Pressure measurement by Piezo-electric transducers in reciprocating combustion engines

The properties, use and construction of quartz Piezo electric transducers are briefly described. The dynamic calibration of quartz pressure transducers have been investigated using a Balanced-Disc pressure pick-up as a standard. The temperature effect on the static and dynamic output of these transducers has also been examined. Various types of engine indicators and their limitations are discussed. Piezo-electric pressure transducers and strain gauges were used for constructing an inertia-free pressure-volume indicator to produce a P-V diagram on an oscilloscope screen from which the trace was recorded. This included a simple and accurate method for obtaining top-dead-centre on pressure-time records. Some aspects of diesel combustion were considered using P-T diagrams from a variable compression Lister F.R.I diesel engine running at different loads and compression ratios. The effect of the shape of transducer passage on the accuracy of P-T diagrams is observed. Volumetric efficiency was measured using a crystal pressure transducer. The assumptions of this method was checked by comparison with the volumetric efficiency obtained by. two other established methods

Effect of 20-years crop rotation and different strategies of fertilization on weed seedbank

Crop rotation is thought to reduce weed density and maintain species diversity, preventing the domination of few competitive weeds. In this work rotations of 1, 2, 4 and 6 years length have been compared in a long-term experiment since 1976. In order to detect the effect of rotation length and fertilization on weed community evolution, a specific study was performed on weed seedbank with soil sampling in 1993 and 2012.Results: show that weed density was not affected by rotation length or fertilization type or rate, and that about 98% of weed species were indifferent to the factors applied. The dominance of Portulaca oleracea and increment of a few grass weeds were consequences of an inadequate management of late emergence and post-harvest weeds. Furthermore, no significant changes in the distribution of seeds longevity groups occurred in the seed-bank from 1993 to 2012. In cropping systems where herbicides are used according to best practices or to In-tegrated Weed Management principles, the effect of rotation on weeds is hard to detect even in long-term experiments. For this, the effect of herbicides must be included in a more general theory of rotational effects

Optimized Selection of Reliable and Cost-Effective Cyber-Physical System Architectures

We address the problem of synthesizing safety-critical cyber-physical system architectures to minimize a cost function while guaranteeing the desired reliability. We cast the problem as an integer linear program on a reconfigurable graph which models the architecture. Since generating symbolic probability constraints by exhaustive enumeration of failure cases on all possible graph configurations takes exponential time, we propose two algorithms to decrease the problem complexity, i.e. Integer-Linear Programming Modulo Reliability (ILP-MR) and Integer-Linear Programming with Approximate Reliability (ILP-AR). We compare the two approaches and demonstrate their effectiveness on the design of aircraft electric power system architectures

GLUT3 is induced during epithelial-mesenchymal transition and promotes tumor cell proliferation in non-small cell lung cancer.

BACKGROUND: Alterations in glucose metabolism and epithelial-mesenchymal transition (EMT) constitute two important characteristics of carcinoma progression toward invasive cancer. Despite an extensive characterization of each of them separately, the links between EMT and glucose metabolism of tumor cells remain elusive. Here we show that the neuronal glucose transporter GLUT3 contributes to glucose uptake and proliferation of lung tumor cells that have undergone an EMT. RESULTS: Using a panel of human non-small cell lung cancer (NSCLC) cell lines, we demonstrate that GLUT3 is strongly expressed in mesenchymal, but not epithelial cells, a finding corroborated in hepatoma cells. Furthermore, we identify that ZEB1 binds to the GLUT3 gene to activate transcription. Importantly, inhibiting GLUT3 expression reduces glucose import and the proliferation of mesenchymal lung tumor cells, whereas ectopic expression in epithelial cells sustains proliferation in low glucose. Using a large microarray data collection of human NSCLCs, we determine that GLUT3 expression correlates with EMT markers and is prognostic of poor overall survival. CONCLUSIONS: Altogether, our results reveal that GLUT3 is a transcriptional target of ZEB1 and that this glucose transporter plays an important role in lung cancer, when tumor cells loose their epithelial characteristics to become more invasive. Moreover, these findings emphasize the development of GLUT3 inhibitory drugs as a targeted therapy for the treatment of patients with poorly differentiated tumors

Optimization and deployment of CNNs at the Edge: The ALOHA experience

Deep learning (DL) algorithms have already proved their effectiveness on a wide variety of application domains, including speech recognition, natural language processing, and image classification. To foster their pervasive adoption in applications where low latency, privacy issues and data bandwidth are paramount, the current trend is to perform inference tasks at the edge. This requires deployment of DL algorithms on low-energy and resource-constrained computing nodes, often heterogenous and parallel, that are usually more complex to program and to manage without adequate support and experience. In this paper, we present ALOHA, an integrated tool flow that tries to facilitate the design of DL applications and their porting on embedded heterogenous architectures. The proposed tool flow aims at automating different design steps and reducing development costs. ALOHA considers hardware-related variables and security, power efficiency, and adaptivity aspects during the whole development process, from pre-training hyperparameter optimization and algorithm configuration to deployment