Adsorption of Cationic Surface Active Agents at Barium Sulphate/Solution Interface

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Broad activation of the ubiquitin-proteasome system by Parkin is critical for mitophagy

Parkin, an E3 ubiquitin ligase implicated in Parkinson's disease, promotes degradation of dysfunctional mitochondria by autophagy. Using proteomic and cellular approaches, we show that upon translocation to mitochondria, Parkin activates the ubiquitin–proteasome system (UPS) for widespread degradation of outer membrane proteins. This is evidenced by an increase in K48-linked polyubiquitin on mitochondria, recruitment of the 26S proteasome and rapid degradation of multiple outer membrane proteins. The degradation of proteins by the UPS occurs independently of the autophagy pathway, and inhibition of the 26S proteasome completely abrogates Parkin-mediated mitophagy in HeLa, SH-SY5Y and mouse cells. Although the mitofusins Mfn1 and Mfn2 are rapid degradation targets of Parkin, we find that degradation of additional targets is essential for mitophagy. These results indicate that remodeling of the mitochondrial outer membrane proteome is important for mitophagy, and reveal a causal link between the UPS and autophagy, the major pathways for degradation of intracellular substrates

A Composite Trust Model for Secure Routing in Mobile Ad-Hoc Networks

It is imperative to address the issue of secure routing in mobile ad-hoc networks (MANETs) where the nodes seek for cooperative and trusted behaviour from the peer nodes in the absence of well-established infrastructure and centralized authority. Due to the inherent absence of security considerations in the traditional ad-hoc routing protocols, providing security and reliability in the routing of data packets is a major challenge. This work addresses this issue by proposing a composite trust metric based on the concept of social trust and quality-of-service (QoS) trust. Extended from the ad-hoc on-demand distance vector (AODV) routing protocol, we propose an enhanced trust-based model integrated with an attack-pattern discovery mechanism, which attempts to mitigate the adversaries craving to carry out distinct types of packet-forwarding misbehaviours. We present the detailed mode of operations of three distinct adversary models against which the proposed scheme is evaluated. Simulation results under different network conditions depict that the combination of social and QoS trust components provides significant improvement in packet delivery ratio, routing overhead, and energy consumption compared to an existing trust-based scheme

Neural Modeling and Control of Diesel Engine with Pollution Constraints

The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identification and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are flexible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The presented work extends optimal neuro-control to the multivariable case and shows the flexibility of neural optimisers. Considering the preliminary results, it appears that neural networks can be used as embedded models for engine control, to satisfy the more and more restricting pollutant emission legislation. Particularly, they are able to model nonlinear dynamics and outperform during transients the control schemes based on static mappings.Comment: 15 page

Study of seasonal incidence and impact of abiotic factors on sucking pests of brinjal

The present investigation was undertaken to find the impact of abiotic factors on seasonal incidence and sucking pest complex of brinjal under field conditions during kharif 2015-2016. The incidence of leaf hopper population (2.80 Lh/L i.e., Leaf hopper mean population/leaf) was noticed during 34th standard week and reached peak by 40th standard week (5.00 Lh/L) (October) whereas the aphid population was noticed during the 34th standard week (3.00 Lh/L) and peak population observed during the 40th standard week (4.60 Lh/L) (October). Correlation studies showed that among the various abiotic factors, maximum temperature showed highly significant positive correlation (r= 0.77) and sunshine hours (r = 0.61) showed significant positive correlation with the leaf hopper population. In case of aphid population, maximum temperature showed significant positive correlation (r = 0.70), rainfall showed highly significant negative correlation (r = -0.74) and relative humidity evening (r = -0.59) showed significant negative correlation with aphid population. The present investigations will give a brief idea about how the abiotic factors influencing the sucking pests of brinjal

Inflation in minimal left-right symmetric model with spontaneous D-parity breaking

