Retrieval of Anomaly Details Using Vehicle Number Plate Identification for Traffic Guards

The ascent in number of vehicles makes different issues in regular daily existence. Arranging such substantial number of vehicles and transportation are intricate and tedious assignment. This paper centers over the above issue. This framework will consequently perceive the number plate of vehicles. The perceived number plate takes after the given strides: 1.To catch continuous picture of number plate. 2. To fragment and perceive characters at the server. 3. Perceived tag is shown on the graphical UI and furthermore put away in database alongside time and date for further utilize. 4. Book the complaint against the anomaly. The different methodologies for the issue are contemplated as takes after

Drosophila Parkin requires PINK1 for mitochondrial translocation and ubiquitinates Mitofusin

Loss of the E3 ubiquitin ligase Parkin causes early onset Parkinson's disease, a neurodegenerative disorder of unknown etiology. Parkin has been linked to multiple cellular processes including protein degradation, mitochondrial homeostasis, and autophagy; however, its precise role in pathogenesis is unclear. Recent evidence suggests that Parkin is recruited to damaged mitochondria, possibly affecting mitochondrial fission and/or fusion, to mediate their autophagic turnover. The precise mechanism of recruitment and the ubiquitination target are unclear. Here we show in Drosophila cells that PINK1 is required to recruit Parkin to dysfunctional mitochondria and promote their degradation. Furthermore, PINK1 and Parkin mediate the ubiquitination of the profusion factor Mfn on the outer surface of mitochondria. Loss of Drosophila PINK1 or parkin causes an increase in Mfn abundance in vivo and concomitant elongation of mitochondria. These findings provide a molecular mechanism by which the PINK1/Parkin pathway affects mitochondrial fission/fusion as suggested by previous genetic interaction studies. We hypothesize that Mfn ubiquitination may provide a mechanism by which terminally damaged mitochondria are labeled and sequestered for degradation by autophagy

Mapping ecologically sensitive, significant and salient areas of Western Ghats: proposed protocols and methodology

The Western Ghats Ecology Expert Panel (WGEEP) of the Ministry of Environment and Forests, Government of India (GOI) has been asked to identify ecologically sensitive areas (ESAs) along the Western Ghats, and to suggest how to manage them. The concept of ESAs has been extensively discussed in the literature. Several ESAs have been set up in India over the last 22 years under the Environment Protection Act, 1986, and a GOI committee under the chairmanship of Pranob Sen has proposed certain criteria for identification of ESAs. However, WGEEP noted that we still lack a global consensus either on the criteria to define ESAs or on a workable methodology to identify them. Furthermore, there are no clear guidelines on the management regime that should prevail in ESAs, and the Pranob Sen Committee has not addressed this issue at all. Hence, WGEEP decided to undertake an exercise of defining ESAs and developing a workable methodology to assign levels of ecological significance/sensitivity as a first step towards putting ESAs on the map of the Western Ghats. This article provides a report on the outcome of a series of discussions and consultations held by WGEEP to build a consensus on defining and mapping ESAs. It hopes to provoke discussion and feedback from a wider section of experts, with the aim of finalizing a generic methodology for mapping ESAs in other ecologically sign ificant, biodiversity-rich areas within and outside the country. We hope to shortly prepare a companion paper that will address the equally vital management issues

Earth Observations and Integrative Models in Support of Food and Water Security

Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries

AMBRA1 is able to induce mitophagy via LC3 binding, regardless of PARKIN and p62/SQSTM1

Damaged mitochondria are eliminated by mitophagy, a selective form of autophagy whose dysfunction associates with neurodegenerative diseases. PINK1, PARKIN and p62/SQTMS1 have been shown to regulate mitophagy, leaving hitherto ill-defined the contribution by key players in 'general' autophagy. In basal conditions, a pool of AMBRA1 - an upstream autophagy regulator and a PARKIN interactor - is present at the mitochondria, where its pro-autophagic activity is inhibited by Bcl-2. Here we show that, upon mitophagy induction, AMBRA1 binds the autophagosome adapter LC3 through a LIR (LC3 interacting region) motif, this interaction being crucial for regulating both canonical PARKIN-dependent and -independent mitochondrial clearance. Moreover, forcing AMBRA1 localization to the outer mitochondrial membrane unleashes a massive PARKIN- and p62-independent but LC3-dependent mitophagy. These results highlight a novel role for AMBRA1 as a powerful mitophagy regulator, through both canonical or noncanonical pathways

How do field of view and resolution affect the information content of panoramic scenes for visual navigation? A computational investigation

The visual systems of animals have to provide information to guide behaviour and the informational requirements of an animal’s behavioural repertoire are often reflected in its sensory system. For insects, this is often evident in the optical array of the compound eye. One behaviour that insects share with many animals is the use of learnt visual information for navigation. As ants are expert visual navigators it may be that their vision is optimised for navigation. Here we take a computational approach in asking how the details of the optical array influence the informational content of scenes used in simple view matching strategies for orientation. We find that robust orientation is best achieved with low-resolution visual information and a large field of view, similar to the optical properties seen for many ant species. A lower resolution allows for a trade-off between specificity and generalisation for stored views. Additionally, our simulations show that orientation performance increases if different portions of the visual field are considered as discrete visual sensors, each giving an independent directional estimate. This suggests that ants might benefit by processing information from their two eyes independently

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Automatic Planning and Control of Robot Natural Motion Via Feedback

A feedback control strategy for the command of robot motion includes some limited automatic planning capabilities. These may be seen as sequential solution algorithms implemented by the robot arm interpreted as a mechanical analog computer. This perspective lends additional insight into the manner in which such control techniques may fail, and motivates a fresh look at requisite sensory capabilities. For more information: Kod*La

Constraint solving in uncertain and dynamic environments - a survey

International audienceThis article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 (Ninth International Conference on Principles and Practice of Constraint Programming) in Kinsale, Ireland. It aims at offering an overview of the main approaches and techniques that have been proposed in the domain of constraint satisfaction to deal with uncertain and dynamic environments