the electron paramagnetic resonance spectrum of LiPc is a linear function of the partial pressure of oxygen (pO2); this linear relation is independent of the medium surrounding the LiPc. It has an extremely exchange-narrowed spectrum (peak-to-peak line width = 14 mG in the absence of O2). Physicochemically LiPc is very stable; its response to pO2 does not change with conditions and environments (e.g., pH, temperature, redox conditions) likely to occur in viable biological systems. These characteristics provide the sensitivity, accuracy, and range to measure physiologically and pathologically pertinent O2 tensions (0.1-50 mmHg; 1 mmHg = 133 Pa). The application of LiPc in biological systems is demonstrated in measurements of pO2 in vivo in the heart, brain, and kidney of rats

Analytical solution of BVPs for fourth-order integrodifferential equations by using homotopy analysis method

Abstract:An analytic technique, the homotopy analysis method (HAM), is applied to obtain the approximate analytical solutions of fourth-order integro-differential equations. The homotopy analysis method (HAM) is one of the most effective method to obtain the exact and approximate solution and provides us with a new way to obtain series solutions of such problems. HAM contains the auxiliary parameter ℏ, which provides us with a simple way to adjust and control the convergence region of series solution. It is shown that the solutions obtained by the Adomian decomposition method (ADM) and the homotopy-perturbation method (HPM) are only special cases of the HAM solutions. we have shown that fourth-order boundary value problems can be transformed into a system of differential equations and integro-differential equation, which can be solved by using homotopy analysis method. Several examples are given to illustrate the efficiency and implementation of the method

Fault Type Estimation in Power Systems

Abstract: This paper presents a novel approach for fault type estimation in power systems. The Fault type estimation is the first step to estimate instantaneous voltage, voltage sag magnitude and duration in a three-phase system at fault duration. The approach is based on time-domain state estimation where redundant measurements are available. The current based model allows a linear mapping between the measured variable and the states to be estimated. This paper shows a possible for fault instance detection, fault location identification and fault type estimation utilizing residual analysis and topology error processing. The idea is that the fault status does not change measurement matrix dimensions but changes some elements of the measurement matrix. The paper addresses how to rebuilt measurement matrix for each type of faults. The proposed algorithm is shown that the method has high effectiveness and high performance for forecasting fault type and for estimating instantaneous bus voltage. The performance of the novel approach is tested on IEEE 14-bus test system and the results are shown

Zinc modulates several transcription-factor regulated pathways in mouse skeletal muscle cells

Zinc is an essential metal ion involved in many biological processes. Studies have shown that zinc can activate several molecules in the insulin signalling pathway and the concomitant uptake of glucose in skeletal muscle cells. However, there is limited information on other potential pathways that zinc can activate in skeletal muscle. Accordingly, this study aimed to identify other zinc-activating pathways in skeletal muscle cells to further delineate the role of this metal ion in cellular processes. Mouse C2C12 skeletal muscle cells were treated with insulin (10 nM), zinc (20 µM), and the zinc chelator TPEN (various concentrations) over 60 min. Western blots were performed for the zinc-activation of pAkt, pErk, and pCreb. A Cignal 45-Reporter Array that targets 45 signalling pathways was utilised to test the ability of zinc to activate pathways that have not yet been described. Zinc and insulin activated pAkt over 60 min as expected. Moreover, the treatment of C2C12 skeletal muscle cells with TPEN reduced the ability of zinc to activate pAkt and pErk. Zinc also activated several associated novel transcription factor pathways including Nrf1/Nrf2, ATF6, CREB, EGR1, STAT1, AP-1, PPAR, and TCF/LEF, and pCREB protein over 120 min of zinc treatment. These studies have shown that zinc’s activity extends beyond that of insulin signalling and plays a role in modulating novel transcription factor activated pathways. Further studies to determine the exact role of zinc in the activation of transcription factor pathways will provide novel insights into this metal ion actions

Reactive direction control for a mobile robot: A locust-like control of escape direction emerges when a bilateral pair of model locust visual neurons are integrated

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have been equipped with only a single, central artificial LGMD sensor, and this triggers a non-directional stop or rotation when a potentially colliding object is detected. Clearly, for a robot to behave autonomously, it must react differently to stimuli approaching from different directions. In this study, we implement a bilateral pair of LGMD models in Khepera robots equipped with normal and panoramic cameras. We integrate the responses of these LGMD models using methodologies inspired by research on escape direction control in cockroaches. Using ‘randomised winner-take-all’ or ‘steering wheel’ algorithms for LGMD model integration, the khepera robots could escape an approaching threat in real time and with a similar distribution of escape directions as real locusts. We also found that by optimising these algorithms, we could use them to integrate the left and right DCMD responses of real jumping locusts offline and reproduce the actual escape directions that the locusts took in a particular trial. Our results significantly advance the development of an artificial collision detection and evasion system based on the locust LGMD by allowing it reactive control over robot behaviour. The success of this approach may also indicate some important areas to be pursued in future biological research

DMRN+17: Digital Music Research Network One-day Workshop 2022

DMRN+17: Digital Music Research Network One-day Workshop 2022 Queen Mary University of London - Tuesday 20th December 2022. The Digital Music Research Network (DMRN) aims to promote research in the area of Digital Music, by bringing together researchers from UK and overseas universities and industry for its annual workshop. The workshop will include invited and contributed talks and posters. The workshop will be an ideal opportunity for networking with other people working in the area. Keynote speakers: Sander Dieleman Tittle: On generative modelling and iterative refinement. Bio: Sander Dieleman is a Research Scientist at DeepMind in London, UK, where he has worked on the development of AlphaGo and WaveNet. He obtained his PhD from Ghent University in 2016, where he conducted research on feature learning and deep learning techniques for learning hierarchical representations of musical audio signals. His current research interests include representation learning and generative modelling of perceptual signals such as speech, music and visual data. DMRN+17 is sponsored by The UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM); a leading PhD research programme aimed at the Music/Audio Technology and Creative Industries, based at Queen Mary University of London