We present a simplest inflationary scenario in the minimal left-right symmetric model with spontaneous D-parity breaking, which is a well motivated particle physics model for neutrino masses. This leads us to connect the observed anisotropies in the cosmic microwave background to the sub-eV neutrino masses. The baryon asymmetry via the leptogenesis route is also discussed briefly.Comment: (v1) 4 pages, 1 figure; (v2) typos corrected; (v3) title and abstract changed, numerical estimates given, minor changes; (v4) 5 pages, relations between the neutrino masses and the CMB fluctuations become more explicit, miscellaneous changes, to appear in Physical Review

A Learning Automata Based Solution to Service Selection in Stochastic Environments

With the abundance of services available in today’s world, identifying those of high quality is becoming increasingly difficult. Reputation systems can offer generic recommendations by aggregating user provided opinions about service quality, however, are prone to ballot stuffing and badmouthing . In general, unfair ratings may degrade the trustworthiness of reputation systems, and changes in service quality over time render previous ratings unreliable. In this paper, we provide a novel solution to the above problems based on Learning Automata (LA), which can learn the optimal action when operating in unknown stochastic environments. Furthermore, they combine rapid and accurate convergence with low computational complexity. In additional to its computational simplicity, unlike most reported approaches, our scheme does not require prior knowledge of the degree of any of the above mentioned problems with reputation systems. Instead, it gradually learns which users provide fair ratings, and which users provide unfair ratings, even when users unintentionally make mistakes. Comprehensive empirical results show that our LA based scheme efficiently handles any degree of unfair ratings (as long as ratings are binary). Furthermore, if the quality of services and/or the trustworthiness of users change, our scheme is able to robustly track such changes over time. Finally, the scheme is ideal for decentralized processing. Accordingly, we believe that our LA based scheme forms a promising basis for improving the performance of reputation systems in general

Prospective, non-randomized, parallel group, comparative observational study to compare maternal and neonatal outcome after regional and general anesthesia for Lower Segment Caesarean Section

Background: LSCS is a routine obstetric procedure performed under general anesthesia (GA) or regional anesthesia (RA). Choice of anesthesia depends on factors like gestational age, parity, co-morbidities, urgency of situation, etc. Both GA and RA involve the use of various medications which may influence maternal and neonatal outcome. As there are few studies comparing maternal and fetal outcome in RA and GA for LSCS in Indian population, the present study was taken up. Objectives of the study was to compare the maternal and neonatal outcome after RA and GA for LSCS.Methods: 60 subjects with indications for LSCS were assigned non-randomly into two groups, 30 for GA and 30 for RA, at the discretion of anesthesiologist. The demographic, anthropometric and clinical data was recorded for all subjects. The maternal outcome after RA and GA for LSCS was assessed by parameters like maternal blood loss, postoperative pain, postoperative nausea and vomiting, maternal satisfaction and neonatal outcome by parameters like birth weight, APGAR scores and NICU admissions. The maternal and neonatal outcome between the two groups was compared.Results: All subjects had clear indications for CS. In most of the subjects it was undertaken as an emergency procedure. GA was preferred in high risk subjects. Maternal blood loss, postoperative pain, NICU admissions, need for resuscitation was less under RA compared to GA. There was no difference in PONV, maternal satisfaction, birth weight and need for intubation.Conclusions: LSCS under RA showed a more favourable maternal and neonatal outcome

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

Decentralised Learning MACs for Collision-free Access in WLANs

By combining the features of CSMA and TDMA, fully decentralised WLAN MAC schemes have recently been proposed that converge to collision-free schedules. In this paper we describe a MAC with optimal long-run throughput that is almost decentralised. We then design two \changed{schemes} that are practically realisable, decentralised approximations of this optimal scheme and operate with different amounts of sensing information. We achieve this by (1) introducing learning algorithms that can substantially speed up convergence to collision free operation; (2) developing a decentralised schedule length adaptation scheme that provides long-run fair (uniform) access to the medium while maintaining collision-free access for arbitrary numbers of stations